NASA Astrophysics Data System (ADS)
Porello, Daniele
The aim of this paper is to propose a methodology for evaluating the quality of collective decisions in sociotechnical systems (STS). We propose using a foundational ontology for conceptualizing the complex hierarchy of information involved in decisions in STS (e.g., normative, conceptual, factual, perceptual). Moreover, we introduce the concept of transparency of decisions as a necessary condition in order to assess the quality of decision-making in STS. We further view transparency as an entitlement of the agent affected by the decision: i.e., the collective decision should be justified.
Somatic Markers and Explicit Knowledge Are both Involved in Decision-Making
ERIC Educational Resources Information Center
Guillaume, Sebastien; Jollant, Fabrice; Jaussent, Isabelle; Lawrence, Natalia; Malafosse, Alain; Courtet, Philippe
2009-01-01
In 1994, it was proposed that decision-making requires emotion-related signals, known as somatic markers. In contrast, some authors argued that conscious knowledge of contingencies is sufficient for advantageous decision-making. We aimed to investigate the respective roles of somatic markers and explicit knowledge in decision-making. Thirty…
Understanding the Role of Numeracy in Health: Proposed Theoretical Framework and Practical Insights
Lipkus, Isaac M.; Peters, Ellen
2009-01-01
Numeracy, that is how facile people are with mathematical concepts and their applications, is gaining importance in medical decision making and risk communication. This paper proposes six critical functions of health numeracy. These functions are integrated into a theoretical framework on health numeracy that has implications for risk-communication and medical-decision-making processes. We examine practical underpinnings for targeted interventions aimed at improving such processes as a function of health numeracy. It is hoped that the proposed functions and theoretical framework will spur more research to determine how an understanding of health numeracy can lead to more effective communication and decision outcomes. PMID:19834054
NASA Astrophysics Data System (ADS)
Heydari, Jafar; Norouzinasab, Yousef
2015-12-01
In this paper, a discount model is proposed to coordinate pricing and ordering decisions in a two-echelon supply chain (SC). Demand is stochastic and price sensitive while lead times are fixed. Decentralized decision making where downstream decides on selling price and order size is investigated. Then, joint pricing and ordering decisions are extracted where both members act as a single entity aim to maximize whole SC profit. Finally, a coordination mechanism based on quantity discount is proposed to coordinate both pricing and ordering decisions simultaneously. The proposed two-level discount policy can be characterized from two aspects: (1) marketing viewpoint: a retail price discount to increase the demand, and (2) operations management viewpoint: a wholesale price discount to induce the retailer to adjust its order quantity and selling price jointly. Results of numerical experiments demonstrate that the proposed policy is suitable to coordinate SC and improve the profitability of SC as well as all SC members in comparison with decentralized decision making.
A model for making project funding decisions at the National Cancer Institute.
Hall, N G; Hershey, J C; Kessler, L G; Stotts, R C
1992-01-01
This paper describes the development of a model for making project funding decisions at The National Cancer Institute (NCI). The American Stop Smoking Intervention Study (ASSIST) is a multiple-year, multiple-site demonstration project, aimed at reducing smoking prevalence. The initial request for ASSIST proposals was answered by about twice as many states as could be funded. Scientific peer review of the proposals was the primary criterion used for funding decisions. However, a modified Delphi process made explicit several criteria of secondary importance. A structured questionnaire identified the relative importance of these secondary criteria, some of which we incorporated into a composite preference function. We modeled the proposal funding decision as a zero-one program, and adjusted the preference function and available budget parametrically to generate many suitable outcomes. The actual funding decision, identified by our model, offers significant advantages over manually generated solutions found by experts at NCI.
[Interoception and decision-making].
Ohira, Hideki
2015-02-01
We sometimes make decisions relying not necessarily on deliberative thoughts but on intuitive and emotional processes in uncertain situations. The somatic marker hypothesis proposed by Damasio argued that interoception, which means bodily responses such as sympathetic activity, can be represented in the insula and anterior cingulate cortex and can play critical roles in decision-making. Though this hypothesis has been criticized in its theoretical and empirical aspects, recent studies are expanding the hypothesis to elucidate multiple bodily responses including autonomic, endocrine, and immune activities that affect decision-making. In addition, cumulative findings suggest that the anterior insula where the inner model of interoception is represented can act as an interface between the brain and body in decision-making. This article aims to survey recent findings on the brain-body interplays underlying decision-making, and to propose hypotheses on the significance of the body in decision-making.
Shared decision-making as an existential journey: Aiming for restored autonomous capacity.
Gulbrandsen, Pål; Clayman, Marla L; Beach, Mary Catherine; Han, Paul K; Boss, Emily F; Ofstad, Eirik H; Elwyn, Glyn
2016-09-01
We describe the different ways in which illness represents an existential problem, and its implications for shared decision-making. We explore core concepts of shared decision-making in medical encounters (uncertainty, vulnerability, dependency, autonomy, power, trust, responsibility) to interpret and explain existing results and propose a broader understanding of shared-decision making for future studies. Existential aspects of being are physical, social, psychological, and spiritual. Uncertainty and vulnerability caused by illness expose these aspects and may lead to dependency on the provider, which underscores that autonomy is not just an individual status, but also a varying capacity, relational of nature. In shared decision-making, power and trust are important factors that may increase as well as decrease the patient's dependency, particularly as information overload may increase uncertainty. The fundamental uncertainty, state of vulnerability, and lack of power of the ill patient, imbue shared decision-making with a deeper existential significance and call for greater attention to the emotional and relational dimensions of care. Hence, we propose that the aim of shared decision-making should be restoration of the patient's autonomous capacity. In doing shared decision-making, care is needed to encompass existential aspects; informing and exploring preferences is not enough. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
ERIC Educational Resources Information Center
Indhraratana, Apinya; Kaemkate, Wannee
2012-01-01
The aim of this paper is to develop a reliable and valid tool to assess ethical decision-making ability of nursing students using rubrics. A proposed ethical decision making process, from reviewing related literature was used as a framework for developing the rubrics. Participants included purposive sample of 86 nursing students from the Royal…
EEG feature selection method based on decision tree.
Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun
2015-01-01
This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.
Zhang, Mingyuan; Velasco, Ferdinand T.; Musser, R. Clayton; Kawamoto, Kensaku
2013-01-01
Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426
Health care workers and their needs: the forgotten shadow of AIM research.
Lillehaug, S I; Lajoie, S
1998-01-01
The field of AI in Medicine (AIM) seems to have accepted that decision support is, and will be, needed within most medical domains. As society calls for cost-effectiveness, and human expertise or expert guidance are not always available, decision support systems (DSSs) are proposed as the solutions. These solutions, however, do not necessarily correspond with the basic needs of their targeted users. We will show this through a review of the literature related to health care workers and the various factors that have an influence on their performances. Furthermore, we will use these empirical findings to argue that the AIM community must go beyond its decision support philosophy, whereby the gaps in human expertise are filled in by the computer. In the future, joint emphasis must be placed on decision support and the promotion towards independent and self-sufficient problem solving. In order to implement this paradigm change, the AIM community will have to incorporate findings from the research discipline of AI in Education.
A Core Journal Decision Model Based on Weighted Page Rank
ERIC Educational Resources Information Center
Wang, Hei-Chia; Chou, Ya-lin; Guo, Jiunn-Liang
2011-01-01
Purpose: The paper's aim is to propose a core journal decision method, called the local impact factor (LIF), which can evaluate the requirements of the local user community by combining both the access rate and the weighted impact factor, and by tracking citation information on the local users' articles. Design/methodology/approach: Many…
Free Schools in the Big Society: The Motivations, Aims and Demography of Free School Proposers
ERIC Educational Resources Information Center
Higham, Rob
2014-01-01
Free school policy claims to partly decentralise to local proposers decisions over who provides a free school, where and for what reasons, within the constraints of a government approval process. This article analyses empirically the people and organisations doing the proposing and their interactions with the approval process. The article begins…
Frantzidis, Christos A; Gilou, Sotiria; Billis, Antonis; Karagianni, Maria; Bratsas, Charalampos D; Bamidis, Panagiotis
2016-03-01
Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community.
Analytic hierarchy process (AHP) as a tool in asset allocation
NASA Astrophysics Data System (ADS)
Zainol Abidin, Siti Nazifah; Mohd Jaffar, Maheran
2013-04-01
Allocation capital investment into different assets is the best way to balance the risk and reward. This can prevent from losing big amount of money. Thus, the aim of this paper is to help investors in making wise investment decision in asset allocation. This paper proposes modifying and adapting Analytic Hierarchy Process (AHP) model. The AHP model is widely used in various fields of study that are related in decision making. The results of the case studies show that the proposed model can categorize stocks and determine the portion of capital investment. Hence, it can assist investors in decision making process and reduce the risk of loss in stock market investment.
Teaching Behavioral Ethics: Overcoming the Key Impediments to Ethical Behavior
ERIC Educational Resources Information Center
Schwartz, Mark S.
2017-01-01
To better understand the ethical decision-making process and why individuals fail to act ethically, the aim of this article is to explore what are seen as the key impediments to ethical behavior and their pedagogical implications. Using the ethical decision-making process proposed by Rest as an overarching framework, the article examines the…
Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.
Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik
2016-01-01
Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.
Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees
Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng
2015-01-01
In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597
A vertical handoff decision algorithm based on ARMA prediction model
NASA Astrophysics Data System (ADS)
Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan
2012-01-01
With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.
2012-01-01
Clinical decision rules are an increasingly common presence in the biomedical literature and represent one strategy of enhancing clinical-decision making with the goal of improving the efficiency and effectiveness of healthcare delivery. In the context of rehabilitation research, clinical decision rules have been predominantly aimed at classifying patients by predicting their treatment response to specific therapies. Traditionally, recommendations for developing clinical decision rules propose a multistep process (derivation, validation, impact analysis) using defined methodology. Research efforts aimed at developing a “diagnosis-based clinical decision rule” have departed from this convention. Recent publications in this line of research have used the modified terminology “diagnosis-based clinical decision guide.” Modifications to terminology and methodology surrounding clinical decision rules can make it more difficult for clinicians to recognize the level of evidence associated with a decision rule and understand how this evidence should be implemented to inform patient care. We provide a brief overview of clinical decision rule development in the context of the rehabilitation literature and two specific papers recently published in Chiropractic and Manual Therapies. PMID:22726639
Emotion-affected decision making in human simulation.
Zhao, Y; Kang, J; Wright, D K
2006-01-01
Human modelling is an interdisciplinary research field. The topic, emotion-affected decision making, was originally a cognitive psychology issue, but is now recognized as an important research direction for both computer science and biomedical modelling. The main aim of this paper is to attempt to bridge the gap between psychology and bioengineering in emotion-affected decision making. The work is based on Ortony's theory of emotions and bounded rationality theory, and attempts to connect the emotion process with decision making. A computational emotion model is proposed, and the initial framework of this model in virtual human simulation within the platform of Virtools is presented.
Hultberg, Josabeth; Rudebeck, Carl Edvard
2017-09-01
The aim of the study was to describe and explore patient agency through resistance in decision-making about cardiovascular preventive drugs in primary care. Six general practitioners from the southeast of Sweden audiorecorded 80 consultations. From these, 28 consultations with proposals from GPs for cardiovascular preventive drug treatments were chosen for theme-oriented discourse analysis. The study shows how patients participate in decision-making about cardiovascular preventive drug treatments through resistance in response to treatment proposals. Passive modes of resistance were withheld responses and minimal unmarked acknowledgements. Active modes were to ask questions, contest the address of an inclusive we, present an identity as a non-drugtaker, disclose non-adherence to drug treatments, and to present counterproposals. The active forms were also found in anticipation to treatment proposals from the GPs. Patients and GPs sometimes displayed mutual renouncement of responsibility for decision-making. The decision-making process appeared to expand both beyond a particular phase in the consultations and beyond the single consultation. The recognition of active and passive resistance from patients as one way of exerting agency may prove valuable when working for patient participation in clinical practice, education and research about patient-doctor communication about cardiovascular preventive medication. We propose particular attentiveness to patient agency through anticipatory resistance, patients' disclosures of non-adherence and presentations of themselves as non-drugtakers. The expansion of the decision-making process beyond single encounters points to the importance of continuity of care. KEY POINTS Guidelines recommend shared decision-making about cardiovascular preventive treatment. We need an understanding of how this is accomplished in actual consultations.This paper describes how patient agency in decision-making is displayed through different forms of resistance to treatment proposals. •The decision-making process expands beyond particular phases in consultations and beyond single encounters, implying the importance of continuity of care. •Attentiveness to patient participation through resistance in treatment negotiations is warranted in clinical practice, research and education about prescribing communication.
Effect of Wind Farm Noise on Local Residents' Decision to Adopt Mitigation Measures.
Botelho, Anabela; Arezes, Pedro; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M Costa
2017-07-11
Wind turbines' noise is frequently pointed out as the reason for local communities' objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes' noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people's decision to adopt mitigating measures, independently of the reported annoyance.
Evolving optimised decision rules for intrusion detection using particle swarm paradigm
NASA Astrophysics Data System (ADS)
Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.
2012-12-01
The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.
Network switching strategy for energy conservation in heterogeneous networks.
Song, Yujae; Choi, Wooyeol; Baek, Seungjae
2017-01-01
In heterogeneous networks (HetNets), the large-scale deployment of small base stations (BSs) together with traditional macro BSs is an economical and efficient solution that is employed to address the exponential growth in mobile data traffic. In dense HetNets, network switching, i.e., handovers, plays a critical role in connecting a mobile terminal (MT) to the best of all accessible networks. In the existing literature, a handover decision is made using various handover metrics such as the signal-to-noise ratio, data rate, and movement speed. However, there are few studies on handovers that focus on energy efficiency in HetNets. In this paper, we propose a handover strategy that helps to minimize energy consumption at BSs in HetNets without compromising the quality of service (QoS) of each MT. The proposed handover strategy aims to capture the effect of the stochastic behavior of handover parameters and the expected energy consumption due to handover execution when making a handover decision. To identify the validity of the proposed handover strategy, we formulate a handover problem as a constrained Markov decision process (CMDP), by which the effects of the stochastic behaviors of handover parameters and consequential handover energy consumption can be accurately reflected when making a handover decision. In the CMDP, the aim is to minimize the energy consumption to service an MT over the lifetime of its connection, and the constraint is to guarantee the QoS requirements of the MT given in terms of the transmission delay and call-dropping probability. We find an optimal policy for the CMDP using a combination of the Lagrangian method and value iteration. Simulation results verify the validity of the proposed handover strategy.
Modular Architecture for Integrated Model-Based Decision Support.
Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen
2018-01-01
Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.
A rough set approach for determining weights of decision makers in group decision making.
Yang, Qiang; Du, Ping-An; Wang, Yong; Liang, Bin
2017-01-01
This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs' decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member' decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs' evaluations and selections.
A knowledge-based patient assessment system: conceptual and technical design.
Reilly, C. A.; Zielstorff, R. D.; Fox, R. L.; O'Connell, E. M.; Carroll, D. L.; Conley, K. A.; Fitzgerald, P.; Eng, T. K.; Martin, A.; Zidik, C. M.; Segal, M.
2000-01-01
This paper describes the design of an inpatient patient assessment application that captures nursing assessment data using a wireless laptop computer. The primary aim of this system is to capture structured information for facilitating decision support and quality monitoring. The system also aims to improve efficiency of recording patient assessments, reduce costs, and improve discharge planning and early identification of patient learning needs. Object-oriented methods were used to elicit functional requirements and to model the proposed system. A tools-based development approach is being used to facilitate rapid development and easy modification of assessment items and rules for decision support. Criteria for evaluation include perceived utility by clinician users, validity of decision support rules, time spent recording assessments, and perceived utility of aggregate reports for quality monitoring. PMID:11079970
A knowledge-based patient assessment system: conceptual and technical design.
Reilly, C A; Zielstorff, R D; Fox, R L; O'Connell, E M; Carroll, D L; Conley, K A; Fitzgerald, P; Eng, T K; Martin, A; Zidik, C M; Segal, M
2000-01-01
This paper describes the design of an inpatient patient assessment application that captures nursing assessment data using a wireless laptop computer. The primary aim of this system is to capture structured information for facilitating decision support and quality monitoring. The system also aims to improve efficiency of recording patient assessments, reduce costs, and improve discharge planning and early identification of patient learning needs. Object-oriented methods were used to elicit functional requirements and to model the proposed system. A tools-based development approach is being used to facilitate rapid development and easy modification of assessment items and rules for decision support. Criteria for evaluation include perceived utility by clinician users, validity of decision support rules, time spent recording assessments, and perceived utility of aggregate reports for quality monitoring.
NASA Astrophysics Data System (ADS)
Al-Qudaimi, Abdullah; Kumar, Amit
2018-05-01
Recently, Abdullah and Najib (International Journal of Sustainable Energy 35(4): 360-377, 2016) proposed an intuitionistic fuzzy analytic hierarchy process to deal with uncertainty in decision-making and applied it to establish preference in the sustainable energy planning decision-making of Malaysia. This work may attract the researchers of other countries to choose energy technology for their countries. However, after a deep study of the published paper (International Journal of Sustainable Energy 35(4): 362-377, 2016), it is noticed that the expression used by Abdullah and Najib in Step 6 of their proposed method for evaluating the intuitionistic fuzzy entropy of each aggregate of each row of intuitionistic fuzzy matrix is not valid. Therefore, it is not genuine to use the method proposed by Abdullah and Najib for solving real-life problems. The aim of this paper was to suggest the required necessary modifications for resolving the flaws of the Abdullah and Najib method.
NASA Astrophysics Data System (ADS)
Kong, Gyuyeol; Choi, Sooyong
2017-09-01
An enhanced 2/3 four-ary modulation code using soft-decision Viterbi decoding is proposed for four-level holographic data storage systems. While the previous four-ary modulation codes focus on preventing maximum two-dimensional intersymbol interference patterns, the proposed four-ary modulation code aims at maximizing the coding gains for better bit error rate performances. For achieving significant coding gains from the four-ary modulation codes, we design a new 2/3 four-ary modulation code in order to enlarge the free distance on the trellis through extensive simulation. The free distance of the proposed four-ary modulation code is extended from 1.21 to 2.04 compared with that of the conventional four-ary modulation code. The simulation result shows that the proposed four-ary modulation code has more than 1 dB gains compared with the conventional four-ary modulation code.
Hultberg, Josabeth; Rudebeck, Carl Edvard
2017-01-01
Objective The aim of the study was to describe and explore patient agency through resistance in decision-making about cardiovascular preventive drugs in primary care. Design Six general practitioners from the southeast of Sweden audiorecorded 80 consultations. From these, 28 consultations with proposals from GPs for cardiovascular preventive drug treatments were chosen for theme-oriented discourse analysis. Results The study shows how patients participate in decision-making about cardiovascular preventive drug treatments through resistance in response to treatment proposals. Passive modes of resistance were withheld responses and minimal unmarked acknowledgements. Active modes were to ask questions, contest the address of an inclusive we, present an identity as a non-drugtaker, disclose non-adherence to drug treatments, and to present counterproposals. The active forms were also found in anticipation to treatment proposals from the GPs. Patients and GPs sometimes displayed mutual renouncement of responsibility for decision-making. The decision-making process appeared to expand both beyond a particular phase in the consultations and beyond the single consultation. Conclusions The recognition of active and passive resistance from patients as one way of exerting agency may prove valuable when working for patient participation in clinical practice, education and research about patient–doctor communication about cardiovascular preventive medication. We propose particular attentiveness to patient agency through anticipatory resistance, patients’ disclosures of non-adherence and presentations of themselves as non-drugtakers. The expansion of the decision-making process beyond single encounters points to the importance of continuity of care. KEY POINTS Guidelines recommend shared decision-making about cardiovascular preventive treatment. We need an understanding of how this is accomplished in actual consultations.This paper describes how patient agency in decision-making is displayed through different forms of resistance to treatment proposals. •The decision-making process expands beyond particular phases in consultations and beyond single encounters, implying the importance of continuity of care. •Attentiveness to patient participation through resistance in treatment negotiations is warranted in clinical practice, research and education about prescribing communication. PMID:28277056
Effect of Wind Farm Noise on Local Residents’ Decision to Adopt Mitigation Measures
Botelho, Anabela; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M. Costa
2017-01-01
Wind turbines’ noise is frequently pointed out as the reason for local communities’ objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes’ noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people’s decision to adopt mitigating measures, independently of the reported annoyance. PMID:28696404
Proctor Creek Boone Boulevard Health Impact Assessment (HIA) Final Report
This is the final report of the EPA-led Proctor Creek Boone Boulevard HIA, which aims to help inform the City of Atlanta’s decision on whether to implement the proposed Boone Boulevard Green Street Project as designed.
A rough set approach for determining weights of decision makers in group decision making
Yang, Qiang; Du, Ping-an; Wang, Yong; Liang, Bin
2017-01-01
This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs’ decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member’ decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs’ evaluations and selections. PMID:28234974
NASA Astrophysics Data System (ADS)
Przybyła-Kasperek, M.; Wakulicz-Deja, A.
2017-05-01
Issues related to decision making based on dispersed knowledge are discussed in the paper. A dispersed decision-making system, which was proposed by the authors in previous articles, is used in this paper. In the system, a process of combining classifiers into coalitions with a negotiation stage is realized. The novelty that is proposed in this article involves the use of six different methods of conflict analysis that are known from the literature.The main purpose of the tests, which were performed, was to compare the methods from the two groups - the abstract level and the rank level. An additional aim was to investigate the efficiency of the fusion methods used in a dispersed system with a dynamic structure with the efficiency that is obtained when no structure is used. Conclusions were drawn that, in most cases, the use of a dispersed system improves the efficiency of inference.
NASA Astrophysics Data System (ADS)
Wu, Shanhua; Yang, Zhongzhen
2018-07-01
This paper aims to optimize the locations of manufacturing industries in the context of economic globalization by proposing a bi-level programming model which integrates the location optimization model with the traffic assignment model. In the model, the transport network is divided into the subnetworks of raw materials and products respectively. The upper-level model is used to determine the location of industries and the OD matrices of raw materials and products. The lower-level model is used to calculate the attributes of traffic flow under given OD matrices. To solve the model, the genetic algorithm is designed. The proposed method is tested using the Chinese steel industry as an example. The result indicates that the proposed method could help the decision-makers to implement the location decisions for the manufacturing industries effectively.
Alamaniotis, Miltiadis; Agarwal, Vivek
2014-04-01
Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less
Multi-test decision tree and its application to microarray data classification.
Czajkowski, Marcin; Grześ, Marek; Kretowski, Marek
2014-05-01
The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the hierarchical process of human decision making. However, existing algorithms for learning decision trees have tendency to underfit gene expression data. The main aim of this work is to improve the performance and stability of decision trees with only a small increase in their complexity. We propose a multi-test decision tree (MTDT); our main contribution is the application of several univariate tests in each non-terminal node of the decision tree. We also search for alternative, lower-ranked features in order to obtain more stable and reliable predictions. Experimental validation was performed on several real-life gene expression datasets. Comparison results with eight classifiers show that MTDT has a statistically significantly higher accuracy than popular decision tree classifiers, and it was highly competitive with ensemble learning algorithms. The proposed solution managed to outperform its baseline algorithm on 14 datasets by an average 6%. A study performed on one of the datasets showed that the discovered genes used in the MTDT classification model are supported by biological evidence in the literature. This paper introduces a new type of decision tree which is more suitable for solving biological problems. MTDTs are relatively easy to analyze and much more powerful in modeling high dimensional microarray data than their popular counterparts. Copyright © 2014 Elsevier B.V. All rights reserved.
Fuzzy-based decision strategy in real-time strategic games
NASA Astrophysics Data System (ADS)
Volna, Eva
2017-11-01
The aim of this article is to describe our own gaming artificial intelligence for OpenTTD, which is a real-time building strategy game. A multi-agent system with fuzzy decision-making was used for the proposal itself. The multiagent system was chosen because real-time strategy games achieve great complexity and require decomposition of the problem into individual problems, which are then solved by individual cooperating agents. The system becomes then more stable and easily expandable. The fuzzy approach makes the decision-making process of strategies easier thanks to the use of uncertainty. In the conclusion, own experimental results were compared with other approaches.
Toupin-April, Karine; Barton, Jennifer; Fraenkel, Liana; Li, Linda; Grandpierre, Viviane; Guillemin, Francis; Rader, Tamara; Stacey, Dawn; Légaré, France; Jull, Janet; Petkovic, Jennifer; Scholte-Voshaar, Marieke; Welch, Vivian; Lyddiatt, Anne; Hofstetter, Cathie; De Wit, Maarten; March, Lyn; Meade, Tanya; Christensen, Robin; Gaujoux-Viala, Cécile; Suarez-Almazor, Maria E; Boonen, Annelies; Pohl, Christoph; Martin, Richard; Tugwell, Peter S
2015-12-01
Despite the importance of shared decision making for delivering patient-centered care in rheumatology, there is no consensus on how to measure its process and outcomes. The aim of this Outcome Measures in Rheumatology (OMERACT) working group is to determine the core set of domains for measuring shared decision making in intervention studies in adults with osteoarthritis (OA), from the perspectives of patients, health professionals, and researchers. We followed the OMERACT Filter 2.0 method to develop a draft core domain set by (1) forming an OMERACT working group; (2) conducting a review of domains of shared decision making; and (3) obtaining opinions of all those involved using a modified nominal group process held at a session activity at the OMERACT 12 meeting. In all, 26 people from Europe, North America, and Australia, including 5 patient research partners, participated in the session activity. Participants identified the following domains for measuring shared decision making to be included as part of the draft core set: (1) identifying the decision, (2) exchanging information, (3) clarifying views, (4) deliberating, (5) making the decision, (6) putting the decision into practice, and (7) assessing the effect of the decision. Contextual factors were also suggested. We proposed a draft core set of shared decision-making domains for OA intervention research studies. Next steps include a workshop at OMERACT 13 to reach consensus on these proposed domains in the wider OMERACT group, as well as to detail subdomains and assess instruments to develop a core outcome measurement set.
Toupin April, Karine; Barton, Jennifer; Fraenkel, Liana; Li, Linda; Grandpierre, Viviane; Guillemin, Francis; Rader, Tamara; Stacey, Dawn; Légaré, France; Jull, Janet; Petkovic, Jennifer; Scholte Voshaar, Marieke; Welch, Vivian; Lyddiatt, Anne; Hofstetter, Cathie; De Wit, Maarten; March, Lyn; Meade, Tanya; Christensen, Robin; Gaujoux-Viala, Cécile; Suarez-Almazor, Maria E.; Boonen, Annelies; Pohl, Christoph; Martin, Richard; Tugwell, Peter
2015-01-01
Objective Despite the importance of shared decision making for delivering patient-centred care in rheumatology, there is no consensus on how to measure its process and outcomes. The aim of this OMERACT working group is to determine the core set of domains for measuring shared decision making in intervention studies in adults with osteoarthritis (OA), from the perspective of patients, health professionals and researchers. Methods We followed the OMERACT Filter 2.0 to develop a draft core domain set, which consisted of: (i) forming an OMERACT working group; (ii) conducting a review of domains of shared decision making; and (iii) obtaining the opinions of stakeholders using a modified nominal group process held at a session activity at the OMERACT 2014 meeting. Results 26 stakeholders from Europe, North America and Australia, including 5 patient research partners, participated in the session activity. Participants identified the following domains for measuring shared decision making to be included as part of the Draft Core Set: 1) Identifying the decision; 2) Exchanging Information; 3) Clarifying views; 4) Deliberating; 5) Making the decision; 6) Putting the decision into practice; and 7) Assessing the impact of the decision. Contextual factors were also suggested. Conclusion We propose a Draft Core Set of shared decision making domains for OA intervention research studies. Next steps include a workshop at OMERACT 2016 to reach consensus on these proposed domains in the wider OMERACT group, as well as detail sub-domains and assess instruments to develop a Core Outcome Measurement Set. PMID:25877502
Banner, Natalie F.
2016-01-01
Capacity legislation aims to protect individual autonomy and avoid undue paternalism as far as possible, partly through ensuring patients are not deemed to lack capacity because they make an unwise decision. To this end, the law employs a procedural test of capacity that excludes substantive judgments about patients’ decisions. However, clinical intuitions about patients’ capacity to make decisions about their treatment often conflict with a strict reading of the legal criteria for assessing capacity, particularly in psychiatry. In this article I argue that this tension arises because the procedural conception of capacity is inadequate and does not reflect the clinical or legal realities of assessing capacity. I propose that conceptualising capacity as having ‘recognisable reasons’ for a treatment decision provides a practical way of legitimately incorporating both procedural and substantive elements of decision-making into assessments of capacity. PMID:27891169
A proposed model for economic evaluations of major depressive disorder.
Haji Ali Afzali, Hossein; Karnon, Jonathan; Gray, Jodi
2012-08-01
In countries like UK and Australia, the comparability of model-based analyses is an essential aspect of reimbursement decisions for new pharmaceuticals, medical services and technologies. Within disease areas, the use of models with alternative structures, type of modelling techniques and/or data sources for common parameters reduces the comparability of evaluations of alternative technologies for the same condition. The aim of this paper is to propose a decision analytic model to evaluate long-term costs and benefits of alternative management options in patients with depression. The structure of the proposed model is based on the natural history of depression and includes clinical events that are important from both clinical and economic perspectives. Considering its greater flexibility with respect to handling time, discrete event simulation (DES) is an appropriate simulation platform for modelling studies of depression. We argue that the proposed model can be used as a reference model in model-based studies of depression improving the quality and comparability of studies.
Multi-focus image fusion with the all convolutional neural network
NASA Astrophysics Data System (ADS)
Du, Chao-ben; Gao, She-sheng
2018-01-01
A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image fusion effect, getting a decision map is very necessary and usually difficult to finish. In this letter, we address this problem with convolutional neural network (CNN), aiming to get a state-of-the-art decision map. The main idea is that the max-pooling of CNN is replaced by a convolution layer, the residuals are propagated backwards by gradient descent, and the training parameters of the individual layers of the CNN are updated layer by layer. Based on this, we propose a new all CNN (ACNN)-based multi-focus image fusion method in spatial domain. We demonstrate that the decision map obtained from the ACNN is reliable and can lead to high-quality fusion results. Experimental results clearly validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.
Rurality Index for Small Areas in Spain
ERIC Educational Resources Information Center
Ocana-Riola, Ricardo; Sanchez-Cantalejo, Carmen
2005-01-01
An operational definition for "rural area" is pivotal if proposals, policies and decisions aimed at optimising the distribution of resources, closing the gap on inequity between areas and raising standards of living for the least advantaged populations are to be put in place. The concept of rurality, however, is often based on…
Deliberation before determination: the definition and evaluation of good decision making.
Elwyn, Glyn; Miron-Shatz, Talya
2010-06-01
In this article, we examine definitions of suggested approaches to measure the concept of good decisions, highlight the ways in which they converge, and explain why we have concerns about their emphasis on post-hoc estimations and post-decisional outcomes, their prescriptive concept of knowledge, and their lack of distinction between the process of deliberation, and the act of decision determination. There has been a steady trend to involve patients in decision making tasks in clinical practice, part of a shift away from paternalism towards the concept of informed choice. An increased understanding of the uncertainties that exist in medicine, arising from a weak evidence base and, in addition, the stochastic nature of outcomes at the individual level, have contributed to shifting the responsibility for decision making from physicians to patients. This led to increasing use of decision support and communication methods, with the ultimate aim of improving decision making by patients. Interest has therefore developed in attempting to define good decision making and in the development of measurement approaches. We pose and reflect whether decisions can be judged good or not, and, if so, how this goodness might be evaluated. We hypothesize that decisions cannot be measured by reference to their outcomes and offer an alternative means of assessment, which emphasizes the deliberation process rather than the decision's end results. We propose decision making comprises a pre-decisional process and an act of decision determination and consider how this model of decision making serves to develop a new approach to evaluating what constitutes a good decision making process. We proceed to offer an alternative, which parses decisions into the pre-decisional deliberation process, the act of determination and post-decisional outcomes. Evaluating the deliberation process, we propose, should comprise of a subjective sufficiency of knowledge, as well as emotional processing and affective forecasting of the alternatives. This should form the basis for a good act of determination.
Leroy, S; Marc, E; Adamsbaum, C; Gendrel, D; Bréart, G; Chalumeau, M
2006-01-01
Aims To test the reproducibility of a highly sensitive clinical decision rule proposed to predict vesicoureteral reflux (VUR) after a first febrile urinary tract infection in children. This rule combines clinical (family history of uropathology, male gender, young age), biological (raised C reactive protein), and radiological (urinary tract dilation on renal ultrasound) predictors in a score, and provides 100% sensitivity. Methods A retrospective hospital based cohort study included all children, 1 month to 4 years old, with a first febrile urinary tract infection. The sensitivities and specificities of the rule at the two previously proposed score thresholds (⩽0 and ⩽5) to predict respectively, all‐grade or grade ⩾3 VUR, were calculated. Results A total of 149 children were included. VUR prevalence was 25%. The rule yielded 100% sensitivity and 3% specificity for all‐grade VUR, and 93% sensitivity and 13% specificity for grade ⩾3 VUR. Some methodological weaknesses explain this lack of reproducibility. Conclusions The reproducibility of the previously proposed decision rule was poor and its potential contribution to clinical management of children with febrile urinary tract infection seems to be modest. PMID:15890693
Zhang, Dezhi; Li, Shuangyan
2014-01-01
This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209
Zhang, Dezhi; Li, Shuangyan; Qin, Jin
2014-01-01
This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.
Recommendations for Health Reporting: Proposal of a Working Paper
ERIC Educational Resources Information Center
Vercellesi, Luisa; Minghetti, Paola; Di Croce, Marianna; Bazzi, Adriana; Pieroni, Bruno; Centemeri, Carlo; Bruno, Flavia
2010-01-01
Objective: Media are a main source of medical information for the public, as well as for decision makers. This scenario demands a good selection of stories and correct medical reporting. Design: Our study aimed to analyze if journalistic guidelines or similar documents were already available and whether they provided satisfactory advice for…
Fuzzy cognitive maps for issue identification in a water resources conflict resolution system
NASA Astrophysics Data System (ADS)
Giordano, R.; Passarella, G.; Uricchio, V. F.; Vurro, M.
In water management, conflicts of interests are inevitable due to the variety in quality demands and the number of stakeholders, which are affected in different ways by decisions concerning the use of the resources. Ignoring the differences among interests involved in water resources management and not resolving the emerging conflicts could lead to controversial strategies. In such cases, proposed solutions could generate strong opposition, making these solutions unfeasible. In our contribution, a Community Decision Support System is proposed. Such a system is able to support discussion and collaboration. The system helps participants to structure their problem, to help them learn about possible alternatives, their constraints and implications and to support the participants in the specification of their own preferences. More in detail, the proposed system helps each user in representing and communicating problem perspectives. To reach this aim, cognitive maps are used to capture parts of the stakeholders’ point of view and to enhance negotiation among individuals and organizations. The aim of the negotiation process is to define a shared cognitive map with regard to water management problems. Such a map can be called a water community cognitive map. The system performance has been tested by simulating a real conflict on water resources management that occurred some years ago in a river basin in the south of Italy.
Fast support vector data descriptions for novelty detection.
Liu, Yi-Hung; Liu, Yan-Chen; Chen, Yen-Jen
2010-08-01
Support vector data description (SVDD) has become a very attractive kernel method due to its good results in many novelty detection problems. However, the decision function of SVDD is expressed in terms of the kernel expansion, which results in a run-time complexity linear in the number of support vectors. For applications where fast real-time response is needed, how to speed up the decision function is crucial. This paper aims at dealing with the issue of reducing the testing time complexity of SVDD. A method called fast SVDD (F-SVDD) is proposed. Unlike the traditional methods which all try to compress a kernel expansion into one with fewer terms, the proposed F-SVDD directly finds the preimage of a feature vector, and then uses a simple relationship between this feature vector and the SVDD sphere center to re-express the center with a single vector. The decision function of F-SVDD contains only one kernel term, and thus the decision boundary of F-SVDD is only spherical in the original space. Hence, the run-time complexity of the F-SVDD decision function is no longer linear in the support vectors, but is a constant, no matter how large the training set size is. In this paper, we also propose a novel direct preimage-finding method, which is noniterative and involves no free parameters. The unique preimage can be obtained in real time by the proposed direct method without taking trial-and-error. For demonstration, several real-world data sets and a large-scale data set, the extended MIT face data set, are used in experiments. In addition, a practical industry example regarding liquid crystal display micro-defect inspection is also used to compare the applicability of SVDD and our proposed F-SVDD when faced with mass data input. The results are very encouraging.
Institutionalizing Telemedicine Applications: The Challenge of Legitimizing Decision-Making
Lettieri, Emanuele
2011-01-01
During the last decades a variety of telemedicine applications have been trialed worldwide. However, telemedicine is still an example of major potential benefits that have not been fully attained. Health care regulators are still debating why institutionalizing telemedicine applications on a large scale has been so difficult and why health care professionals are often averse or indifferent to telemedicine applications, thus preventing them from becoming part of everyday clinical routines. We believe that the lack of consolidated procedures for supporting decision making by health care regulators is a major weakness. We aim to further the current debate on how to legitimize decision making about the institutionalization of telemedicine applications on a large scale. We discuss (1) three main requirements— rationality, fairness, and efficiency—that should underpin decision making so that the relevant stakeholders perceive them as being legitimate, and (2) the domains and criteria for comparing and assessing telemedicine applications—benefits and sustainability. According to these requirements and criteria, we illustrate a possible reference process for legitimate decision making about which telemedicine applications to implement on a large scale. This process adopts the health care regulators’ perspective and is made up of 2 subsequent stages, in which a preliminary proposal and then a full proposal are reviewed. PMID:21955510
Institutionalizing telemedicine applications: the challenge of legitimizing decision-making.
Zanaboni, Paolo; Lettieri, Emanuele
2011-09-28
During the last decades a variety of telemedicine applications have been trialed worldwide. However, telemedicine is still an example of major potential benefits that have not been fully attained. Health care regulators are still debating why institutionalizing telemedicine applications on a large scale has been so difficult and why health care professionals are often averse or indifferent to telemedicine applications, thus preventing them from becoming part of everyday clinical routines. We believe that the lack of consolidated procedures for supporting decision making by health care regulators is a major weakness. We aim to further the current debate on how to legitimize decision making about the institutionalization of telemedicine applications on a large scale. We discuss (1) three main requirements--rationality, fairness, and efficiency--that should underpin decision making so that the relevant stakeholders perceive them as being legitimate, and (2) the domains and criteria for comparing and assessing telemedicine applications--benefits and sustainability. According to these requirements and criteria, we illustrate a possible reference process for legitimate decision making about which telemedicine applications to implement on a large scale. This process adopts the health care regulators' perspective and is made up of 2 subsequent stages, in which a preliminary proposal and then a full proposal are reviewed.
Cost-effectiveness in Clostridium difficile treatment decision-making
Nuijten, Mark JC; Keller, Josbert J; Visser, Caroline E; Redekop, Ken; Claassen, Eric; Speelman, Peter; Pronk, Marja H
2015-01-01
AIM: To develop a framework for the clinical and health economic assessment for management of Clostridium difficile infection (CDI). METHODS: CDI has vast economic consequences emphasizing the need for innovative and cost effective solutions, which were aim of this study. A guidance model was developed for coverage decisions and guideline development in CDI. The model included pharmacotherapy with oral metronidazole or oral vancomycin, which is the mainstay for pharmacological treatment of CDI and is recommended by most treatment guidelines. RESULTS: A design for a patient-based cost-effectiveness model was developed, which can be used to estimate the cost-effectiveness of current and future treatment strategies in CDI. Patient-based outcomes were extrapolated to the population by including factors like, e.g., person-to-person transmission, isolation precautions and closing and cleaning wards of hospitals. CONCLUSION: The proposed framework for a population-based CDI model may be used for clinical and health economic assessments of CDI guidelines and coverage decisions for emerging treatments for CDI. PMID:26601096
Harris, Claire; Allen, Kelly; Waller, Cara; Dyer, Tim; Brooke, Vanessa; Garrubba, Marie; Melder, Angela; Voutier, Catherine; Gust, Anthony; Farjou, Dina
2017-06-21
This is the seventh in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was a systematic, integrated, evidence-based program for resource allocation within a large Australian health service. It aimed to facilitate proactive use of evidence from research and local data; evidence-based decision-making for resource allocation including disinvestment; and development, implementation and evaluation of disinvestment projects. From the literature and responses of local stakeholders it was clear that provision of expertise and education, training and support of health service staff would be required to achieve these aims. Four support services were proposed. This paper is a detailed case report of the development, implementation and evaluation of a Data Service, Capacity Building Service and Project Support Service. An Evidence Service is reported separately. Literature reviews, surveys, interviews, consultation and workshops were used to capture and process the relevant information. Existing theoretical frameworks were adapted for evaluation and explication of processes and outcomes. Surveys and interviews identified current practice in use of evidence in decision-making, implementation and evaluation; staff needs for evidence-based practice; nature, type and availability of local health service data; and preferred formats for education and training. The Capacity Building and Project Support Services were successful in achieving short term objectives; but long term outcomes were not evaluated due to reduced funding. The Data Service was not implemented at all. Factors influencing the processes and outcomes are discussed. Health service staff need access to education, training, expertise and support to enable evidence-based decision-making and to implement and evaluate the changes arising from those decisions. Three support services were proposed based on research evidence and local findings. Local factors, some unanticipated and some unavoidable, were the main barriers to successful implementation. All three proposed support services hold promise as facilitators of EBP in the local healthcare setting. The findings from this study will inform further exploration.
Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M
2010-01-01
This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.
FlooDSuM - a decision support methodology for assisting local authorities in flood situations
NASA Astrophysics Data System (ADS)
Schwanbeck, Jan; Weingartner, Rolf
2014-05-01
Decision making in flood situations is a difficult task, especially in small to medium-sized mountain catchments (30 - 500 km2) which are usually characterized by complex topography, high drainage density and quick runoff response to rainfall events. Operating hydrological models driven by numerical weather prediction systems, which have a lead-time of several hours up to few even days, would be beneficial in this case as time for prevention could be gained. However, the spatial and quantitative accuracy of such meteorological forecasts usually decrease with increasing lead-time. In addition, the sensitivity of rainfall-runoff models to inaccuracies in estimations of areal rainfall increases with decreasing catchment size. Accordingly, decisions on flood alerts should ideally be based on areal rainfall from high resolution and short-term numerical weather prediction, nowcasts or even real-time measurements, which is transformed into runoff by a hydrological model. In order to benefit from the best possible rainfall data while retaining enough time for alerting and for prevention, the hydrological model should be fast and easily applicable by decision makers within local authorities themselves. The proposed decision support methodology FlooDSuM (Flood Decision Support Methodology) aims to meet those requirements. Applying FlooDSuM, a few successive binary decisions of increasing complexity have to be processed following a flow-chart-like structure. Prepared data and straightforwardly applicable tools are provided for each of these decisions. Maps showing the current flood disposition are used for the first step. While danger of flooding cannot be excluded more and more complex and time consuming methods will be applied. For the final decision, a set of scatter-plots relating areal precipitation to peak flow is provided. These plots take also further decisive parameters into account such as storm duration, distribution of rainfall intensity in time as well as the catchment's antecedent moisture conditions. The proposed approach is currently tested in two catchments in the Swiss Pre-Alps and Alps. We will show the general setup and selected results. The findings of those case studies will lead to further improvements of the proposed approach.
NASA Astrophysics Data System (ADS)
Wasielewska, K.; Ganzha, M.
2012-10-01
In this paper we consider combining ontologically demarcated information with Saaty's Analytic Hierarchy Process (AHP) [1] for the multicriterial assessment of offers during contract negotiations. The context for the proposal is provided by the Agents in Grid project (AiG; [2]), which aims at development of an agent-based infrastructure for efficient resource management in the Grid. In the AiG project, software agents representing users can either (1) join a team and earn money, or (2) find a team to execute a job. Moreover, agents form teams, managers of which negotiate with clients and workers terms of potential collaboration. Here, ontologically described contracts (Service Level Agreements) are the results of autonomous multiround negotiations. Therefore, taking into account relatively complex nature of the negotiated contracts, multicriterial assessment of proposals plays a crucial role. The AHP method is based on pairwise comparisons of criteria and relies on the judgement of a panel of experts. It measures how well does an offer serve the objective of a decision maker. In this paper, we propose how the AHP method can be used to assess ontologically described contract proposals.
A decision modeling for phasor measurement unit location selection in smart grid systems
NASA Astrophysics Data System (ADS)
Lee, Seung Yup
As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed.
NASA Astrophysics Data System (ADS)
Zhang, Wancheng; Xu, Yejun; Wang, Huimin
2016-01-01
The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making (MAGDM) problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.
Intelligent Scheduling for Underground Mobile Mining Equipment.
Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John
2015-01-01
Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine.
ERIC Educational Resources Information Center
Collins, J. Michael; Odders-White, Elizabeth
2015-01-01
Concerns about consumers' ability to manage their finances have triggered a range of proposals, including interventions aimed at elementary school students. The goal of these approaches is to improve lifelong economic decision making, but the evidence supporting their efficacy is thin. In this article, the authors discuss the trend toward…
Evidence-Based Administration for Decision Making in the Framework of Knowledge Strategic Management
ERIC Educational Resources Information Center
Del Junco, Julio Garcia; Zaballa, Rafael De Reyna; de Perea, Juan Garcia Alvarez
2010-01-01
Purpose: This paper seeks to present a model based on evidence-based administration (EBA), which aims to facilitate the creation, transformation and diffusion of knowledge in learning organizations. Design/methodology/approach: A theoretical framework is proposed based on EBA and the case method. Accordingly, an empirical study was carried out in…
ERIC Educational Resources Information Center
Chen, Baoguo; Zhou, Huixia; Gao, Yiwen; Dunlap, Susan
2014-01-01
The present study aimed to test the Sense Model of cross-linguistic masked translation priming asymmetry, proposed by Finkbeiner et al. ("J Mem Lang" 51:1-22, 2004), by manipulating the number of senses that bilingual participants associated with words from both languages. Three lexical decision experiments were conducted with…
Measuring Distance of Fuzzy Numbers by Trapezoidal Fuzzy Numbers
NASA Astrophysics Data System (ADS)
Hajjari, Tayebeh
2010-11-01
Fuzzy numbers and more generally linguistic values are approximate assessments, given by experts and accepted by decision-makers when obtaining value that is more accurate is impossible or unnecessary. Distance between two fuzzy numbers plays an important role in linguistic decision-making. It is reasonable to define a fuzzy distance between fuzzy objects. To achieve this aim, the researcher presents a new distance measure for fuzzy numbers by means of improved centroid distance method. The metric properties are also studied. The advantage is the calculation of the proposed method is far simple than previous approaches.
Minciardi, Riccardo; Paolucci, Massimo; Robba, Michela; Sacile, Roberto
2008-11-01
An approach to sustainable municipal solid waste (MSW) management is presented, with the aim of supporting the decision on the optimal flows of solid waste sent to landfill, recycling and different types of treatment plants, whose sizes are also decision variables. This problem is modeled with a non-linear, multi-objective formulation. Specifically, four objectives to be minimized have been taken into account, which are related to economic costs, unrecycled waste, sanitary landfill disposal and environmental impact (incinerator emissions). An interactive reference point procedure has been developed to support decision making; these methods are considered appropriate for multi-objective decision problems in environmental applications. In addition, interactive methods are generally preferred by decision makers as they can be directly involved in the various steps of the decision process. Some results deriving from the application of the proposed procedure are presented. The application of the procedure is exemplified by considering the interaction with two different decision makers who are assumed to be in charge of planning the MSW system in the municipality of Genova (Italy).
Dale, William; Stankus, Nicole; Sachs, Greg A.
2008-01-01
Background Chronic kidney disease (CKD) is a growing public health concern that overwhelmingly affects older adults. National guidelines have called for earlier referral of CKD patients, but it is unclear how these should apply to older adults. Objective This scholarly review aims to explore the current literature about upstream referral decisions for CKD within the context of decisions about initiation of dialysis and general referral decisions. The authors propose a model for understanding the referral process and discuss future directions for research to guide decision making for older patients with CKD. Results While age has been shown to be influential in decisions to refer patients for dialysis and other medical therapies, the role of other patient factors such as competing medical co-morbidities, functional loss, or cognitive impairment in the decision making of physicians has been less well elucidated, particularly for CKD. Conclusions More information is needed on the decision-making behavior of physicians for upstream referral decisions like those being advocated for CKD. Exploring the role of geriatric factors like cognitive and functional status may help facilitate more appropriate use of resources and improve patient outcomes. PMID:18175190
Shared decision making in the medical encounter: are we all talking about the same thing?
Moumjid, Nora; Gafni, Amiram; Brémond, Alain; Carrère, Marie-Odile
2007-01-01
This article aims to explore 1) whether after all the research done on shared decision making (SDM) in the medical encounter, a clear definition (or definitions) of SDM exists; 2) whether authors provide a definition of SDM when they use the term; 3) and whether authors are consistent, throughout a given paper, with respect to the research described and the definition they propose or cite. The authors searched different databases (Medline, HealthStar, Cinahl, Cancerlit, Sociological Abstracts, and Econlit) from 1997 to December 2004. The keywords used were informed decision making and shared decision making as these are the keywords more often encountered in the literature. The languages selected were English and French. The 76 reported papers show that 1) several authors clearly define what they mean by SDM or by another closely related phrase, such as informed shared decision making. 2) About a third of the papers reviewed (25/76) cite these authors although 8 of them do not use the term in a manner consistent with the definition cited. 3) Certain authors use the term SDM inconsistently with the definition they propose, and some use the terms informed decision making and SDM as if they were synonymous. 4) Twenty-one papers do not provide or cite any definition, or their use of the term (i.e., SDM) is not consistent with the definition they provide. Although several clear definitions of shared decision making have been proposed, they are cited by only about a third of the papers reviewed. In the other papers, authors refer to the term without specifying or citing a definition or use the term inconsistently with their definition. This is a problem because having a clear definition of the concept and following this definition are essential to guide and focus research. Authors should use the term consistently with the identified definition.
HEALTH TECHNOLOGY ASSESSMENT FOR DECISION MAKING IN LATIN AMERICA: GOOD PRACTICE PRINCIPLES.
Pichon-Riviere, Andrés; Soto, Natalie C; Augustovski, Federico Ariel; García Martí, Sebastián; Sampietro-Colom, Laura
2018-06-11
The aim of this study was to identify good practice principles for health technology assessment (HTA) that are the most relevant and of highest priority for application in Latin America and to identify potential barriers to their implementation in the region. HTA good practice principles proposed at the international level were identified and then explored during a deliberative process in a forum of assessors, funders, and product manufacturers. Forty-two representatives from ten Latin American countries participated. Good practice principles proposed at the international level were considered valid and potentially relevant to Latin America. Five principles were identified as priority and with the greatest potential to be strengthened at this time: transparency in the production of HTA, involvement of relevant stakeholders in the HTA process, mechanisms to appeal decisions, clear priority-setting processes in HTA, and a clear link between HTA and decision making. The main challenge identified was to find a balance between the application of these principles and the available resources in a way that would not detract from the production of reports and adaptation to the needs of decision makers. The main recommendation was to progress gradually in strengthening HTA and its link to decision making by developing appropriate processes for each country, without trying to impose, in the short-term, standards taken from examples at the international level without adequate adaptation of these to local contexts.
2011-01-01
Background Despite the recent publication of results from two randomized clinical trials, prostate specific antigen (PSA) screening for prostate cancer remains a controversial issue. There is lack of agreement across studies that PSA screening significantly reduces prostate cancer mortality. In spite of these facts, the widespread use of PSA testing in the United States leads to overdetection and overtreatment of clinically indolent prostate cancer, and its associated harms of incontinence and impotence. Discussion Given the inconclusive results from clinical trials and incongruent PSA screening guidelines, the decision to screen for prostate cancer with PSA testing is an uncertain one for patients and health care providers. Screening guidelines from some health organizations recommend an informed decision making (IDM) or shared decision making (SDM) approach for deciding on PSA screening. These approaches aim to empower patients to choose among the available options by making them active participants in the decision making process. By increasing involvement of patients in the clinical decision-making process, IDM/SDM places more of the responsibility for a complex decision on the patient. Research suggests, however, that patients are not well-informed of the harms and benefits associated with prostate cancer screening and are also subject to an assortment of biases, emotion, fears, and irrational thought that interferes with making an informed decision. In response, the IDM/SDM approaches can be augmented with strategies from the philosophy of libertarian paternalism (LP) to improve decision making. LP uses the insights of behavioural economics to help people better make better choices. Some of the main strategies of LP applicable to PSA decision making are a default decision rule, framing of decision aids, and timing of the decision. In this paper, we propose that applying strategies from libertarian paternalism can help with PSA screening decision-making. Summary Our proposal to augment IDM and SDM approaches with libertarian paternalism strategies is intended to guide patients toward a better decision about testing while maintaining personal freedom of choice. While PSA screening remains controversial and evidence conflicting, a libertarian-paternalism influenced approach to decision making can help prevent the overdiagnosis and overtreatment of prostate cancer. PMID:21510865
Wheeler, David C; Szymanski, Konrad M; Black, Amanda; Nelson, David E
2011-04-21
Despite the recent publication of results from two randomized clinical trials, prostate specific antigen (PSA) screening for prostate cancer remains a controversial issue. There is lack of agreement across studies that PSA screening significantly reduces prostate cancer mortality. In spite of these facts, the widespread use of PSA testing in the United States leads to overdetection and overtreatment of clinically indolent prostate cancer, and its associated harms of incontinence and impotence. Given the inconclusive results from clinical trials and incongruent PSA screening guidelines, the decision to screen for prostate cancer with PSA testing is an uncertain one for patients and health care providers. Screening guidelines from some health organizations recommend an informed decision making (IDM) or shared decision making (SDM) approach for deciding on PSA screening. These approaches aim to empower patients to choose among the available options by making them active participants in the decision making process. By increasing involvement of patients in the clinical decision-making process, IDM/SDM places more of the responsibility for a complex decision on the patient. Research suggests, however, that patients are not well-informed of the harms and benefits associated with prostate cancer screening and are also subject to an assortment of biases, emotion, fears, and irrational thought that interferes with making an informed decision. In response, the IDM/SDM approaches can be augmented with strategies from the philosophy of libertarian paternalism (LP) to improve decision making. LP uses the insights of behavioural economics to help people better make better choices. Some of the main strategies of LP applicable to PSA decision making are a default decision rule, framing of decision aids, and timing of the decision. In this paper, we propose that applying strategies from libertarian paternalism can help with PSA screening decision-making. Our proposal to augment IDM and SDM approaches with libertarian paternalism strategies is intended to guide patients toward a better decision about testing while maintaining personal freedom of choice. While PSA screening remains controversial and evidence conflicting, a libertarian-paternalism influenced approach to decision making can help prevent the overdiagnosis and overtreatment of prostate cancer.
A review of clinical decision making: models and current research.
Banning, Maggi
2008-01-01
The aim of this paper was to review the current literature clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information-processing model, the intuitive-humanist model and the clinical decision-making model. Clinical decision making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognized from the literature; the information-processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information-processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Literature review. Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 to November 2005. The characteristics of the three models of decision making were identified and the related research discussed. Three approaches to clinical decision making were identified, each having its own attributes and uses. The most recent addition to the clinical decision making is a theoretical, multidimensional model which was developed through an evaluation of current literature and the assessment of a limited number of research studies that focused on the clinical decision-making skills of inexperienced nurses in pseudoclinical settings. The components of this model and the relative merits to clinical practice are discussed. It is proposed that clinical decision making improves as the nurse gains experience of nursing patients within a specific speciality and with experience, nurses gain a sense of saliency in relation to decision making. Experienced nurses may use all three forms of clinical decision making both independently and concurrently to solve nursing-related problems. It is suggested that O'Neill's clinical decision-making model could be tested by educators and experienced nurses to assess the efficacy of this hybrid approach to decision making.
Interprofessional education about patient decision support in specialty care.
Politi, Mary C; Pieterse, Arwen H; Truant, Tracy; Borkhoff, Cornelia; Jha, Vikram; Kuhl, Laura; Nicolai, Jennifer; Goss, Claudia
2011-11-01
Specialty care involves services provided by health professionals who focus on treating diseases affecting one body system. In contrast to primary care - aimed at providing continuous, comprehensive care - specialty care often involves intermittent episodes of care focused around specific medical conditions. In addition, it typically includes multiple providers who have unique areas of expertise that are important in supporting patients' care. Interprofessional care involves multiple professionals from different disciplines collaborating to provide an integrated approach to patient care. For patients to experience continuity of care across interprofessional providers, providers need to communicate and maintain a shared sense of responsibility to their patients. In this article, we describe challenges inherent in providing interprofessional patient decision support in specialty care. We propose ways for providers to engage in interprofessional decision support and discuss promising approaches to teaching an interprofessional decision support to specialty care providers. Additional evaluation and empirical research are required before further recommendations can be made about education for interprofessional decision support in specialty care.
ERIC Educational Resources Information Center
Lavidor, Michal; Hayes, Adrian; Shillcock, Richard; Ellis, Andrew W.
2004-01-01
The split fovea theory proposes that visual word recognition of centrally presented words is mediated by the splitting of the foveal image, with letters to the left of fixation being projected to the right hemisphere (RH) and letters to the right of fixation being projected to the left hemisphere (LH). Two lexical decision experiments aimed to…
Therapy Decision Support Based on Recommender System Methods
Gräßer, Felix; Beckert, Stefanie; Küster, Denise; Schmitt, Jochen; Abraham, Susanne; Malberg, Hagen
2017-01-01
We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system. PMID:29065657
Carnero, María Carmen; Gómez, Andrés
2016-04-23
Healthcare organizations have far greater maintenance needs for their medical equipment than other organization, as many are used directly with patients. However, the literature on asset management in healthcare organizations is very limited. The aim of this research is to provide more rational application of maintenance policies, leading to an increase in quality of care. This article describes a multicriteria decision-making approach which integrates Markov chains with the multicriteria Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), to facilitate the best choice of combination of maintenance policies by using the judgements of a multi-disciplinary decision group. The proposed approach takes into account the level of acceptance that a given alternative would have among professionals. It also takes into account criteria related to cost, quality of care and impact of care cover. This multicriteria approach is applied to four dialysis subsystems: patients infected with hepatitis C, infected with hepatitis B, acute and chronic; in all cases, the maintenance strategy obtained consists of applying corrective and preventive maintenance plus two reserve machines. The added value in decision-making practices from this research comes from: (i) integrating the use of Markov chains to obtain the alternatives to be assessed by a multicriteria methodology; (ii) proposing the use of MACBETH to make rational decisions on asset management in healthcare organizations; (iii) applying the multicriteria approach to select a set or combination of maintenance policies in four dialysis subsystems of a health care organization. In the multicriteria decision making approach proposed, economic criteria have been used, related to the quality of care which is desired for patients (availability), and the acceptance that each alternative would have considering the maintenance and healthcare resources which exist in the organization, with the inclusion of a decision-making group. This approach is better suited to actual health care organization practice and depending on the subsystem analysed, improvements are introduced that are not included in normal maintenance policies; in this way, not only have different maintenance policies been suggested, but also alternatives that, in each case and according to viability, provide a more complete decision tool for the maintenance manager.
Predefined three tier business intelligence architecture in healthcare enterprise.
Wang, Meimei
2013-04-01
Business Intelligence (BI) has caused extensive concerns and widespread use in gathering, processing and analyzing data and providing enterprise users the methodology to make decisions. Different from traditional BI architecture, this paper proposes a new BI architecture, Top-Down Scalable BI architecture with defining mechanism for enterprise decision making solutions and aims at establishing a rapid, consistent, and scalable multiple applications on multiple platforms of BI mechanism. The two opposite information flows in our BI architecture offer the merits of having the high level of organizational prospects and making full use of the existing resources. We also introduced the avg-bed-waiting-time factor to evaluate hospital care capacity.
Management of Customer Service in Terms of Logistics Information Systems
NASA Astrophysics Data System (ADS)
Kampf, Rudolf; Ližbetinová, Lenka; Tišlerová, Kamila
2017-03-01
This paper is focused on perceiving the logistic services as the competition advantage in frame of the ecommerce. Customers consider their purchases in its complexity and all the logistic services should be designed to meet with customers' preferences as much as possible. Our aim was to identify and evaluate of customers perceiving in frame of sales proposals offered by e-shops. Collected data of research were processed with the usage of cluster analysis. The aim of this paper is to present the results and conclusions from this research with focus on the elements of logistics services within e-commerce. These outputs can be used for knowledge base of information systems through which enterprises evaluate their decisions and selection of variants. For the enterprise, it is important to appropriate decisions about resource allocation and design of the structure of logistics services were set based on real customer preferences.
Rennie, Sarah C; van Rij, Andre M; Jaye, Chrystal; Hall, Katherine H
2011-06-01
Decision making is a key competency of surgeons; however, how best to assess decisions and decision makers is not clearly established. The aim of the present study was to identify criteria that inform judgments about surgical trainees' decision-making skills. A qualitative free text web-based survey was distributed to recognized international experts in Surgery, Medical Education, and Cognitive Research. Half the participants were asked to identify features of good decisions, characteristics of good decision makers, and essential factors for developing good decision-making skills. The other half were asked to consider these areas in relation to poor decision making. Template analysis of free text responses was performed. Twenty-nine (52%) experts responded to the survey, identifying 13 categories for judging a decision and 14 for judging a decision maker. Twelve features/characteristics overlapped (considered, informed, well timed, aware of limitations, communicated, knowledgeable, collaborative, patient-focused, flexible, able to act on the decision, evidence-based, and coherent). Fifteen categories were generated for essential factors leading to development of decision-making skills that fall into three major themes (personal qualities, training, and culture). The categories compiled from the perspectives of good/poor were predominantly the inverse of each other; however, the weighting given to some categories varied. This study provides criteria described by experts when considering surgical decisions, decision makers, and development of decision-making skills. It proposes a working definition of a good decision maker. Understanding these criteria will enable clinical teachers to better recognize and encourage good decision-making skills and identify poor decision-making skills for remediation.
Losing Your Gut Feelings. Intuition in Depression
Remmers, Carina; Michalak, Johannes
2016-01-01
Whereas in basic research, intuition has become a topic of great interest, clinical research and depression research in specific have not applied to the topic of intuition, yet. This is astonishing because a well-known phenomenon during depression is that patients have difficulties to judge and decide. In contrast to healthy individuals who take most daily life decisions intuitively (Kahneman, 2011), depressed individuals seem to have difficulties to come to fast and adaptive decisions. The current article pursues three goals. First, our aim is to establish the hypothesis that intuition is impaired in depression against the background of influential theoretical accounts as well as empirical evidence from basic and clinical research. The second aim of the current paper is to provide explanations for recent findings on the depression-intuition interplay and to present directions for future research that may help to broaden our understanding of decision difficulties in depression. Third, we seek to propose ideas on how therapeutic interventions can support depressed individuals in taking better decisions. Even though our knowledge regarding this topic is still limited, we will tentatively launch the idea that an important first step may be to enhance patients’ access to intuitions. Overall, this paper seeks to introduce the topic of intuition to clinical research on depression and to hereby set the stage for upcoming theory and practice. PMID:27602015
Losing Your Gut Feelings. Intuition in Depression.
Remmers, Carina; Michalak, Johannes
2016-01-01
Whereas in basic research, intuition has become a topic of great interest, clinical research and depression research in specific have not applied to the topic of intuition, yet. This is astonishing because a well-known phenomenon during depression is that patients have difficulties to judge and decide. In contrast to healthy individuals who take most daily life decisions intuitively (Kahneman, 2011), depressed individuals seem to have difficulties to come to fast and adaptive decisions. The current article pursues three goals. First, our aim is to establish the hypothesis that intuition is impaired in depression against the background of influential theoretical accounts as well as empirical evidence from basic and clinical research. The second aim of the current paper is to provide explanations for recent findings on the depression-intuition interplay and to present directions for future research that may help to broaden our understanding of decision difficulties in depression. Third, we seek to propose ideas on how therapeutic interventions can support depressed individuals in taking better decisions. Even though our knowledge regarding this topic is still limited, we will tentatively launch the idea that an important first step may be to enhance patients' access to intuitions. Overall, this paper seeks to introduce the topic of intuition to clinical research on depression and to hereby set the stage for upcoming theory and practice.
From research to evidence-informed decision making: a systematic approach
Poot, Charlotte C; van der Kleij, Rianne M; Brakema, Evelyn A; Vermond, Debbie; Williams, Siân; Cragg, Liza; van den Broek, Jos M; Chavannes, Niels H
2018-01-01
Abstract Background Knowledge creation forms an integral part of the knowledge-to-action framework aimed at bridging the gap between research and evidence-informed decision making. Although principles of science communication, data visualisation and user-centred design largely impact the effectiveness of communication, their role in knowledge creation is still limited. Hence, this article aims to provide researchers a systematic approach on how knowledge creation can be put into practice. Methods A systematic two-phased approach towards knowledge creation was formulated and executed. First, during a preparation phase the purpose and audience of the knowledge were defined. Subsequently, a developmental phase facilitated how the content is ‘said’ (language) and communicated (channel). This developmental phase proceeded via two pathways: a translational cycle and design cycle, during which core translational and design components were incorporated. The entire approach was demonstrated by a case study. Results The case study demonstrated how the phases in this systematic approach can be operationalised. It furthermore illustrated how created knowledge can be delivered. Conclusion The proposed approach offers researchers a systematic, practical and easy-to-implement tool to facilitate effective knowledge creation towards decision-makers in healthcare. Through the integration of core components of knowledge creation evidence-informed decision making will ultimately be optimized. PMID:29538728
Intelligent Scheduling for Underground Mobile Mining Equipment
Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John
2015-01-01
Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine. PMID:26098934
Chronic Heart Failure Follow-up Management Based on Agent Technology.
Mohammadzadeh, Niloofar; Safdari, Reza
2015-10-01
Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.
Haws, Kelly L; Liu, Peggy J
2016-08-01
Given the prevalence and rising rates of obesity in many countries, including the United States, much food decision-making research ultimately aims at understanding how consumers can make healthier choices. The two predominant choice paradigms used in food decision-making research ask consumers to choose (a) between a "vice" (or unhealthy food) and a "virtue" (or healthy food) or (b) among varying portion sizes of "vice." We propose a new food choice paradigm that encourages consumers to jointly consider both food type(s) choice and food portion size at each decision point. The purpose of this paradigm is two-fold. First, it aims to allow examination of more comprehensive eating behavior (e.g., to examine the overall composition of a plate of food rather than choice of a single food). Second, it aims to shift consumers towards including large proportions of virtues and smaller proportions of vice in their overall consumption portfolios. For this paradigm, we draw upon a recently introduced food product innovation called "vice-virtue bundles" (Liu et al., 2015) that illustrates the basis of this new food choice paradigm, in which food type(s) and portion decisions are made simultaneously. Accordingly, we first discuss relevant findings on vice-virtue bundles as well as the differences between simultaneous and sequential choice of multiple products. Second, we examine the benefits for managing and controlling one's consumption that are provided by vice-virtue bundles and this joint food choice paradigm more generally. Third and finally, we point out opportunities for future research by discussing (a) multiple factors that influence food choices, (b) decision processes affected by food choice paradigms, and (c) issues of generalizability related to the presence of vice-virtue bundles. Copyright © 2015 Elsevier Ltd. All rights reserved.
Rajagopal, Rekha; Ranganathan, Vidhyapriya
2018-06-05
Automation in cardiac arrhythmia classification helps medical professionals make accurate decisions about the patient's health. The aim of this work was to design a hybrid classification model to classify cardiac arrhythmias. The design phase of the classification model comprises the following stages: preprocessing of the cardiac signal by eliminating detail coefficients that contain noise, feature extraction through Daubechies wavelet transform, and arrhythmia classification using a collaborative decision from the K nearest neighbor classifier (KNN) and a support vector machine (SVM). The proposed model is able to classify 5 arrhythmia classes as per the ANSI/AAMI EC57: 1998 classification standard. Level 1 of the proposed model involves classification using the KNN and the classifier is trained with examples from all classes. Level 2 involves classification using an SVM and is trained specifically to classify overlapped classes. The final classification of a test heartbeat pertaining to a particular class is done using the proposed KNN/SVM hybrid model. The experimental results demonstrated that the average sensitivity of the proposed model was 92.56%, the average specificity 99.35%, the average positive predictive value 98.13%, the average F-score 94.5%, and the average accuracy 99.78%. The results obtained using the proposed model were compared with the results of discriminant, tree, and KNN classifiers. The proposed model is able to achieve a high classification accuracy.
Clarinval, Caroline; Biller-Andorno, Nikola
2014-06-23
This paper aims to raise awareness regarding ethical issues in the context of humanitarian action, and to offer a framework for systematically and effectively addressing such issues. Several cases highlight ethical issues that humanitarian aid workers are confronted with at different levels over the course of their deployments. The first case discusses a situation at a macro-level concerning decisions being made at the headquarters of a humanitarian organization. The second case looks at meso-level issues that need to be solved at a country or regional level. The third case proposes an ethical dilemma at the micro-level of the individual patient-provider relationship. These real-life cases have been selected to illustrate the ethical dimension of conflicts within the context of humanitarian action that might remain unrecognized in everyday practice. In addition, we propose an ethical framework to assist humanitarian aid workers in their decision-making process. The framework draws on the principles and values that guide humanitarian action and public health ethics more generally. Beyond identifying substantive core values, the framework also includes a ten-step process modelled on tools used in the clinical setting that promotes a transparent and clear decision-making process and improves the monitoring and evaluation of aid interventions. Finally, we recommend organizational measures to implement the framework effectively. This paper uses a combination of public health/clinical ethics concepts and practices and applies them to the decision-making challenges encountered in relief operations in the humanitarian aid context.
43 CFR 2450.3 - Proposed classification decision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Proposed classification decision. 2450.3... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) PETITION-APPLICATION CLASSIFICATION SYSTEM Petition-Application Procedures § 2450.3 Proposed classification decision. (a) The State Director...
De Feo, Giovanni; De Gisi, Sabino
2010-11-01
The main aim of this study was to verify the efficacy of using an innovative criteria weighting tool (the "priority scale") for stakeholders involvement to rank a list of suitable municipal solid waste (MSW) facility sites with the multi-criteria decision-making (MCDM) technique known as analytic hierarchy process (AHP). One of the main objectives of the study was to verify the behaviour of the "priority scale" with both technical and non-technical decision-makers. All over the world, the siting of MSW treatment or disposal plants is a complex process involving politicians, technicians as well as citizens, where stakeholders who are not effectively involved strongly oppose (or even obstruct) the realization of new facilities. In this study, in order to pursue both the technical (select the best site) and social aims (all the stakeholders have to give their aware contribution), the use of the "priority scale" is suggested as a tool to easily collect non-contradictory criteria preferences by the various decision-makers. Every decision-maker filled in "priority scale", which was subsequently uploaded in the AHP tool in order to indirectly calculate the individual priority of alternatives given by each stakeholder (not using group aggregation techniques). The proposed method was applied to the siting of a composting plant in an area suffering from a serious MSW emergency, which has lasted for over 15 years, in the Campania Region, in Southern Italy. The best site (the "first choice") was taken as the one that appeared the most times at the first place of each decision-maker ranking list. The involved technical and non-technical decision-makers showed the same behaviour in (indirectly) selecting the best site as well as in terms of the most appraised criteria ("absence of areas of the highest value for natural habitats and species of plants and animals"). Moreover, they showed the same AHP inconsistency ratio as well as the same behaviour in comparison with a "balanced decision-maker" (who assigns identical weights to all the considered criteria). Therefore, the proposed criteria weighting tool could be widely as well as easily used for stakeholders involvement to rank MSW facility sites (or other kinds of alternatives) with the AHP or with other MCDM techniques, taking or not into consideration group aggregation methods. Copyright © 2010 Elsevier Ltd. All rights reserved.
Qi, Xiao-Wen; Zhang, Jun-Ling; Zhao, Shu-Ping; Liang, Chang-Yong
2017-10-02
In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager's prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches.
Qi, Xiao-Wen; Zhang, Jun-Ling; Zhao, Shu-Ping; Liang, Chang-Yong
2017-01-01
In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager’s prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches. PMID:28974045
Following Human Footsteps: Proposal of a Decision Theory Based on Human Behavior
NASA Technical Reports Server (NTRS)
Mahmud, Faisal
2011-01-01
Human behavior is a complex nature which depends on circumstances and decisions varying from time to time as well as place to place. The way a decision is made either directly or indirectly related to the availability of the options. These options though appear at random nature, have a solid directional way for decision making. In this paper, a decision theory is proposed which is based on human behavior. The theory is structured with model sets that will show the all possible combinations for making a decision, A virtual and simulated environment is considered to show the results of the proposed decision theory
Poonam Khanijo Ahluwalia; Nema, Arvind K
2011-07-01
Selection of optimum locations for locating new facilities and decision regarding capacities at the proposed facilities is a major concern for municipal authorities/managers. The decision as to whether a single facility is preferred over multiple facilities of smaller capacities would vary with varying priorities to cost and associated risks such as environmental or health risk or risk perceived by the society. Currently management of waste streams such as that of computer waste is being done using rudimentary practices and is flourishing as an unorganized sector, mainly as backyard workshops in many cities of developing nations such as India. Uncertainty in the quantification of computer waste generation is another major concern due to the informal setup of present computer waste management scenario. Hence, there is a need to simultaneously address uncertainty in waste generation quantities while analyzing the tradeoffs between cost and associated risks. The present study aimed to address the above-mentioned issues in a multi-time-step, multi-objective decision-support model, which can address multiple objectives of cost, environmental risk, socially perceived risk and health risk, while selecting the optimum configuration of existing and proposed facilities (location and capacities).
NASA Astrophysics Data System (ADS)
Kwak, Minjung; Kim, Harrison
2015-01-01
Remanufacturing is emerging as a promising solution for achieving green, profitable businesses. This article considers a manufacturer that produces new products and also remanufactured versions of the new products that become available at the end of their life cycle. For such a manufacturer, design decisions at the initial design stage determine both the current profit from manufacturing and future profit from remanufacturing. To maximize the total profit, design decisions must carefully consider both ends of product life cycle, i.e. manufacturing and end-of-life stages. This article proposes a decision-support model for the life-cycle design using mixed-integer nonlinear programming. With an aim to maximize the total life-cycle profit, the proposed model searches for an (at least locally) optimal product design (i.e. design specifications and the selling price) for the new and remanufactured products. It optimizes both the initial design and design upgrades at the end-of-life stage and also provides corresponding production strategies, including production quantities and take-back rate. The model is extended to a multi-objective model that maximizes both economic profit and environmental-impact saving. To illustrate, the developed model is demonstrated with an example of a desktop computer.
Cai, Hao; Long, Weiding; Li, Xianting; Kong, Lingjuan; Xiong, Shuang
2010-06-15
In case hazardous contaminants are suddenly released indoors, the prompt and proper emergency responses are critical to protect occupants. This paper aims to provide a framework for determining the optimal combination of ventilation and evacuation strategies by considering the uncertainty of source locations. The certainty of source locations is classified as complete certainty, incomplete certainty, and complete uncertainty to cover all the possible situations. According to this classification, three types of decision analysis models are presented. A new concept, efficiency factor of contaminant source (EFCS), is incorporated in these models to evaluate the payoffs of the ventilation and evacuation strategies. A procedure of decision-making based on these models is proposed and demonstrated by numerical studies of one hundred scenarios with ten ventilation modes, two evacuation modes, and five source locations. The results show that the models can be useful to direct the decision analysis of both the ventilation and evacuation strategies. In addition, the certainty of the source locations has an important effect on the outcomes of the decision-making. Copyright 2010 Elsevier B.V. All rights reserved.
Velez-Montoya, Raul; Jacobo-Oceguera, Paola; Flores-Preciado, Javier; Dalma-Weiszhausz, Jose; Guerrero-Naranjo, Jose; Salcedo-Villanueva, Guillermo; Garcia-Aguirre, Gerardo; Fromow-Guerra, Jans; Morales-Canton, Virgilio
2016-01-01
We reviewed all the available data regarding the current management of non-complex rhegmatogenous retinal detachment and aimed to propose a new decision-making algorithm aimed to improve the single surgery success rate for mid-severity rhegmatogenous retinal detachment. An online review of the Pubmed database was performed. We searched for all available manuscripts about the anatomical and functional outcomes after the surgical management, by either scleral buckle or primary pars plana vitrectomy, of retinal detachment. The search was limited to articles published from January 1995 to December 2015. All articles obtained from the search were carefully screened and their references were manually reviewed for additional relevant data. Our search specifically focused on preoperative clinical data that were associated with the surgical outcomes. After categorizing the available data according to their level of evidence, with randomized-controlled clinical trials as the highest possible level of evidence, followed by retrospective studies, and retrospective case series as the lowest level of evidence, we proceeded to design a logical decision-making algorithm, enhanced by our experiences as retinal surgeons. A total of 7 randomized-controlled clinical trials, 19 retrospective studies, and 9 case series were considered. Additional articles were also included in order to support the observations further. Rhegmatogenous retinal detachment is a potentially blinding disorder. Its surgical management seems to depend more on a surgeon´s preference than solid scientific data or is based on a good clinical history and examination. The algorithms proposed herein strive to offer a more rational approach to improve both anatomical and functional outcomes after the first surgery.
VELEZ-MONTOYA, Raul; JACOBO-OCEGUERA, Paola; FLORES-PRECIADO, Javier; DALMA-WEISZHAUSZ, Jose; GUERRERO-NARANJO, Jose; SALCEDO-VILLANUEVA, Guillermo; GARCIA-AGUIRRE, Gerardo; FROMOW-GUERRA, Jans; MORALES-CANTON, Virgilio
2016-01-01
We reviewed all the available data regarding the current management of non-complex rhegmatogenous retinal detachment and aimed to propose a new decision-making algorithm aimed to improve the single surgery success rate for mid-severity rhegmatogenous retinal detachment. An online review of the Pubmed database was performed. We searched for all available manuscripts about the anatomical and functional outcomes after the surgical management, by either scleral buckle or primary pars plana vitrectomy, of retinal detachment. The search was limited to articles published from January 1995 to December 2015. All articles obtained from the search were carefully screened and their references were manually reviewed for additional relevant data. Our search specifically focused on preoperative clinical data that were associated with the surgical outcomes. After categorizing the available data according to their level of evidence, with randomized-controlled clinical trials as the highest possible level of evidence, followed by retrospective studies, and retrospective case series as the lowest level of evidence, we proceeded to design a logical decision-making algorithm, enhanced by our experiences as retinal surgeons. A total of 7 randomized-controlled clinical trials, 19 retrospective studies, and 9 case series were considered. Additional articles were also included in order to support the observations further. Rhegmatogenous retinal detachment is a potentially blinding disorder. Its surgical management seems to depend more on a surgeon´s preference than solid scientific data or is based on a good clinical history and examination. The algorithms proposed herein strive to offer a more rational approach to improve both anatomical and functional outcomes after the first surgery. PMID:28289689
Why do patients engage in medical tourism?
Runnels, Vivien; Carrera, P M
2012-12-01
Medical tourism is commonly perceived and popularly depicted as an economic issue, both at the system and individual levels. The decision to engage in medical tourism, however, is more complex, driven by patients' unmet need, the nature of services sought and the manner by which treatment is accessed. In order to beneficially employ the opportunities medical tourism offers, and address and contain possible threats and harms, an informed decision is crucial. This paper aims to enhance the current knowledge on medical tourism by isolating the focal content of the decisions that patients make. Based on the existing literature, it proposes a sequential decision-making process in opting for or against medical care abroad, and engaging in medical tourism, including considerations of the required treatments, location of treatment, and quality and safety issues attendant to seeking care. Accordingly, it comments on the imperative of access to health information and the current regulatory environment which impact on this increasingly popular and complex form of accessing and providing medical care. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389
Huang, Guangzao; Yuan, Mingshun; Chen, Moliang; Li, Lei; You, Wenjie; Li, Hanjie; Cai, James J; Ji, Guoli
2017-10-07
The application of machine learning in cancer diagnostics has shown great promise and is of importance in clinic settings. Here we consider applying machine learning methods to transcriptomic data derived from tumor-educated platelets (TEPs) from individuals with different types of cancer. We aim to define a reliability measure for diagnostic purposes to increase the potential for facilitating personalized treatments. To this end, we present a novel classification method called MFRB (for Multiple Fitting Regression and Bayes decision), which integrates the process of multiple fitting regression (MFR) with Bayes decision theory. MFR is first used to map multidimensional features of the transcriptomic data into a one-dimensional feature. The probability density function of each class in the mapped space is then adjusted using the Gaussian probability density function. Finally, the Bayes decision theory is used to build a probabilistic classifier with the estimated probability density functions. The output of MFRB can be used to determine which class a sample belongs to, as well as to assign a reliability measure for a given class. The classical support vector machine (SVM) and probabilistic SVM (PSVM) are used to evaluate the performance of the proposed method with simulated and real TEP datasets. Our results indicate that the proposed MFRB method achieves the best performance compared to SVM and PSVM, mainly due to its strong generalization ability for limited, imbalanced, and noisy data.
Belmartino, Susana
2014-04-01
This article presents a comparative analysis of the processes leading to health care reform in Argentina and in the USA. The core of the analysis centers on the ideological references utilized by advocates of the reform and the decision-making processes that support or undercut such proposals. The analysis begins with a historical summary of the issue in each country. The political process that led to the sanction of the Obama reform is then described. The text defends a hypothesis aiming to show that deficiencies in the institutional capacities of Argentina's decision-making bodies are a severe obstacle to attaining substantial changes in this area within the country.
Research design of decision support system for team sport
NASA Astrophysics Data System (ADS)
Abidin, Mohammad Zukuwwan Zainol; Nawawi, Mohd Kamal Mohd; Kasim, Maznah Mat
2016-10-01
This paper proposes a suitable research procedure that can be referred to while conducting a Decision Support System (DSS) study, especially when the development activity of system artifacts becomes one of the research objectives. The design of the research procedure was based on the completion of a football DSS development that can help in determining the position of a player and the best team formation to be used during a game. After studying the relevant literature, we found that it is necessary to combine the conventional rainfall System Development Life Cycle (SDLC) approach with Case Study approach to help in structuring the research task and phases, which can contribute to the fulfillment of the research aim and objectives.
Abe, James; Lobo, Jennifer M; Trifiletti, Daniel M; Showalter, Timothy N
2017-08-24
Despite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. We report findings from a stakeholder engagement program that aimed to develop a framework for using Markov models with individualized model inputs, including genomics-based estimates of cancer recurrence probability, to generate personalized decision aids for prostate cancer patients faced with radiation therapy treatment decisions after prostatectomy. We engaged a total of 22 stakeholders, including: prostate cancer patients, urological surgeons, radiation oncologists, genomic testing industry representatives, and biomedical informatics faculty. Slides were at each meeting to provide background information regarding the analytical framework. Participants were invited to provide feedback during the meeting, including revising the overall project aims. Stakeholder meeting content was reviewed and summarized by stakeholder group and by theme. The majority of stakeholder suggestions focused on aspects of decision aid design and formatting. Stakeholders were enthusiastic about the potential value of using decision analysis modeling with personalized model inputs for cancer recurrence risk, as well as competing risks from age and comorbidities, to generate a patient-centered tool to assist decision-making. Stakeholders did not view privacy considerations as a major barrier to the proposed decision aid program. A common theme was that decision aids should be portable across multiple platforms (electronic and paper), should allow for interaction by the user to adjust model inputs iteratively, and available to patients both before and during consult appointments. Emphasis was placed on the challenge of explaining the model's composite result of quality-adjusted life years. A range of stakeholders provided valuable insights regarding the design of a personalized decision aid program, based upon Markov modeling with individualized model inputs, to provide a patient-centered framework to support for genomic-based treatment decisions for cancer patients. The guidance provided by our stakeholders may be broadly applicable to the communication of genomic test results to patients in a patient-centered fashion that supports effective shared decision-making that represents a spectrum of personal factors such as age, medical comorbidities, and individual priorities and values.
78 FR 4366 - Appeal Proceedings Before the Commission
Federal Register 2010, 2011, 2012, 2013, 2014
2013-01-22
... Commission's proposals to remove certificates of self-regulation, the Chair's decisions to approve or object... proposals to remove certificates of self- regulation, the Chair's decisions to approve or object to a tribal...'s proposal to remove a certificate of self-regulation, the Chair's decision to approve or object to...
Public health and valorization of genome-based technologies: a new model.
Lal, Jonathan A; Schulte In den Bäumen, Tobias; Morré, Servaas A; Brand, Angela
2011-12-05
The success rate of timely translation of genome-based technologies to commercially feasible products/services with applicability in health care systems is significantly low. We identified both industry and scientists neglect health policy aspects when commercializing their technology, more specifically, Public Health Assessment Tools (PHAT) and early on involvement of decision makers through which market authorization and reimbursements are dependent. While Technology Transfer (TT) aims to facilitate translation of ideas into products, Health Technology Assessment, one component of PHAT, for example, facilitates translation of products/processes into healthcare services and eventually comes up with recommendations for decision makers. We aim to propose a new model of valorization to optimize integration of genome-based technologies into the healthcare system. The method used to develop our model is an adapted version of the Fish Trap Model and the Basic Design Cycle. We found although different, similarities exist between TT and PHAT. Realizing the potential of being mutually beneficial justified our proposal of their relative parallel initiation. We observed that the Public Health Genomics Wheel should be included in this relative parallel activity to ensure all societal/policy aspects are dealt with preemptively by both stakeholders. On further analysis, we found out this whole process is dependent on the Value of Information. As a result, we present our LAL (Learning Adapting Leveling) model which proposes, based on market demand; TT and PHAT by consultation/bi-lateral communication should advocate for relevant technologies. This can be achieved by public-private partnerships (PPPs). These widely defined PPPs create the innovation network which is a developing, consultative/collaborative-networking platform between TT and PHAT. This network has iterations and requires learning, assimilating and using knowledge developed and is called absorption capacity. We hypothesize that the higher absorption capacity, higher success possibility. Our model however does not address the phasing out of technology although we believe the same model can be used to simultaneously phase out a technology. This model proposes to facilitate optimization/decrease the timeframe of integration in healthcare. It also helps industry and researchers to come to a strategic decision at an early stage, about technology being developed thus, saving on resources, hence minimizing failures.
Azadmanjir, Zahra; Safdari, Reza; Ghazisaeedi, Marjan; Mokhtaran, Mehrshad; Kameli, Mohammad Esmail
2017-01-01
Introduction: Accurate coded data in the healthcare are critical. Computer-Assisted Coding (CAC) is an effective tool to improve clinical coding in particular when a new classification will be developed and implemented. But determine the appropriate method for development need to consider the specifications of existing CAC systems, requirements for each type, our infrastructure and also, the classification scheme. Aim: The aim of the study was the development of a decision model for determining accurate code of each medical intervention in Iranian Classification of Health Interventions (IRCHI) that can be implemented as a suitable CAC system. Methods: first, a sample of existing CAC systems was reviewed. Then feasibility of each one of CAC types was examined with regard to their prerequisites for their implementation. The next step, proper model was proposed according to the structure of the classification scheme and was implemented as an interactive system. Results: There is a significant relationship between the level of assistance of a CAC system and integration of it with electronic medical documents. Implementation of fully automated CAC systems is impossible due to immature development of electronic medical record and problems in using language for medical documenting. So, a model was proposed to develop semi-automated CAC system based on hierarchical relationships between entities in the classification scheme and also the logic of decision making to specify the characters of code step by step through a web-based interactive user interface for CAC. It was composed of three phases to select Target, Action and Means respectively for an intervention. Conclusion: The proposed model was suitable the current status of clinical documentation and coding in Iran and also, the structure of new classification scheme. Our results show it was practical. However, the model needs to be evaluated in the next stage of the research. PMID:28883671
Emotion, Decision-Making and Substance Dependence: A Somatic-Marker Model of Addiction
Verdejo-García, A; Pérez-García, M; Bechara, A
2006-01-01
Similar to patients with orbitofrontal cortex lesions, substance dependent individuals (SDI) show signs of impairments in decision-making, characterised by a tendency to choose the immediate reward at the expense of severe negative future consequences. The somatic-marker hypothesis proposes that decision-making depends in many important ways on neural substrates that regulate homeostasis, emotion and feeling. According to this model, there should be a link between abnormalities in experiencing emotions in SDI, and their severe impairments in decision-making in real-life. Growing evidence from neuroscientific studies suggests that core aspects of substance addiction may be explained in terms of abnormal emotional guidance of decision-making. Behavioural studies have revealed emotional processing and decision-making deficits in SDI. Combined neuropsychological and physiological assessment has demonstrated that the poorer decision-making of SDI is associated with altered reactions to reward and punishing events. Imaging studies have shown that impaired decision-making in addiction is associated with abnormal functioning of a distributed neural network critical for the processing of emotional information, including the ventromedial cortex, the amygdala, the striatum, the anterior cingulate cortex, and the insular/somato-sensory cortices, as well as non-specific neurotransmitter systems that modulate activities of neural processes involved in decision-making. The aim of this paper is to review this growing evidence, and to examine the extent of which these studies support a somatic-marker model of addiction. PMID:18615136
The Assisted Decision-Making (Capacity) Bill 2013: content, commentary, controversy.
Kelly, B D
2015-03-01
Ireland's Assisted Decision-Making (Capacity) Bill (2013) aims to reform the law relating to persons who require assistance exercising their decision-making capacity. When finalised, the Bill will replace Ireland's outdated Ward of Court system which has an all-or-nothing approach to capacity; does not adequately define capacity; is poorly responsive to change; makes unwieldy provision for appointing decision-makers; and has insufficient provision for review. To explore the content and implications of the Assisted Decision-Making (Capacity) Bill. Review of the content of the Assisted Decision-Making (Capacity) Bill and related literature. The new Bill includes a presumption of capacity and defines lack of capacity. All interventions must minimise restriction of rights and freedom, and have due regard for "dignity, bodily integrity, privacy and autonomy". The Bill proposes legal frameworks for "assisted decision-making" (where an individual voluntarily appoints someone to assist with specific decisions relating to personal welfare or property and affairs, by, among other measures, assisting the individual to communicate his or her "will and preferences"); "co-decision-making" (where the Circuit Court declares the individual's capacity is reduced but he or she can make specific decisions with a co-decision-maker to share authority); "decision-making representatives" (substitute decision-making); "enduring power of attorney"; and "informal decision-making on personal welfare matters" (without apparent oversight). These measures, if implemented, will shift Ireland's capacity laws away from an approach based on "best interests" to one based on "will and preferences", and increase compliance with the United Nations' Convention on the Rights of Persons with Disabilities.
Zhang, Xiaodong; Huang, Guo H; Nie, Xianghui
2009-12-20
Nonpoint source (NPS) water pollution is one of serious environmental issues, especially within an agricultural system. This study aims to propose a robust chance-constrained fuzzy possibilistic programming (RCFPP) model for water quality management within an agricultural system, where solutions for farming area, manure/fertilizer application amount, and livestock husbandry size under different scenarios are obtained and interpreted. Through improving upon the existing fuzzy possibilistic programming, fuzzy robust programming and chance-constrained programming approaches, the RCFPP can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original fuzzy constraints, the RCFPP enhances the robustness of the optimization processes and resulting solutions. The results of the case study indicate that useful information can be obtained through the proposed RCFPP model for providing feasible decision schemes for different agricultural activities under different scenarios (combinations of different p-necessity and p(i) levels). A p-necessity level represents the certainty or necessity degree of the imprecise objective function, while a p(i) level means the probabilities at which the constraints will be violated. A desire to acquire high agricultural income would decrease the certainty degree of the event that maximization of the objective be satisfied, and potentially violate water management standards; willingness to accept low agricultural income will run into the risk of potential system failure. The decision variables under combined p-necessity and p(i) levels were useful for the decision makers to justify and/or adjust the decision schemes for the agricultural activities through incorporation of their implicit knowledge. The results also suggest that this developed approach is applicable to many practical problems where fuzzy and probabilistic distribution information simultaneously exist.
Underground Mining Method Selection Using WPM and PROMETHEE
NASA Astrophysics Data System (ADS)
Balusa, Bhanu Chander; Singam, Jayanthu
2018-04-01
The aim of this paper is to represent the solution to the problem of selecting suitable underground mining method for the mining industry. It is achieved by using two multi-attribute decision making techniques. These two techniques are weighted product method (WPM) and preference ranking organization method for enrichment evaluation (PROMETHEE). In this paper, analytic hierarchy process is used for weight's calculation of the attributes (i.e. parameters which are used in this paper). Mining method selection depends on physical parameters, mechanical parameters, economical parameters and technical parameters. WPM and PROMETHEE techniques have the ability to consider the relationship between the parameters and mining methods. The proposed techniques give higher accuracy and faster computation capability when compared with other decision making techniques. The proposed techniques are presented to determine the effective mining method for bauxite mine. The results of these techniques are compared with methods used in the earlier research works. The results show, conventional cut and fill method is the most suitable mining method.
Agreement Technologies for Energy Optimization at Home.
González-Briones, Alfonso; Chamoso, Pablo; De La Prieta, Fernando; Demazeau, Yves; Corchado, Juan M
2018-05-19
Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%.
NASA Astrophysics Data System (ADS)
Ghasemy Yaghin, R.; Fatemi Ghomi, S. M. T.; Torabi, S. A.
2015-10-01
In most markets, price differentiation mechanisms enable manufacturers to offer different prices for their products or services in different customer segments; however, the perfect price discrimination is usually impossible for manufacturers. The importance of accounting for uncertainty in such environments spurs an interest to develop appropriate decision-making tools to deal with uncertain and ill-defined parameters in joint pricing and lot-sizing problems. This paper proposes a hybrid bi-objective credibility-based fuzzy optimisation model including both quantitative and qualitative objectives to cope with these issues. Taking marketing and lot-sizing decisions into account simultaneously, the model aims to maximise the total profit of manufacturer and to improve service aspects of retailing simultaneously to set different prices with arbitrage consideration. After applying appropriate strategies to defuzzify the original model, the resulting non-linear multi-objective crisp model is then solved by a fuzzy goal programming method. An efficient stochastic search procedure using particle swarm optimisation is also proposed to solve the non-linear crisp model.
On decentralized design: Rationale, dynamics, and effects on decision-making
NASA Astrophysics Data System (ADS)
Chanron, Vincent
The focus of this dissertation is the design of complex systems, including engineering systems such as cars, airplanes, and satellites. Companies who design these systems are under constant pressure to design better products that meet customer expectations, and competition forces them to develop them faster. One of the responses of the industry to these conflicting challenges has been the decentralization of the design responsibilities. The current lack of understanding of the dynamics of decentralized design processes is the main motivation for this research, and places value on the descriptive base. It identifies the main reasons and the true benefits for companies to decentralize the design of their products. It also demonstrates the limitations of this approach by listing the relevant issues and problems created by the decentralization of decisions. Based on these observations, a game-theoretic approach to decentralized design is proposed to model the decisions made during the design process. The dynamics are modeled using mathematical formulations inspired from control theory. Building upon this formalism, the issue of convergence in decentralized design is analyzed: the equilibrium points of the design space are identified and convergent and divergent patterns are recognized. This rigorous investigation of the design process provides motivation and support for proposing new approaches to decentralized design problems. Two methods are developed, which aim at improving the design process in two ways: decreasing the product development time, and increasing the optimality of the final design. The frame of these methods are inspired by eigenstructure decomposition and set-based design, respectively. The value of the research detailed within this dissertation is in the proposed methods which are built upon the sound mathematical formalism developed. The contribution of this work is two fold: rigorous investigation of the design process, and practical support to decision-making in decentralized environments.
An overview of bipolar qualitative decision rules
NASA Astrophysics Data System (ADS)
Bonnefon, Jean-Francois; Dubois, Didier; Fargier, Hélène
Making a good decision is often a matter of listing and comparing positive and negative arguments, as studies in cognitive psychology have shown. In such cases, the evaluation scale should be considered bipolar, that is, negative and positive values are explicitly distinguished. Generally, positive and negative features are evaluated separately, as done in Cumulative Prospect Theory. However, contrary to the latter framework that presupposes genuine numerical assessments, decisions are often made on the basis of an ordinal ranking of the pros and the cons, and focusing on the most salient features, i.e., the decision process is qualitative. In this paper, we report on a project aiming at characterizing several decision rules, based on possibilistic order of magnitude reasoning, and tailored for the joint handling of positive and negative affects, and at testing their empirical validity. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case and, like them, suffer from a lack of discrimination power. More decisive rules that refine them are also proposed. They account for both the principle of Pareto-efficiency and the notion of order of magnitude reasoning. The most decisive one uses a lexicographic ranking of the pros and cons. It comes down to a special case of Cumulative Prospect Theory, and subsumes the “Take the best” heuristic.
Kriston, Levente; Meister, Ramona
2014-03-01
Judging applicability (relevance) of meta-analytical findings to particular clinical decision-making situations remains challenging. We aimed to describe an evidence synthesis method that accounts for possible uncertainty regarding applicability of the evidence. We conceptualized uncertainty regarding applicability of the meta-analytical estimates to a decision-making situation as the result of uncertainty regarding applicability of the findings of the trials that were included in the meta-analysis. This trial-level applicability uncertainty can be directly assessed by the decision maker and allows for the definition of trial inclusion probabilities, which can be used to perform a probabilistic meta-analysis with unequal probability resampling of trials (adaptive meta-analysis). A case study with several fictitious decision-making scenarios was performed to demonstrate the method in practice. We present options to elicit trial inclusion probabilities and perform the calculations. The result of an adaptive meta-analysis is a frequency distribution of the estimated parameters from traditional meta-analysis that provides individually tailored information according to the specific needs and uncertainty of the decision maker. The proposed method offers a direct and formalized combination of research evidence with individual clinical expertise and may aid clinicians in specific decision-making situations. Copyright © 2014 Elsevier Inc. All rights reserved.
Garrigan, Beverley; Adlam, Anna L R; Langdon, Peter E
2016-10-01
The aims of this systematic review were to determine: (a) which brain areas are consistently more active when making (i) moral response decisions, defined as choosing a response to a moral dilemma, or deciding whether to accept a proposed solution, or (ii) moral evaluations, defined as judging the appropriateness of another's actions in a moral dilemma, rating moral statements as right or wrong, or identifying important moral issues; and (b) shared and significantly different activation patterns for these two types of moral judgements. A systematic search of the literature returned 28 experiments. Activation likelihood estimate analysis identified the brain areas commonly more active for moral response decisions and for moral evaluations. Conjunction analysis revealed shared activation for both types of moral judgement in the left middle temporal gyrus, cingulate gyrus, and medial frontal gyrus. Contrast analyses found no significant clusters of increased activation for the moral evaluations-moral response decisions contrast, but found that moral response decisions additionally activated the left and right middle temporal gyrus and the right precuneus. Making one's own moral decisions involves different brain areas compared to judging the moral actions of others, implying that these judgements may involve different processes. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
40 CFR 154.23 - Proposed decision not to initiate a Special Review.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Proposed decision not to initiate a Special Review. 154.23 Section 154.23 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS SPECIAL REVIEW PROCEDURES Procedures § 154.23 Proposed decision not to initiate a Special...
Support Tool in the Diagnosis of Major Depressive Disorder
NASA Astrophysics Data System (ADS)
Nunes, Luciano Comin; Pinheiro, Plácido Rogério; Pequeno, Tarcísio Cavalcante; Pinheiro, Mirian Calíope Dantas
Major Depressive Disorder have been responsible for millions of professionals temporary removal, and even permanent, from diverse fields of activities around the world, generating damage to social, financial, productive systems and social security, and especially damage to the image of the individual and his family that these disorders produce in individuals who are patients, characteristics that make them stigmatized and discriminated into their society, making difficult their return to the production system. The lack of early diagnosis has provided reactive and late measures, only when the professional suffering psychological disorder is already showing signs of incapacity for working and social relationships. This article aims to assist in the decision making to establish early diagnosis of these types of psychological disorders. It presents a proposal for a hybrid model composed of expert system structured methodologies for decision support (Multi-Criteria Decision Analysis - MCDA) and representations of knowledge structured in logical rules of production and probabilities (Artificial Intelligence - AI).
Warmth of familiarity and chill of error: affective consequences of recognition decisions.
Chetverikov, Andrey
2014-04-01
The present research aimed to assess the effect of recognition decision on subsequent affective evaluations of recognised and non-recognised objects. Consistent with the proposed account of post-decisional preferences, results showed that the effect of recognition on preferences depends upon objective familiarity. If stimuli are recognised, liking ratings are positively associated with exposure frequency; if stimuli are not recognised, this link is either absent (Experiment 1) or negative (Experiments 2 and 3). This interaction between familiarity and recognition exists even when recognition accuracy is at chance level and the "mere exposure" effect is absent. Finally, data obtained from repeated measurements of preferences and using manipulations of task order confirm that recognition decisions have a causal influence on preferences. The findings suggest that affective evaluation can provide fine-grained access to the efficacy of cognitive processing even in simple cognitive tasks.
Mining balance disorders' data for the development of diagnostic decision support systems.
Exarchos, T P; Rigas, G; Bibas, A; Kikidis, D; Nikitas, C; Wuyts, F L; Ihtijarevic, B; Maes, L; Cenciarini, M; Maurer, C; Macdonald, N; Bamiou, D-E; Luxon, L; Prasinos, M; Spanoudakis, G; Koutsouris, D D; Fotiadis, D I
2016-10-01
In this work we present the methodology for the development of the EMBalance diagnostic Decision Support System (DSS) for balance disorders. Medical data from patients with balance disorders have been analysed using data mining techniques for the development of the diagnostic DSS. The proposed methodology uses various data, ranging from demographic characteristics to clinical examination, auditory and vestibular tests, in order to provide an accurate diagnosis. The system aims to provide decision support for general practitioners (GPs) and experts in the diagnosis of balance disorders as well as to provide recommendations for the appropriate information and data to be requested at each step of the diagnostic process. Detailed results are provided for the diagnosis of 12 balance disorders, both for GPs and experts. Overall, the reported accuracy ranges from 59.3 to 89.8% for GPs and from 74.3 to 92.1% for experts. Copyright © 2016 Elsevier Ltd. All rights reserved.
Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties
NASA Astrophysics Data System (ADS)
Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.
2017-12-01
Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.
Clarinval, Caroline; Biller-Andorno, Nikola
2014-01-01
Introduction: This paper aims to raise awareness regarding ethical issues in the context of humanitarian action, and to offer a framework for systematically and effectively addressing such issues. Methods: Several cases highlight ethical issues that humanitarian aid workers are confronted with at different levels over the course of their deployments. The first case discusses a situation at a macro-level concerning decisions being made at the headquarters of a humanitarian organization. The second case looks at meso-level issues that need to be solved at a country or regional level. The third case proposes an ethical dilemma at the micro-level of the individual patient-provider relationship. Discussion: These real-life cases have been selected to illustrate the ethical dimension of conflicts within the context of humanitarian action that might remain unrecognized in everyday practice. In addition, we propose an ethical framework to assist humanitarian aid workers in their decision-making process. The framework draws on the principles and values that guide humanitarian action and public health ethics more generally. Beyond identifying substantive core values, the framework also includes a ten-step process modelled on tools used in the clinical setting that promotes a transparent and clear decision-making process and improves the monitoring and evaluation of aid interventions. Finally, we recommend organizational measures to implement the framework effectively. Conclusion: This paper uses a combination of public health/clinical ethics concepts and practices and applies them to the decision-making challenges encountered in relief operations in the humanitarian aid context. PMID:24987575
Skyttberg, Niclas; Vicente, Joana; Chen, Rong; Blomqvist, Hans; Koch, Sabine
2016-06-04
Vital sign data are important for clinical decision making in emergency care. Clinical Decision Support Systems (CDSS) have been advocated to increase patient safety and quality of care. However, the efficiency of CDSS depends on the quality of the underlying vital sign data. Therefore, possible factors affecting vital sign data quality need to be understood. This study aims to explore the factors affecting vital sign data quality in Swedish emergency departments and to determine in how far clinicians perceive vital sign data to be fit for use in clinical decision support systems. A further aim of the study is to provide recommendations on how to improve vital sign data quality in emergency departments. Semi-structured interviews were conducted with sixteen physicians and nurses from nine hospitals and vital sign documentation templates were collected and analysed. Follow-up interviews and process observations were done at three of the hospitals to verify the results. Content analysis with constant comparison of the data was used to analyse and categorize the collected data. Factors related to care process and information technology were perceived to affect vital sign data quality. Despite electronic health records (EHRs) being available in all hospitals, these were not always used for vital sign documentation. Only four out of nine sites had a completely digitalized vital sign documentation flow and paper-based triage records were perceived to provide a better mobile workflow support than EHRs. Observed documentation practices resulted in low currency, completeness, and interoperability of the vital signs. To improve vital sign data quality, we propose to standardize the care process, improve the digital documentation support, provide workflow support, ensure interoperability and perform quality control. Vital sign data quality in Swedish emergency departments is currently not fit for use by CDSS. To address both technical and organisational challenges, we propose five steps for vital sign data quality improvement to be implemented in emergency care settings.
AI in medical education--another grand challenge for medical informatics.
Lillehaug, S I; Lajoie, S P
1998-03-01
The potential benefits of artificial intelligence in medicine (AIM) were never realized as anticipated. This paper addresses ways in which such potential can be achieved. Recent discussions of this topic have proposed a stronger integration between AIM applications and health information systems, and emphasize computer guidelines to support the new health care paradigms of evidence-based medicine and cost-effectiveness. These proposals, however, promote the initial definition of AIM applications as being AI systems that can perform or aid in diagnoses. We challenge this traditional philosophy of AIM and propose a new approach aiming at empowering health care workers to become independent self-sufficient problem solvers and decision makers. Our philosophy is based on findings from a review of empirical research that examines the relationship between the health care personnel's level of knowledge and skills, their job satisfaction, and the quality of the health care they provide. This review supports addressing the quality of health care by empowering health care workers to reach their full potential. As an aid in this empowerment process we argue for reviving a long forgotten AIM research area, namely, AI based applications for medical education and training. There is a growing body of research in artificial intelligence in education that demonstrates that the use of artificial intelligence can enhance learning in numerous domains. By examining the strengths of these educational applications and the results from previous AIM research we derive a framework for empowering medical personnel and consequently raising the quality of health care through the use of advanced AI based technology.
EmoBurnout: An Approach for Supporting Burnout Syndrome Diagnosis.
Martinez, Esteban; Mera, Giovanni; González, Carolina; López, Diego M; Blobel, Bernd
2015-01-01
Burnout is scientifically a work related syndrome which consists of three dimensions: emotional exhaustion, depersonalization and reduced professional efficacy. Different instruments for the diagnosis of burnout exist, accompanied by many associated problems, however. This paper describes a proposal aiming at supporting the diagnosis of burnout using measures complementary to the Maslach Burnout Inventory (MBI). It specifically focuses on emotions detection to provide useful information that contributes to the decision making process about the syndrome.
Bouzguenda, Lotfi; Turki, Manel
2014-04-01
This paper shows how the combined use of agent and web services technologies can help to design an architectural style for dynamic medical Cross-Organizational Workflow (COW) management system. Medical COW aims at supporting the collaboration between several autonomous and possibly heterogeneous medical processes, distributed over different organizations (Hospitals, Clinic or laboratories). Dynamic medical COW refers to occasional cooperation between these health organizations, free of structural constraints, where the medical partners involved and their number are not pre-defined. More precisely, this paper proposes a new architecture style based on agents and web services technologies to deal with two key coordination issues of dynamic COW: medical partners finding and negotiation between them. It also proposes how the proposed architecture for dynamic medical COW management system can connect to a multi-agent system coupling the Clinical Decision Support System (CDSS) with Computerized Prescriber Order Entry (CPOE). The idea is to assist the health professionals such as doctors, nurses and pharmacists with decision making tasks, as determining diagnosis or patient data analysis without stopping their clinical processes in order to act in a coherent way and to give care to the patient.
Chronic Heart Failure Follow-up Management Based on Agent Technology
Safdari, Reza
2015-01-01
Objectives Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. Methods This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Results Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. Conclusions The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making. PMID:26618038
A Generalized Quantum-Inspired Decision Making Model for Intelligent Agent
Loo, Chu Kiong
2014-01-01
A novel decision making for intelligent agent using quantum-inspired approach is proposed. A formal, generalized solution to the problem is given. Mathematically, the proposed model is capable of modeling higher dimensional decision problems than previous researches. Four experiments are conducted, and both empirical experiments results and proposed model's experiment results are given for each experiment. Experiments showed that the results of proposed model agree with empirical results perfectly. The proposed model provides a new direction for researcher to resolve cognitive basis in designing intelligent agent. PMID:24778580
An approximate dynamic programming approach to resource management in multi-cloud scenarios
NASA Astrophysics Data System (ADS)
Pietrabissa, Antonio; Priscoli, Francesco Delli; Di Giorgio, Alessandro; Giuseppi, Alessandro; Panfili, Martina; Suraci, Vincenzo
2017-03-01
The programmability and the virtualisation of network resources are crucial to deploy scalable Information and Communications Technology (ICT) services. The increasing demand of cloud services, mainly devoted to the storage and computing, requires a new functional element, the Cloud Management Broker (CMB), aimed at managing multiple cloud resources to meet the customers' requirements and, simultaneously, to optimise their usage. This paper proposes a multi-cloud resource allocation algorithm that manages the resource requests with the aim of maximising the CMB revenue over time. The algorithm is based on Markov decision process modelling and relies on reinforcement learning techniques to find online an approximate solution.
Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach
NASA Astrophysics Data System (ADS)
Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi
Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.
NASA Astrophysics Data System (ADS)
Arthurs, Leilani A.; Kreager, Bailey Zo
2017-10-01
Engaging students in active learning is linked to positive learning outcomes. This study aims to synthesise the peer-reviewed literature about 'active learning' in college science classroom settings. Using the methodology of an integrative literature review, 337 articles archived in the Educational Resources Information Center (ERIC) are examined. Four categories of in-class activities emerge: (i) individual non-polling activities, (ii) in-class polling activities, (iii) whole-class discussion or activities, and (iv) in-class group activities. Examining the collection of identified in-class activities through the lens of a theoretical framework informed by constructivism and social interdependence theory, we synthesise the reviewed literature to propose the active learning strategies (ALSs) model and the instructional decisions to enable active learning (IDEAL) theory. The ALS model characterises in-class activities in terms of the degrees to which they are designed to promote (i) peer interaction and (ii) social interdependence. The IDEAL theory includes the ALS model and provides a framework for conceptualising different levels of the general concept 'active learning' and how these levels connect to instructional decision-making about using in-class activities. The proposed ALS model and IDEAL theory can be utilised to inform instructional decision-making and future research about active learning in college science courses.
Ye, Yalan; He, Wenwen; Cheng, Yunfei; Huang, Wenxia; Zhang, Zhilin
2017-02-16
The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking.
Multiple attribute decision making model and application to food safety risk evaluation.
Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng
2017-01-01
Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.
Demeter, Sandor J
2016-12-21
Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals.
Societal values in the allocation of healthcare resources: is it all about the health gain?
Stafinski, Tania; Menon, Devidas; Marshall, Deborah; Caulfield, Timothy
2011-01-01
Over the past decade, public distrust in unavoidable value-laden decisions on the allocation of resources to new health technologies has grown. In response, healthcare organizations have made considerable efforts to improve their acceptability by increasing transparency in decision-making processes. However, the social value judgments (distributive preferences of the public) embedded in them have yet to be defined. While the need to explicate such judgments has become widely recognized, the most appropriate approach to accomplishing this remains unclear. The aims of this review were to identify factors around which distributive preferences of the public have been sought, create a list of social values proposed or used in current resource allocation decision-making processes for new health technologies, and review approaches to eliciting such values from the general public. Social values proposed or used in making resource allocation decisions for new health technologies were identified through three approaches: (i) a comprehensive review of published, peer-reviewed, empirical studies of public preferences for the distribution of healthcare; (ii) an analysis of non-technical factors or social value statements considered by technology funding decision-making processes in Canada and abroad; and (iii) a review of appeals to funding decisions on grounds in part related to social value judgments. A total of 34 empirical studies, 10 technology funding decision-making processes, and 12 appeals to decisions were identified and reviewed. The key factors/patient characteristics addressed through policy statements and around which distributive preferences of the public have been sought included severity of illness, immediate need, age (and its relationship to lifetime health), health gain (amount and final outcome/health state), personal responsibility for illness, caregiving responsibilities, and number of patients who could benefit (rarity). Empirical studies typically examined the importance of these factors in isolation. Therefore, the extent to which preferences around one factor may be modified in the presence of others is still unclear. Research that seeks to clarify interactions among factors by asking the public to weigh several of them at once is needed to ensure the relevance of elicited preferences to real-world technology funding decisions.
Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J
2015-03-15
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.
Motivational Reasons for Biased Decisions: The Sunk-Cost Effect's Instrumental Rationality.
Domeier, Markus; Sachse, Pierre; Schäfer, Bernd
2018-01-01
The present study describes the mechanism of need regulation, which accompanies the so-called "biased" decisions. We hypothesized an unconscious urge for psychological need satisfaction as the trigger for cognitive biases. In an experimental study ( N = 106), participants had the opportunity to win money in a functionality test. In the test, they could either use the solution they had developed (sunk cost) or an alternative solution that offered a higher probability of winning. The selection of the sunk-cost option (SCO) was the most chosen option, supporting the hypothesis of this study. The reason behind the majority of participants choosing the SCO seemed to be the satisfaction of psychological needs, despite a reduced chance of winning money. An intervention, which aimed at triggering self-reflection, had no impact on the decision. The findings of this study contribute to the discussion on the reasons for cognitive biases and their formation in the human mind. Moreover, it discusses the application of the label "irrational" for biased decisions and proposes reasons for instrumental rationality, which exist at an unconscious, need-regulative level.
Klostermann, André; Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim
2015-01-01
For perceptual-cognitive skill training, a variety of intervention methods has been proposed, including the so-called “color-cueing method” which aims on superior gaze-path learning by applying visual markers. However, recent findings challenge this method, especially, with regards to its actual effects on gaze behavior. Consequently, after a preparatory study on the identification of appropriate visual cues for life-size displays, a perceptual-training experiment on decision-making in beach volleyball was conducted, contrasting two cueing interventions (functional vs. dysfunctional gaze path) with a conservative control condition (anticipation-related instructions). Gaze analyses revealed learning effects for the dysfunctional group only. Regarding decision-making, all groups showed enhanced performance with largest improvements for the control group followed by the functional and the dysfunctional group. Hence, the results confirm cueing effects on gaze behavior, but they also question its benefit for enhancing decision-making. However, before completely denying the method’s value, optimisations should be checked regarding, for instance, cueing-pattern characteristics and gaze-related feedback. PMID:26648894
Merkel cell carcinoma: An algorithm for multidisciplinary management and decision-making.
Prieto, Isabel; Pérez de la Fuente, Teresa; Medina, Susana; Castelo, Beatriz; Sobrino, Beatriz; Fortes, Jose R; Esteban, David; Cassinello, Fernando; Jover, Raquel; Rodríguez, Nuria
2016-02-01
Merkel cell carcinoma (MCC) is a rare and aggressive neuroendocrine tumor of the skin. Therapeutic approach is often unclear, and considerable controversy exists regarding MCC pathogenesis and optimal management. Due to its rising incidence and poor prognosis, it is imperative to establish the optimal therapy for both the tumor and the lymph node basin, and for treatment to include sentinel node biopsy. Sentinel node biopsy is currently the most consistent predictor of survival for MCC patients, although there are conflicting views and a lack of awareness regarding node management. Tumor and node management involve different specialists, and their respective decisions and interventions are interrelated. No effective systemic treatment has been made available to date, and therefore patients continue to experience distant failure, often without local failure. This review aims to improve multidisciplinary decision-making by presenting scientific evidence of the contributions of each team member implicated in MCC management. Following this review of previously published research, the authors conclude that multidisciplinary team management is beneficial for care, and propose a multidisciplinary decision algorithm for managing this tumor. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Motivational Reasons for Biased Decisions: The Sunk-Cost Effect’s Instrumental Rationality
Domeier, Markus; Sachse, Pierre; Schäfer, Bernd
2018-01-01
The present study describes the mechanism of need regulation, which accompanies the so-called “biased” decisions. We hypothesized an unconscious urge for psychological need satisfaction as the trigger for cognitive biases. In an experimental study (N = 106), participants had the opportunity to win money in a functionality test. In the test, they could either use the solution they had developed (sunk cost) or an alternative solution that offered a higher probability of winning. The selection of the sunk-cost option (SCO) was the most chosen option, supporting the hypothesis of this study. The reason behind the majority of participants choosing the SCO seemed to be the satisfaction of psychological needs, despite a reduced chance of winning money. An intervention, which aimed at triggering self-reflection, had no impact on the decision. The findings of this study contribute to the discussion on the reasons for cognitive biases and their formation in the human mind. Moreover, it discusses the application of the label “irrational” for biased decisions and proposes reasons for instrumental rationality, which exist at an unconscious, need-regulative level. PMID:29881366
Federal Register 2010, 2011, 2012, 2013, 2014
2010-02-23
... DEPARTMENT OF AGRICULTURE Agricultural Marketing Service 7 CFR Part 920 [Doc. No. AO-FV-08-0174... on Proposed Amendments to Marketing Order No. 920 AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule and referendum order. SUMMARY: This decision proposes amendments to Marketing Order...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1976-11-29
The Federal Aviation Administration has determined not to prescribe the proposed amendment to the FAA Regulations as submitted by the Environmental Protection Agency (40 F.R. 1072) on January 6, 1975, regarding noise abatement minimum altitudes for civil turbojet-powered airplanes. Instead, an internal directive is being issued aimed at the air traffic control function, which is designed to firmly integrate safety, fuel conservation, and noise abatement objectives into a single national program. It provides the flexibility needed to allow and encourage change with experience. (PCS)
Integrating Personalized and Community Services for Mobile Travel Planning and Management
NASA Astrophysics Data System (ADS)
Yu, Chien-Chih
Personalized and community services have been noted as keys to enhance and facilitate e-tourism as well as mobile applications. This paper aims at proposing an integrated service framework for combining personalized and community functions to support mobile travel planning and management. Major mobile tourism related planning and decision support functions specified include personalized profile management, information search and notification, evaluation and recommendation, do-it-yourself planning and design, community and collaboration management, auction and negotiation, transaction and payment, as well as trip tracking and quality control. A system implementation process with an example prototype is also presented for illustrating the feasibility and effectiveness of the proposed system framework, process model, and development methodology.
A new web-based framework development for fuzzy multi-criteria group decision-making.
Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik
2016-01-01
Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.
Public health and valorization of genome-based technologies: a new model
2011-01-01
Background The success rate of timely translation of genome-based technologies to commercially feasible products/services with applicability in health care systems is significantly low. We identified both industry and scientists neglect health policy aspects when commercializing their technology, more specifically, Public Health Assessment Tools (PHAT) and early on involvement of decision makers through which market authorization and reimbursements are dependent. While Technology Transfer (TT) aims to facilitate translation of ideas into products, Health Technology Assessment, one component of PHAT, for example, facilitates translation of products/processes into healthcare services and eventually comes up with recommendations for decision makers. We aim to propose a new model of valorization to optimize integration of genome-based technologies into the healthcare system. Methods The method used to develop our model is an adapted version of the Fish Trap Model and the Basic Design Cycle. Results We found although different, similarities exist between TT and PHAT. Realizing the potential of being mutually beneficial justified our proposal of their relative parallel initiation. We observed that the Public Health Genomics Wheel should be included in this relative parallel activity to ensure all societal/policy aspects are dealt with preemptively by both stakeholders. On further analysis, we found out this whole process is dependent on the Value of Information. As a result, we present our LAL (Learning Adapting Leveling) model which proposes, based on market demand; TT and PHAT by consultation/bi-lateral communication should advocate for relevant technologies. This can be achieved by public-private partnerships (PPPs). These widely defined PPPs create the innovation network which is a developing, consultative/collaborative-networking platform between TT and PHAT. This network has iterations and requires learning, assimilating and using knowledge developed and is called absorption capacity. We hypothesize that the higher absorption capacity, higher success possibility. Our model however does not address the phasing out of technology although we believe the same model can be used to simultaneously phase out a technology. Conclusions This model proposes to facilitate optimization/decrease the timeframe of integration in healthcare. It also helps industry and researchers to come to a strategic decision at an early stage, about technology being developed thus, saving on resources, hence minimizing failures. PMID:22142533
NASA Astrophysics Data System (ADS)
Mesbah, Mostefa; Balakrishnan, Malarvili; Colditz, Paul B.; Boashash, Boualem
2012-12-01
This article proposes a new method for newborn seizure detection that uses information extracted from both multi-channel electroencephalogram (EEG) and a single channel electrocardiogram (ECG). The aim of the study is to assess whether additional information extracted from ECG can improve the performance of seizure detectors based solely on EEG. Two different approaches were used to combine this extracted information. The first approach, known as feature fusion, involves combining features extracted from EEG and heart rate variability (HRV) into a single feature vector prior to feeding it to a classifier. The second approach, called classifier or decision fusion, is achieved by combining the independent decisions of the EEG and the HRV-based classifiers. Tested on recordings obtained from eight newborns with identified EEG seizures, the proposed neonatal seizure detection algorithms achieved 95.20% sensitivity and 88.60% specificity for the feature fusion case and 95.20% sensitivity and 94.30% specificity for the classifier fusion case. These results are considerably better than those involving classifiers using EEG only (80.90%, 86.50%) or HRV only (85.70%, 84.60%).
Bazzani, Roberto; Levcovitz, Eduardo; Urrutia, Soledad; Zarowsky, Christina
2006-01-01
The Pan American Health Organization (PAHO) and International Development Research Centre (IDRC) have promoted a joint initiative to design, implement, and evaluate innovative strategies for the Extension of Social Protection in Health (SPH) in Latin America and the Caribbean (LAC), involving active partnership between researchers and research users. This initiative was based on a previous review of research on health sector reforms and the recommendations of the workshop on "Health Sector Reforms in the Americas: Strengthening the Links between Research and Policy" (Montreal, Canada, 2001). In its first phase, the initiative supported the development of proposals aiming to extend SPH, elaborated jointly by researchers and decision-makers. In the second phase, the implementation of five of these proposals was supported in order to promote the development of new SPH strategies and new stakeholder interaction models. In this edition of the journal, the process of linking researchers and decision-makers will be analyzed in the context of the five projects supported by this initiative.
Expanded DEMATEL for Determining Cause and Effect Group in Bidirectional Relations
Falatoonitoosi, Elham; Ahmed, Shamsuddin; Sorooshian, Shahryar
2014-01-01
Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology has been proposed to solve complex and intertwined problem groups in many situations such as developing the capabilities, complex group decision making, security problems, marketing approaches, global managers, and control systems. DEMATEL is able to realize casual relationships by dividing important issues into cause and effect group as well as making it possible to visualize the casual relationships of subcriteria and systems in the course of casual diagram that it may demonstrate communication network or a little control relationships between individuals. Despite of its ability to visualize cause and effect inside a network, the original DEMATEL has not been able to find the cause and effect group between different networks. Therefore, the aim of this study is proposing the expanded DEMATEL to cover this deficiency by new formulations to determine cause and effect factors between separate networks that have bidirectional direct impact on each other. At the end, the feasibility of new extra formulations is validated by case study in three numerical examples of green supply chain networks for an automotive company. PMID:24693224
Expanded DEMATEL for determining cause and effect group in bidirectional relations.
Falatoonitoosi, Elham; Ahmed, Shamsuddin; Sorooshian, Shahryar
2014-01-01
Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology has been proposed to solve complex and intertwined problem groups in many situations such as developing the capabilities, complex group decision making, security problems, marketing approaches, global managers, and control systems. DEMATEL is able to realize casual relationships by dividing important issues into cause and effect group as well as making it possible to visualize the casual relationships of subcriteria and systems in the course of casual diagram that it may demonstrate communication network or a little control relationships between individuals. Despite of its ability to visualize cause and effect inside a network, the original DEMATEL has not been able to find the cause and effect group between different networks. Therefore, the aim of this study is proposing the expanded DEMATEL to cover this deficiency by new formulations to determine cause and effect factors between separate networks that have bidirectional direct impact on each other. At the end, the feasibility of new extra formulations is validated by case study in three numerical examples of green supply chain networks for an automotive company.
Agreement Technologies for Energy Optimization at Home
2018-01-01
Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%. PMID:29783768
NASA Astrophysics Data System (ADS)
Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero
2014-10-01
Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.
77 FR 15368 - Clean Water Act; Availability of List Decisions
Federal Register 2010, 2011, 2012, 2013, 2014
2012-03-15
... ENVIRONMENTAL PROTECTION AGENCY [FRL-9646-9] Clean Water Act; Availability of List Decisions...) proposed decision identifying water quality limited segments and associated pollutants in Oregon to be listed pursuant to section 303(d)(2) of the Clean Water Act (CWA). EPA is proposing to add 1004 water...
78 FR 26747 - Oglethorpe Power Corporation: Proposed Biomass Power Plant
Federal Register 2010, 2011, 2012, 2013, 2014
2013-05-08
.... Accordingly, comments submitted in the EIS process also informed RUS's decision making in the Section 106... Decision. SUMMARY: The Rural Utilities Service (RUS) has issued a Record of Decision (ROD) for the... take into account the effect of the Proposal on historic properties in [[Page 26748
Customer-Specific Transaction Risk Management in E-Commerce
NASA Astrophysics Data System (ADS)
Ruch, Markus; Sackmann, Stefan
Increasing potential for turnover in e-commerce is inextricably linked with an increase in risk. Online retailers (e-tailers), aiming for a company-wide value orientation should manage this risk. However, current approaches to risk management either use average retail prices elevated by an overall risk premium or restrict the payment methods offered to customers. Thus, they neglect customer-specific value and risk attributes and leave turnover potentials unconsidered. To close this gap, an innovative valuation model is proposed in this contribution that integrates customer-specific risk and potential turnover. The approach presented evaluates different payment methods using their risk-turnover characteristic, provides a risk-adjusted decision basis for selecting payment methods and allows e-tailers to derive automated risk management decisions per customer and transaction without reducing turnover potential.
NextGen Future Safety Assessment Game
NASA Technical Reports Server (NTRS)
Ancel, Ersin; Gheorghe, Adian; Jones, Sharon Monica
2010-01-01
The successful implementation of the next generation infrastructure systems requires solid understanding of their technical, social, political and economic aspects along with their interactions. The lack of historical data that relate to the long-term planning of complex systems introduces unique challenges for decision makers and involved stakeholders which in turn result in unsustainable systems. Also, the need to understand the infrastructure at the societal level and capture the interaction between multiple stakeholders becomes important. This paper proposes a methodology in order to develop a holistic approach aiming to provide an alternative subject-matter expert (SME) elicitation and data collection method for future sociotechnical systems. The methodology is adapted to Next Generation Air Transportation System (NextGen) decision making environment in order to demonstrate the benefits of this holistic approach.
NextGen Future Safety Assessment Game
NASA Technical Reports Server (NTRS)
Ancel, Ersin; Gheorghe, Adrian; Jones, Sharon Monica
2011-01-01
The successful implementation of the next generation infrastructure systems requires solid understanding of their technical, social, political and economic aspects along with their interactions. The lack of historical data that relate to the long-term planning of complex systems introduces unique challenges for decision makers and involved stakeholders which in turn result in unsustainable systems. Also, the need to understand the infrastructure at the societal level and capture the interaction between multiple stakeholders becomes important. This paper proposes a methodology in order to develop a holistic approach aiming to provide an alternative subject-matter expert (SME) elicitation and data collection method for future sociotechnical systems. The methodology is adapted to Next Generation Air Transportation System (NextGen) decision making environment in order to demonstrate the benefits of this holistic approach.
Markopoulos, Constantinos; Andreas, Cord J; Vertzoni, Maria; Dressman, Jennifer; Reppas, Christos
2015-06-01
Biorelevant media for evaluation of dosage form performance in the gastrointestinal lumen were first introduced in the late 1990s. Since then, a variety of additional media have been proposed, making it now possible to simulate most regions in the gastrointestinal tract in both prandial states. However, recent work suggests that the complexity and degree of biorelevance required to predict in-vivo release varies with the drug, dosage form and dosing conditions. The aim of this commentary was to establish which levels of biorelevant media are appropriate to various combinations of active pharmaceutical ingredient(s), dosage form and dosing conditions. With regard to their application, a decision tree for the selection of the appropriate biorelevant medium/media is proposed and illustrative case scenarios are provided. Additionally, media to represent the distal small intestine in both prandial states are presented. The newly proposed levels of biorelevance and accompanying decision tree may serve as a useful tool during formulation development in order to ensure high quality, predictive performance results without unnecessary complexity of media. In future work, further specific case examples will be evolved, which will additionally address the need to take gastrointestinal passage times and type and intensity of agitation into consideration. Copyright © 2015 Elsevier B.V. All rights reserved.
Limited Rationality and Its Quantification Through the Interval Number Judgments With Permutations.
Liu, Fang; Pedrycz, Witold; Zhang, Wei-Guo
2017-12-01
The relative importance of alternatives expressed in terms of interval numbers in the fuzzy analytic hierarchy process aims to capture the uncertainty experienced by decision makers (DMs) when making a series of comparisons. Under the assumption of full rationality, the judgements of DMs in the typical analytic hierarchy process could be consistent. However, since the uncertainty in articulating the opinions of DMs is unavoidable, the interval number judgements are associated with the limited rationality. In this paper, we investigate the concept of limited rationality by introducing interval multiplicative reciprocal comparison matrices. By analyzing the consistency of interval multiplicative reciprocal comparison matrices, it is observed that the interval number judgements are inconsistent. By considering the permutations of alternatives, the concepts of approximation-consistency and acceptable approximation-consistency of interval multiplicative reciprocal comparison matrices are proposed. The exchange method is designed to generate all the permutations. A novel method of determining the interval weight vector is proposed under the consideration of randomness in comparing alternatives, and a vector of interval weights is determined. A new algorithm of solving decision making problems with interval multiplicative reciprocal preference relations is provided. Two numerical examples are carried out to illustrate the proposed approach and offer a comparison with the methods available in the literature.
NASA Astrophysics Data System (ADS)
Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying
Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.
How to Assess the Value of Medicines?
Simoens, Steven
2010-01-01
This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value. PMID:21607066
How to assess the value of medicines?
Simoens, Steven
2010-01-01
This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value.
NASA Astrophysics Data System (ADS)
Khalilpourazari, Soheyl; Khalilpourazary, Saman
2017-05-01
In this article a multi-objective mathematical model is developed to minimize total time and cost while maximizing the production rate and surface finish quality in the grinding process. The model aims to determine optimal values of the decision variables considering process constraints. A lexicographic weighted Tchebycheff approach is developed to obtain efficient Pareto-optimal solutions of the problem in both rough and finished conditions. Utilizing a polyhedral branch-and-cut algorithm, the lexicographic weighted Tchebycheff model of the proposed multi-objective model is solved using GAMS software. The Pareto-optimal solutions provide a proper trade-off between conflicting objective functions which helps the decision maker to select the best values for the decision variables. Sensitivity analyses are performed to determine the effect of change in the grain size, grinding ratio, feed rate, labour cost per hour, length of workpiece, wheel diameter and downfeed of grinding parameters on each value of the objective function.
Cost-effectiveness modelling in diagnostic imaging: a stepwise approach.
Sailer, Anna M; van Zwam, Wim H; Wildberger, Joachim E; Grutters, Janneke P C
2015-12-01
Diagnostic imaging (DI) is the fastest growing sector in medical expenditures and takes a central role in medical decision-making. The increasing number of various and new imaging technologies induces a growing demand for cost-effectiveness analysis (CEA) in imaging technology assessment. In this article we provide a comprehensive framework of direct and indirect effects that should be considered for CEA in DI, suitable for all imaging modalities. We describe and explain the methodology of decision analytic modelling in six steps aiming to transfer theory of CEA to clinical research by demonstrating key principles of CEA in a practical approach. We thereby provide radiologists with an introduction to the tools necessary to perform and interpret CEA as part of their research and clinical practice. • DI influences medical decision making, affecting both costs and health outcome. • This article provides a comprehensive framework for CEA in DI. • A six-step methodology for conducting and interpreting cost-effectiveness modelling is proposed.
Taroni, F; Biedermann, A; Bozza, S
2016-02-01
Many people regard the concept of hypothesis testing as fundamental to inferential statistics. Various schools of thought, in particular frequentist and Bayesian, have promoted radically different solutions for taking a decision about the plausibility of competing hypotheses. Comprehensive philosophical comparisons about their advantages and drawbacks are widely available and continue to span over large debates in the literature. More recently, controversial discussion was initiated by an editorial decision of a scientific journal [1] to refuse any paper submitted for publication containing null hypothesis testing procedures. Since the large majority of papers published in forensic journals propose the evaluation of statistical evidence based on the so called p-values, it is of interest to expose the discussion of this journal's decision within the forensic science community. This paper aims to provide forensic science researchers with a primer on the main concepts and their implications for making informed methodological choices. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Cost-effectiveness in Clostridium difficile treatment decision-making.
Nuijten, Mark Jc; Keller, Josbert J; Visser, Caroline E; Redekop, Ken; Claassen, Eric; Speelman, Peter; Pronk, Marja H
2015-11-16
To develop a framework for the clinical and health economic assessment for management of Clostridium difficile infection (CDI). CDI has vast economic consequences emphasizing the need for innovative and cost effective solutions, which were aim of this study. A guidance model was developed for coverage decisions and guideline development in CDI. The model included pharmacotherapy with oral metronidazole or oral vancomycin, which is the mainstay for pharmacological treatment of CDI and is recommended by most treatment guidelines. A design for a patient-based cost-effectiveness model was developed, which can be used to estimate the cost-effectiveness of current and future treatment strategies in CDI. Patient-based outcomes were extrapolated to the population by including factors like, e.g., person-to-person transmission, isolation precautions and closing and cleaning wards of hospitals. The proposed framework for a population-based CDI model may be used for clinical and health economic assessments of CDI guidelines and coverage decisions for emerging treatments for CDI.
Use of a decision aid did not decrease decisional conflict in patients with carpal tunnel syndrome.
Gong, Hyun Sik; Park, Jin Woo; Shin, Young Ho; Kim, Kahyun; Cho, Kwan Jae; Baek, Goo Hyun
2017-03-21
Although a model for shared decision-making is important for patient-centered care, decisional conflict can emerge when patients participate in the decision-making. A decision aid is proposed to provide information and to involve patients more comfortably in the decision-making process. We aimed to determine whether a decision aid helps patients with carpal tunnel syndrome (CTS) experience less decisional conflict regarding their decision-making for surgery. Eighty patients with CTS were randomized into two groups. The test group was given a decision aid in addition to regular information and the control group regular information only. The decision aid consisted of a 6-min videoclip that explains diagnosis and information regarding surgery for CTS with other treatment options. We evaluated patients' decisional conflict regarding surgery, knowledge about CTS, and symptom severity as measured by the Disabilities of Arm, Shoulder, and Hand (DASH) Questionnaire. There was no difference in the decisional conflict scale (DCS) between both groups (p = 0.76). The test group had significantly better knowledge than the control group (p = 0.04). There was no correlation between the knowledge score and the DCS (p = 0.76). However, less severe symptoms were correlated with greater decisional conflict (r = -0.29, p = 0.02). We found that a decision aid does not reduce decisional conflict in patients with CTS, although it can help them be better informed. This study suggests that although a decision-aid is effective for patient education, doctor-patient communication should be more emphasized for patients with less severe symptoms, as they can have greater decisional conflict. SNUBH Registry 1510/317-003 Registered November 13, 2015.
A Conceptual Model of the Role of Communication in Surrogate Decision Making for Hospitalized Adults
Torke, Alexia M.; Petronio, Sandra; Sachs, Greg A.; Helft, Paul R.; Purnell, Christianna
2011-01-01
Objective To build a conceptual model of the role of communication in decision making, based on literature from medicine, communication studies and medical ethics. Methods We propose a model and describe each construct in detail. We review what is known about interpersonal and patient-physician communication, describe literature about surrogate-clinician communication, and discuss implications for our developing model. Results The communication literature proposes two major elements of interpersonal communication: information processing and relationship building. These elements are composed of constructs such as information disclosure and emotional support that are likely to be relevant to decision making. We propose these elements of communication impact decision making, which in turn affects outcomes for both patients and surrogates. Decision making quality may also mediate the relationship between communication and outcomes. Conclusion Although many elements of the model have been studied in relation to patient-clinician communication, there is limited data about surrogate decision making. There is evidence of high surrogate distress associated with decision making that may be alleviated by communication–focused interventions. More research is needed to test the relationships proposed in the model. Practice Implications Good communication with surrogates may improve both the quality of medical decisions and outcomes for the patient and surrogate. PMID:21889865
Torke, Alexia M; Petronio, Sandra; Sachs, Greg A; Helft, Paul R; Purnell, Christianna
2012-04-01
To build a conceptual model of the role of communication in decision making, based on literature from medicine, communication studies and medical ethics. We proposed a model and described each construct in detail. We review what is known about interpersonal and patient-physician communication, described literature about surrogate-clinician communication, and discussed implications for our developing model. The communication literature proposes two major elements of interpersonal communication: information processing and relationship building. These elements are composed of constructs such as information disclosure and emotional support that are likely to be relevant to decision making. We propose these elements of communication impact decision making, which in turn affects outcomes for both patients and surrogates. Decision making quality may also mediate the relationship between communication and outcomes. Although many elements of the model have been studied in relation to patient-clinician communication, there is limited data about surrogate decision making. There is evidence of high surrogate distress associated with decision making that may be alleviated by communication-focused interventions. More research is needed to test the relationships proposed in the model. Good communication with surrogates may improve both the quality of medical decisions and outcomes for the patient and surrogate. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Malfuson, Jean-Valère; Etienne, Anne; Turlure, Pascal; de Revel, Thierry; Thomas, Xavier; Contentin, Nathalie; Terré, Christine; Rigaudeau, Sophie; Bordessoule, Dominique; Vey, Norbert; Gardin, Claude; Dombret, Hervé
2008-12-01
There is a need for standardization of treatment decisions in older patients with acute myeloid leukemia. The aim of the present study was to analyze the decisional value of poor risk factors in 416 elderly patients treated in the ALFA-9803 trial in order to derive a decisional index. Standard multivariate analysis was used to identify risk factors for overall survival. Risk factors were then considered as good decision tools if associated with a frequency >10% and a false positive rate <10% in predicting overall survival as poor as observed after low-dose cytarabine therapy (25% survival or less at 12 months). Among six independent risk factors (age, performance status, white blood cell count, hematopoietic cell transplantation comorbidity index, infection at baseline, and cytogenetics), cytogenetics was the only potent, independent decision tool. High hematopoietic cell transplantation comorbidity index scores or infections were found too rarely to guide further decisions. The three other factors (age, performance status, and white cell count) needed to be combined to provide a good specificity. The proposed decisional index, therefore, included high-risk cytogenetics and/or the presence of at least two of the following criteria: age > or =75 years, performance status > or =2, and white cell count > or =50 x 10(9)/L. This simple two-class decisional index, which was validated in an independent patient set, enabled us to discriminate 100 patients (24%) who had an estimated overall survival of only 19% at 12 months, with a good 9% false positive rate. We propose waiting for cytogenetic information before making treatment decisions in elderly patients with acute myeloid leukemia. Those patients with unfavorable cytogenetics, as well as patients with at least two of the following features, age > or =75 years, performance status > or =2, and white cell count > or =50 x 10(9)/L, should not be considered for standard intensive chemotherapy (ClinicalTrials.gov identifier: NCT00363025).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bereketli Zafeirakopoulos, Ilke, E-mail: ibereketli@gsu.edu.tr; Erol Genevois, Mujde, E-mail: merol@gsu.edu.tr
Life Cycle Assessment is a tool to assess, in a systematic way, the environmental aspects and its potential environmental impacts and resources used throughout a product's life cycle. It is widely accepted and considered as one of the most powerful tools to support decision-making processes used in ecodesign and sustainable production in order to learn about the most problematic parts and life cycle phases of a product and to have a projection for future improvements. However, since Life Cycle Assessment is a cost and time intensive method, companies do not intend to carry out a full version of it, exceptmore » for large corporate ones. Especially for small and medium sized enterprises, which do not have enough budget for and knowledge on sustainable production and ecodesign approaches, focusing only on the most important possible environmental aspect is unavoidable. In this direction, finding the right environmental aspect to work on is crucial for the companies. In this study, a multi-criteria decision-making methodology, Analytic Network Process is proposed to select the most relevant environmental aspect. The proposed methodology aims at providing a simplified environmental assessment to producers. It is applied for a hand blender, which is a member of the Electrical and Electronic Equipment family. The decision criteria for the environmental aspects and relations of dependence are defined. The evaluation is made by the Analytic Network Process in order to create a realistic approach to inter-dependencies among the criteria. The results are computed via the Super Decisions software. Finally, it is observed that the procedure is completed in less time, with less data, with less cost and in a less subjective way than conventional approaches. - Highlights: • We present a simplified environmental assessment methodology to support LCA. • ANP is proposed to select the most relevant environmental aspect. • ANP deals well with the interdependencies between aspects and impacts. • The methodology is less subjective, less complicated, and less time–money consuming. • The proposed methodology is suitable for use by SMEs.« less
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.
Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.
48 CFR 873.116 - Source selection decision.
Code of Federal Regulations, 2014 CFR
2014-10-01
... Source selection decision. (a) An integrated comparative assessment of proposals should be performed... source selection team, or advisory boards or panels, may conduct comparative analysis(es) of proposals...
48 CFR 873.116 - Source selection decision.
Code of Federal Regulations, 2013 CFR
2013-10-01
... Source selection decision. (a) An integrated comparative assessment of proposals should be performed... source selection team, or advisory boards or panels, may conduct comparative analysis(es) of proposals...
48 CFR 873.116 - Source selection decision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... Source selection decision. (a) An integrated comparative assessment of proposals should be performed... source selection team, or advisory boards or panels, may conduct comparative analysis(es) of proposals...
48 CFR 873.116 - Source selection decision.
Code of Federal Regulations, 2012 CFR
2012-10-01
... Source selection decision. (a) An integrated comparative assessment of proposals should be performed... source selection team, or advisory boards or panels, may conduct comparative analysis(es) of proposals...
48 CFR 873.116 - Source selection decision.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Source selection decision. (a) An integrated comparative assessment of proposals should be performed... source selection team, or advisory boards or panels, may conduct comparative analysis(es) of proposals...
[Refusal of care in the intensive care: how makes decision?].
Borel, M; Veber, B; Villette-Baron, K; Hariri, S; Dureuil, B; Hervé, C
2009-11-01
Decision-making bringing to an admission or not in intensive care is complex. The aim of this study is to analyze with an ethical point of view the making decision process leading to the refusal and its consequences. It is proposed a setting in prospect through the principles of beneficence, non-maleficience, respect for autonomy, justice, and the Leonetti law. Prospective study in surgical reanimation at the University Hospital of Rouen over 9 months (November 2007-September 2008). Systematic collection for each non-admitted patient of the general characters, the methods of decision making, immediate becoming and within 48 h Constitution of two groups: patients for whom an admission in intensive care could be an unreasonable situation of obstinacy, and patients for whom an admission in reanimation would not be about unreasonable if it occurred. One hundred and fifty situations were analyzed. The potentially unreasonable character of an admission does not involve necessarily a refusal of care in intensive care. The question of the lack of place and equity in the access to the care is real but relative according to the typology of the patients. The research of the respect of the autonomy of the patient is difficult but could be facilitated. The Leonetti law does not appear to be able to be a framework with the situation of refusal of care in intensive care. It is not a question of going towards a systematic admission in intensive care of any patient proposed, but to make sure that so if there is a refusal, it is carried out according to a step ethically acceptable.
NASA Astrophysics Data System (ADS)
Montefrio, M. F.
2012-12-01
Burgeoning attention in biofuels and natural rubber has spurred interest among governments and private companies in integrating marginalized communities into global commodity markets. Upland farmers from diverse cultural backgrounds and biophysical settings today are deciding whether to agree with partnership proposals from governments and private firms to grow biofuels and natural rubber. In this paper, I examine whether upland farmers' socio-environmental constructions (evaluative beliefs, place satisfaction, and ecological worldviews) and the actual biophysical attributes (land cover and soil types) of upland environments, respectively, function as significant predictors of the intent and decisions of indigenous and non-indigenous farmers to cooperate with government and private actors to establish certain biofuel crops and natural rubber production systems in Palawan, Philippines. Drawing from ethnography and statistical analysis of household surveys, I propose that social constructions and the biophysical attributes of the environment are closely related with each other and in turn both influence individual decision-making behavior in resource-based production partnership regimes. This has significant implications on the resilience of socio-ecological systems, particularly agro-ecosystems, as certain upland farmers prefer to engage in intensive, monocrop production of biofuels and natural rubber on relatively more biodiverse areas, such as secondary forests and traditional shifting cultivation lands. The study aims to advance new institutional theories of resource management, particularly Ostrom's Institutional Analysis and Development and Socio-Ecological Systems frameworks, and scholarship on environmental decision-making in the context of collective action.
Zadeh, Rana; Sadatsafavi, Hessam; Xue, Ryan
2015-01-01
This study describes a vision and framework that can facilitate the implementation of evidence-based design (EBD), scientific knowledge base into the process of the design, construction, and operation of healthcare facilities and clarify the related safety and quality outcomes for the stakeholders. The proposed framework pairs EBD with value-driven decision making and aims to improve communication among stakeholders by providing a common analytical language. Recent EBD research indicates that the design and operation of healthcare facilities contribute to an organization's operational success by improving safety, quality, and efficiency. However, because little information is available about the financial returns of evidence-based investments, such investments are readily eliminated during the capital-investment decision-making process. To model the proposed framework, we used engineering economy tools to evaluate the return on investments in six successful cases, identified by a literature review, in which facility design and operation interventions resulted in reductions in hospital-acquired infections, patient falls, staff injuries, and patient anxiety. In the evidence-based cases, calculated net present values, internal rates of return, and payback periods indicated that the long-term benefits of interventions substantially outweighed the intervention costs. This article explained a framework to develop a research-based and value-based communication language on specific interventions along the planning, design and construction, operation, and evaluation stages. Evidence-based and value-based design frameworks can be applied to communicate the life-cycle costs and savings of EBD interventions to stakeholders, thereby contributing to more informed decision makings and the optimization of healthcare infrastructures. © The Author(s) 2015.
Harris, Claire; Garrubba, Marie; Melder, Angela; Voutier, Catherine; Waller, Cara; King, Richard; Ramsey, Wayne
2018-03-02
This is the eighth in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was a systematic, integrated, evidence-based program for disinvestment within a large Australian health service. One of the aims was to explore methods to deliver existing high quality synthesised evidence directly to decision-makers to drive decision-making proactively. An Evidence Dissemination Service (EDS) was proposed. While this was conceived as a method to identify disinvestment opportunities, it became clear that it could also be a way to review all practices for consistency with current evidence. This paper reports the development, implementation and evaluation of two models of an in-house EDS. Frameworks for development of complex interventions, implementation of evidence-based change, and evaluation and explication of processes and outcomes were adapted and/or applied. Mixed methods including a literature review, surveys, interviews, workshops, audits, document analysis and action research were used to capture barriers, enablers and local needs; identify effective strategies; develop and refine proposals; ascertain feedback and measure outcomes. Methods to identify, capture, classify, store, repackage, disseminate and facilitate use of synthesised research evidence were investigated. In Model 1, emails containing links to multiple publications were sent to all self-selected participants who were asked to determine whether they were the relevant decision-maker for any of the topics presented, whether change was required, and to take the relevant action. This voluntary framework did not achieve the aim of ensuring practice was consistent with current evidence. In Model 2, the need for change was established prior to dissemination, then a summary of the evidence was sent to the decision-maker responsible for practice in the relevant area who was required to take appropriate action and report the outcome. This mandatory governance framework was successful. The factors influencing decisions, processes and outcomes were identified. An in-house EDS holds promise as a method of identifying disinvestment opportunities and/or reviewing local practice for consistency with current evidence. The resource-intensive nature of delivery of the EDS is a potential barrier. The findings from this study will inform further exploration.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-12
.../Record of Decision (FONSI/ROD) for the Supplemental Environmental Assessment (EA) for changes proposed to... previously addressed in the December 2007 environmental assessment FONSI/ROD. The proposed changes include... Supplemental Finding of No Significant Impact and Record of Decision for the Supplemental Environmental...
Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospitals
Alam, Md Golam Rabiul; Masum, Abdul Kadar Muhammad; Beh, Loo-See; Hong, Choong Seon
2016-01-01
The aim of this research is to explore factors influencing the management decisions to adopt human resource information system (HRIS) in the hospital industry of Bangladesh—an emerging developing country. To understand this issue, this paper integrates two prominent adoption theories—Human-Organization-Technology fit (HOT-fit) model and Technology-Organization-Environment (TOE) framework. Thirteen factors under four dimensions were investigated to explore their influence on HRIS adoption decisions in hospitals. Employing non-probability sampling method, a total of 550 copies of structured questionnaires were distributed among HR executives of 92 private hospitals in Bangladesh. Among the respondents, usable questionnaires were 383 that suggesting a valid response rate of 69.63%. We classify the sample into 3 core groups based on the HRIS initial implementation, namely adopters, prospectors, and laggards. The obtained results specify 5 most critical factors i.e. IT infrastructure, top management support, IT capabilities of staff, perceived cost, and competitive pressure. Moreover, the most significant dimension is technological dimension followed by organisational, human, and environmental among the proposed 4 dimensions. Lastly, the study found existence of significant differences in all factors across different adopting groups. The study results also expose constructive proposals to researchers, hospitals, and the government to enhance the likelihood of adopting HRIS. The present study has important implications in understanding HRIS implementation in developing countries. PMID:27494334
NASA Astrophysics Data System (ADS)
Kun, Mete; Topaloǧlu, Şeyda; Malli, Tahir
2013-03-01
The marble mining in Turkey has been rising since the early 80's. In relation to that, the marble income has become noticeably bigger than those of other mining sectors. In recent years, marble and natural stone export composes half of the total mine export with a value of two billion dollars. This rapid development observed in marble operation has increased the importance of mining economics, income-expenditure balance and cost analysis. The most important cost elements observed in marble quarrying are machinery and equipment, labor costs and geological structures of the field. The aim of this study is to is to propose a multi-criteria decision making (MCDM) approach to evaluate the wheel loader alternatives and select the best loader under multiple criteria. A two-step methodology based on two MCDM methods, which are namely the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), are used in the evaluation procedure. More precisely, AHP is applied to determine the relative weights of evaluation criteria and TOPSIS is applied to rank the wheel loader alternatives. The proposed approach also provides a relatively simple and very well suited decision making tool for this type of decision making problems.
Alam, Md Golam Rabiul; Masum, Abdul Kadar Muhammad; Beh, Loo-See; Hong, Choong Seon
2016-01-01
The aim of this research is to explore factors influencing the management decisions to adopt human resource information system (HRIS) in the hospital industry of Bangladesh-an emerging developing country. To understand this issue, this paper integrates two prominent adoption theories-Human-Organization-Technology fit (HOT-fit) model and Technology-Organization-Environment (TOE) framework. Thirteen factors under four dimensions were investigated to explore their influence on HRIS adoption decisions in hospitals. Employing non-probability sampling method, a total of 550 copies of structured questionnaires were distributed among HR executives of 92 private hospitals in Bangladesh. Among the respondents, usable questionnaires were 383 that suggesting a valid response rate of 69.63%. We classify the sample into 3 core groups based on the HRIS initial implementation, namely adopters, prospectors, and laggards. The obtained results specify 5 most critical factors i.e. IT infrastructure, top management support, IT capabilities of staff, perceived cost, and competitive pressure. Moreover, the most significant dimension is technological dimension followed by organisational, human, and environmental among the proposed 4 dimensions. Lastly, the study found existence of significant differences in all factors across different adopting groups. The study results also expose constructive proposals to researchers, hospitals, and the government to enhance the likelihood of adopting HRIS. The present study has important implications in understanding HRIS implementation in developing countries.
Improved Frame Mode Selection for AMR-WB+ Based on Decision Tree
NASA Astrophysics Data System (ADS)
Kim, Jong Kyu; Kim, Nam Soo
In this letter, we propose a coding mode selection method for the AMR-WB+ audio coder based on a decision tree. In order to reduce computation while maintaining good performance, decision tree classifier is adopted with the closed loop mode selection results as the target classification labels. The size of the decision tree is controlled by pruning, so the proposed method does not increase the memory requirement significantly. Through an evaluation test on a database covering both speech and music materials, the proposed method is found to achieve a much better mode selection accuracy compared with the open loop mode selection module in the AMR-WB+.
Expectation Violation in Political Decision Making: A Psychological Case Study.
Öllinger, Michael; Meissner, Karin; von Müller, Albrecht; Collado Seidel, Carlos
2017-01-01
Since the early Gestaltists there has been a strong interest in the question of how problem solvers get stuck in a mental impasse. A key idea is that the repeated activation of a successful strategy from the past results in a mental set ('Einstellung') which determines and constrains the option space to solve a problem. We propose that this phenomenon, which mostly was tested by fairly restricted experiments in the lab, could also be applied to more complex problem constellations and naturalistic decision making. We aim at scrutinizing and reconstructing how a mental set determines the misinterpretation of facts in the field of political decision making and leads in consequence to wrong expectations and an ill-defined problem representation. We will exemplify this psychological mechanism considering a historical example, namely the unexpected stabilization of the Franco regime at the end of World War II and its survival thereafter. A specific focus will be drawn to the significant observation that erroneous expectations were taken as the basis for decisions. This is congruent with the notion that in case of discrepancy between preconceived notions and new information, the former prevails over the new findings. Based on these findings, we suggest a theoretical model for expectation violation in political decision making and develop novel approaches for cognitive empirical research on the mechanisms of expectation violation and its maintenance in political decision making processes.
Expectation Violation in Political Decision Making: A Psychological Case Study
Öllinger, Michael; Meissner, Karin; von Müller, Albrecht; Collado Seidel, Carlos
2017-01-01
Since the early Gestaltists there has been a strong interest in the question of how problem solvers get stuck in a mental impasse. A key idea is that the repeated activation of a successful strategy from the past results in a mental set (‘Einstellung’) which determines and constrains the option space to solve a problem. We propose that this phenomenon, which mostly was tested by fairly restricted experiments in the lab, could also be applied to more complex problem constellations and naturalistic decision making. We aim at scrutinizing and reconstructing how a mental set determines the misinterpretation of facts in the field of political decision making and leads in consequence to wrong expectations and an ill-defined problem representation. We will exemplify this psychological mechanism considering a historical example, namely the unexpected stabilization of the Franco regime at the end of World War II and its survival thereafter. A specific focus will be drawn to the significant observation that erroneous expectations were taken as the basis for decisions. This is congruent with the notion that in case of discrepancy between preconceived notions and new information, the former prevails over the new findings. Based on these findings, we suggest a theoretical model for expectation violation in political decision making and develop novel approaches for cognitive empirical research on the mechanisms of expectation violation and its maintenance in political decision making processes. PMID:29085316
Extracting decision rules from police accident reports through decision trees.
de Oña, Juan; López, Griselda; Abellán, Joaquín
2013-01-01
Given the current number of road accidents, the aim of many road safety analysts is to identify the main factors that contribute to crash severity. To pinpoint those factors, this paper shows an application that applies some of the methods most commonly used to build decision trees (DTs), which have not been applied to the road safety field before. An analysis of accidents on rural highways in the province of Granada (Spain) between 2003 and 2009 (both inclusive) showed that the methods used to build DTs serve our purpose and may even be complementary. Applying these methods has enabled potentially useful decision rules to be extracted that could be used by road safety analysts. For instance, some of the rules may indicate that women, contrary to men, increase their risk of severity under bad lighting conditions. The rules could be used in road safety campaigns to mitigate specific problems. This would enable managers to implement priority actions based on a classification of accidents by types (depending on their severity). However, the primary importance of this proposal is that other databases not used here (i.e. other infrastructure, roads and countries) could be used to identify unconventional problems in a manner easy for road safety managers to understand, as decision rules. Copyright © 2012 Elsevier Ltd. All rights reserved.
The influence of number line estimation precision and numeracy on risky financial decision making.
Park, Inkyung; Cho, Soohyun
2018-01-10
This study examined whether different aspects of mathematical proficiency influence one's ability to make adaptive financial decisions. "Numeracy" refers to the ability to process numerical and probabilistic information and is commonly reported as an important factor which contributes to financial decision-making ability. The precision of mental number representation (MNR), measured with the number line estimation (NLE) task has been reported to be another critical factor. This study aimed to examine the contribution of these mathematical proficiencies while controlling for the influence of fluid intelligence, math anxiety and personality factors. In our decision-making task, participants chose between two options offering probabilistic monetary gain or loss. Sensitivity to expected value was measured as an index for the ability to discriminate between optimal versus suboptimal options. Partial correlation and hierarchical regression analyses revealed that NLE precision better explained EV sensitivity compared to numeracy, after controlling for all covariates. These results suggest that individuals with more precise MNR are capable of making more rational financial decisions. We also propose that the measurement of "numeracy," which is commonly used interchangeably with general mathematical proficiency, should include more diverse aspects of mathematical cognition including basic understanding of number magnitude. © 2018 International Union of Psychological Science.
Peinemann, Frank; Kleijnen, Jos
2015-01-01
Objectives To develop an algorithm that aims to provide guidance and awareness for choosing multiple study designs in systematic reviews of healthcare interventions. Design Method study: (1) To summarise the literature base on the topic. (2) To apply the integration of various study types in systematic reviews. (3) To devise decision points and outline a pragmatic decision tree. (4) To check the plausibility of the algorithm by backtracking its pathways in four systematic reviews. Results (1) The results of our systematic review of the published literature have already been published. (2) We recaptured the experience from our four previously conducted systematic reviews that required the integration of various study types. (3) We chose length of follow-up (long, short), frequency of events (rare, frequent) and types of outcome as decision points (death, disease, discomfort, disability, dissatisfaction) and aligned the study design labels according to the Cochrane Handbook. We also considered practical or ethical concerns, and the problem of unavailable high-quality evidence. While applying the algorithm, disease-specific circumstances and aims of interventions should be considered. (4) We confirmed the plausibility of the pathways of the algorithm. Conclusions We propose that the algorithm can assist to bring seminal features of a systematic review with multiple study designs to the attention of anyone who is planning to conduct a systematic review. It aims to increase awareness and we think that it may reduce the time burden on review authors and may contribute to the production of a higher quality review. PMID:26289450
He, Xin; Frey, Eric C
2006-08-01
Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the "general" three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems.
Harris, Claire; Garrubba, Marie; Allen, Kelly; King, Richard; Kelly, Cate; Thiagarajan, Malar; Castleman, Beverley; Ramsey, Wayne; Farjou, Dina
2015-12-28
This paper reports the process of establishing a transparent, accountable, evidence-based program for introduction of new technologies and clinical practices (TCPs) in a large Australian healthcare network. Many countries have robust evidence-based processes for assessment of new TCPs at national level. However many decisions are made by local health services where the resources and expertise to undertake health technology assessment (HTA) are limited and a lack of structure, process and transparency has been reported. An evidence-based model for process change was used to establish the program. Evidence from research and local data, experience of health service staff and consumer perspectives were incorporated at each of four steps: identifying the need for change, developing a proposal, implementation and evaluation. Checklists assessing characteristics of success, factors for sustainability and barriers and enablers were applied and implementation strategies were based on these findings. Quantitative and qualitative methods were used for process and outcome evaluation. An action research approach underpinned ongoing refinement to systems, processes and resources. A Best Practice Guide developed from the literature and stakeholder consultation identified seven program components: Governance, Decision-Making, Application Process, Monitoring and Reporting, Resources, Administration, and Evaluation and Quality Improvement. The aims of transparency and accountability were achieved. The processes are explicit, decisions published, outcomes recorded and activities reported. The aim of ascertaining rigorous evidence-based information for decision-making was not achieved in all cases. Applicants proposing new TCPs provided the evidence from research literature and local data however the information was often incorrect or inadequate, overestimating benefits and underestimating costs. Due to these limitations the initial application process was replaced by an Expression of Interest from applicants followed by a rigorous HTA by independent in-house experts. The program is generalisable to most health care organisations. With one exception, the components would be achievable with minimal additional resources; the lack of skills and resources required for HTA will limit effective application in many settings. A toolkit containing details of the processes and sample materials is provided to facilitate replication or local adaptation by those wishing to establish a similar program.
FPGA implementation of concatenated non-binary QC-LDPC codes for high-speed optical transport.
Zou, Ding; Djordjevic, Ivan B
2015-06-01
In this paper, we propose a soft-decision-based FEC scheme that is the concatenation of a non-binary LDPC code and hard-decision FEC code. The proposed NB-LDPC + RS with overhead of 27.06% provides a superior NCG of 11.9dB at a post-FEC BER of 10-15. As a result, the proposed NB-LDPC codes represent the strong FEC candidate of soft-decision FEC for beyond 100Gb/s optical transmission systems.
Closed loop supply chain network design with fuzzy tactical decisions
NASA Astrophysics Data System (ADS)
Sherafati, Mahtab; Bashiri, Mahdi
2016-09-01
One of the most strategic and the most significant decisions in supply chain management is reconfiguration of the structure and design of the supply chain network. In this paper, a closed loop supply chain network design model is presented to select the best tactical and strategic decision levels simultaneously considering the appropriate transportation mode in activated links. The strategic decisions are made for a long term; thus, it is more satisfactory and more appropriate when the decision variables are considered uncertain and fuzzy, because it is more flexible and near to the real world. This paper is the first research which considers fuzzy decision variables in the supply chain network design model. Moreover, in this study a new fuzzy optimization approach is proposed to solve a supply chain network design problem with fuzzy tactical decision variables. Finally, the proposed approach and model are verified using several numerical examples. The comparison of the results with other existing approaches confirms efficiency of the proposed approach. Moreover the results confirms that by considering the vagueness of tactical decisions some properties of the supply chain network will be improved.
A spiral model of musical decision-making.
Bangert, Daniel; Schubert, Emery; Fabian, Dorottya
2014-01-01
This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1) and deliberate (Type 2) decision-making processes changes with increasing expertise and conceptualizes this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning toward greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural), increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion toward the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans' (2011) Intervention Model of dual-process theories, Cognitive Continuum Theory Hammond et al. (1987), Hammond (2007), Baylor's (2001) U-shaped model for the development of intuition by level of expertise. By theorizing how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally.
A spiral model of musical decision-making
Bangert, Daniel; Schubert, Emery; Fabian, Dorottya
2014-01-01
This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1) and deliberate (Type 2) decision-making processes changes with increasing expertise and conceptualizes this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning toward greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural), increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion toward the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans’ (2011) Intervention Model of dual-process theories, Cognitive Continuum Theory Hammond et al. (1987), Hammond (2007), Baylor’s (2001) U-shaped model for the development of intuition by level of expertise. By theorizing how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally. PMID:24795673
Evaluation of a rule base for decision making in general practice.
Essex, B; Healy, M
1994-01-01
BACKGROUND. Decision making in general practice relies heavily on judgmental expertise. It should be possible to codify this expertise into rules and principles. AIM. A study was undertaken to evaluate the effectiveness, of rules from a rule base designed to improve students' and trainees' management decisions relating to patients seen in general practice. METHOD. The rule base was developed after studying decisions about and management of thousands of patients seen in one general practice over an eight year period. Vignettes were presented to 93 fourth year medical students and 179 general practitioner trainees. They recorded their perception and management of each case before and after being presented with a selection of relevant rules. Participants also commented on their level of agreement with each of the rules provided with the vignettes. A panel of five independent assessors then rated as good, acceptable or poor, the participants' perception and management of each case before and after seeing the rules. RESULTS. Exposure to a few selected rules of thumb improved the problem perception and management decisions of both undergraduates and trainees. The degree of improvement was not related to previous experience or to the stated level of agreement with the proposed rules. The assessors identified difficulties students and trainees experienced in changing their perceptions and management decisions when the rules suggested options they had not considered. CONCLUSION. The rules developed to improve decision making skills in general practice are effective when used with vignettes. The next phase is to transform the rule base into an expert system to train students and doctors to acquire decision making skills. It could also be used to provide decision support when confronted with difficult management decisions in general practice. PMID:8204334
12 CFR 622.12 - Proposed findings and conclusions; recommended decision.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Proposed findings and conclusions; recommended decision. 622.12 Section 622.12 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM RULES OF PRACTICE AND PROCEDURE Rules Applicable to Formal Hearings § 622.12 Proposed findings and conclusions...
Visual saliency-based fast intracoding algorithm for high efficiency video coding
NASA Astrophysics Data System (ADS)
Zhou, Xin; Shi, Guangming; Zhou, Wei; Duan, Zhemin
2017-01-01
Intraprediction has been significantly improved in high efficiency video coding over H.264/AVC with quad-tree-based coding unit (CU) structure from size 64×64 to 8×8 and more prediction modes. However, these techniques cause a dramatic increase in computational complexity. An intracoding algorithm is proposed that consists of perceptual fast CU size decision algorithm and fast intraprediction mode decision algorithm. First, based on the visual saliency detection, an adaptive and fast CU size decision method is proposed to alleviate intraencoding complexity. Furthermore, a fast intraprediction mode decision algorithm with step halving rough mode decision method and early modes pruning algorithm is presented to selectively check the potential modes and effectively reduce the complexity of computation. Experimental results show that our proposed fast method reduces the computational complexity of the current HM to about 57% in encoding time with only 0.37% increases in BD rate. Meanwhile, the proposed fast algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.
Coping with complexity, uncertainty and ambiguity in risk governance: a synthesis.
Renn, Ortwin; Klinke, Andreas; van Asselt, Marjolein
2011-03-01
The term governance describes the multitude of actors and processes that lead to collectively binding decisions. The term risk governance translates the core principles of governance to the context of risk-related policy making. We aim to delineate some basic lessons from the insights of the other articles in this special issue for our understanding of risk governance. Risk governance provides a conceptual as well as normative basis for how to cope with uncertain, complex and/or ambiguous risks. We propose to synthesize the breadth of the articles in this special issue by suggesting some changes to the risk governance framework proposed by the International Risk Governance Council (IRGC) and adding some insights to its analytical and normative implications.
77 FR 26316 - Sunshine Act Meeting
Federal Register 2010, 2011, 2012, 2013, 2014
2012-05-03
... Proposed Decisions in claims against Libya. Thursday, May 17, 2012: 9:00 a.m.--Issuance of Proposed Decisions in claims against Libya. Status: Open. All meetings are held at the Foreign Claims Settlement...
Nearest unlike neighbor (NUN): an aid to decision confidence estimation
NASA Astrophysics Data System (ADS)
Dasarathy, Belur V.
1995-09-01
The concept of nearest unlike neighbor (NUN), proposed and explored previously in the design of nearest neighbor (NN) based decision systems, is further exploited in this study to develop a measure of confidence in the decisions made by NN-based decision systems. This measure of confidence, on the basis of comparison with a user-defined threshold, may be used to determine the acceptability of the decision provided by the NN-based decision system. The concepts, associated methodology, and some illustrative numerical examples using the now classical Iris data to bring out the ease of implementation and effectiveness of the proposed innovations are presented.
Chen, Innie; Money, Deborah; Yong, Paul; Williams, Christina; Allaire, Catherine
2015-09-01
Chronic pelvic pain (CPP) is a prevalent, debilitating, and costly condition. Although national guidelines and empiric evidence support the use of a multidisciplinary model of care for such patients, such clinics are uncommon in Canada. The BC Women's Centre for Pelvic Pain and Endometriosis was created to respond to this need, and there is interest in this model of care's impact on the burden of disease in British Columbia. We sought to create an approach to its evaluation using the RE-AIM (Reach, Efficacy, Adoption, Implementation, Maintenance) evaluation framework to assess the impact of the care model and to guide clinical decision-making and policy. The RE-AIM evaluation framework was applied to consider the different dimensions of impact of the BC Centre. The proposed measures, data sources, and data management strategies for this mixed-methods approach were identified. The five dimensions of impact were considered at individual and organizational levels, and corresponding indicators were proposed to enable integration into existing data infrastructure to facilitate collection and early program evaluation. The RE-AIM framework can be applied to the evaluation of a multidisciplinary chronic pelvic pain clinic. This will allow better assessment of the impact of innovative models of care for women with chronic pelvic pain.
TargetCrys: protein crystallization prediction by fusing multi-view features with two-layered SVM.
Hu, Jun; Han, Ke; Li, Yang; Yang, Jing-Yu; Shen, Hong-Bin; Yu, Dong-Jun
2016-11-01
The accurate prediction of whether a protein will crystallize plays a crucial role in improving the success rate of protein crystallization projects. A common critical problem in the development of machine-learning-based protein crystallization predictors is how to effectively utilize protein features extracted from different views. In this study, we aimed to improve the efficiency of fusing multi-view protein features by proposing a new two-layered SVM (2L-SVM) which switches the feature-level fusion problem to a decision-level fusion problem: the SVMs in the 1st layer of the 2L-SVM are trained on each of the multi-view feature sets; then, the outputs of the 1st layer SVMs, which are the "intermediate" decisions made based on the respective feature sets, are further ensembled by a 2nd layer SVM. Based on the proposed 2L-SVM, we implemented a sequence-based protein crystallization predictor called TargetCrys. Experimental results on several benchmark datasets demonstrated the efficacy of the proposed 2L-SVM for fusing multi-view features. We also compared TargetCrys with existing sequence-based protein crystallization predictors and demonstrated that the proposed TargetCrys outperformed most of the existing predictors and is competitive with the state-of-the-art predictors. The TargetCrys webserver and datasets used in this study are freely available for academic use at: http://csbio.njust.edu.cn/bioinf/TargetCrys .
Development by Design in Colombia: Making Mitigation Decisions Consistent with Conservation Outcomes
Saenz, Shirley; Walschburger, Tomas; González, Juan Carlos; León, Jorge; McKenney, Bruce; Kiesecker, Joseph
2013-01-01
Mitigation policy and regulatory frameworks are consistent in their strong support for the mitigation hierarchy of: (1) avoiding impacts, (2) minimizing impacts, and then (3) offsetting/compensating for residual impacts. While mitigation frameworks require developers to avoid, minimize and restore biodiversity on-site before considering an offset for residual impacts, there is a lack of quantitative guidance for this decision-making process. What are the criteria for requiring impacts be avoided altogether? Here we examine how conservation planning can guide the application of the mitigation hierarchy to address this issue. In support of the Colombian government's aim to improve siting and mitigation practices for planned development, we examined five pilot projects in landscapes expected to experience significant increases in mining, petroleum and/or infrastructure development. By blending landscape-level conservation planning with application of the mitigation hierarchy, we can proactively identify where proposed development and conservation priorities would be in conflict and where impacts should be avoided. The approach we outline here has been adopted by the Colombian Ministry of Environment and Sustainable Development to guide licensing decisions, avoid piecemeal licensing, and promote mitigation decisions that maintain landscape condition. PMID:24339972
Saenz, Shirley; Walschburger, Tomas; González, Juan Carlos; León, Jorge; McKenney, Bruce; Kiesecker, Joseph
2013-01-01
Mitigation policy and regulatory frameworks are consistent in their strong support for the mitigation hierarchy of: (1) avoiding impacts, (2) minimizing impacts, and then (3) offsetting/compensating for residual impacts. While mitigation frameworks require developers to avoid, minimize and restore biodiversity on-site before considering an offset for residual impacts, there is a lack of quantitative guidance for this decision-making process. What are the criteria for requiring impacts be avoided altogether? Here we examine how conservation planning can guide the application of the mitigation hierarchy to address this issue. In support of the Colombian government's aim to improve siting and mitigation practices for planned development, we examined five pilot projects in landscapes expected to experience significant increases in mining, petroleum and/or infrastructure development. By blending landscape-level conservation planning with application of the mitigation hierarchy, we can proactively identify where proposed development and conservation priorities would be in conflict and where impacts should be avoided. The approach we outline here has been adopted by the Colombian Ministry of Environment and Sustainable Development to guide licensing decisions, avoid piecemeal licensing, and promote mitigation decisions that maintain landscape condition.
Grassi, Giacomo; Figee, Martijn; Ooms, Pieter; Righi, Lorenzo; Nakamae, Takashi; Pallanti, Stefano; Schuurman, Rick; Denys, Damiaan
2018-06-04
Impulsivity and impaired decision-making have been proposed as obsessive-compulsive disorder (OCD) endophenotypes, running in OCD and their healthy relatives independently of symptom severity and medication status. Deep brain stimulation (DBS) targeting the ventral limb of the internal capsule (vALIC) and the nucleus accumbens (Nacc) is an effective treatment strategy for treatment-refractory OCD. The effectiveness of vALIC-DBS for OCD has been linked to its effects on a frontostriatal network that is also implicated in reward, impulse control, and decision-making. While vALIC-DBS has been shown to restore reward dysfunction in OCD patients, little is known about the effects of vALIC-DBS on impulsivity and decision-making. The aim of the study was to compare cognitive impulsivity and decision-making between OCD patients undergoing effective vALIC-DBS or treatment as usual (TAU), and healthy controls. We used decision-making performances under ambiguity on the Iowa Gambling Task and reflection impulsivity on the Beads Task to compare 20 OCD patients effectively treated with vALIC-DBS, 40 matched OCD patients undergoing effective TAU (medication and/or cognitive behavioural therapy), and 40 healthy subjects. Effective treatment was defined as at least 35% improvement of OCD symptoms. OCD patients, irrespective of treatment modality (DBS or TAU), showed increased reflection impulsivity and impaired decision-making compared to healthy controls. No differences were observed between OCD patients treated with DBS or TAU. OCD patients effectively treated with vALIC-DBS or TAU display increased reflection impulsivity and impaired decision-making independent of the type of treatment.
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694
23 CFR 636.512 - What is the basis for the source selection decision?
Code of Federal Regulations, 2013 CFR
2013-04-01
... AND TRAFFIC OPERATIONS DESIGN-BUILD CONTRACTING Discussions, Proposal Revisions and Source Selection... decision on a comparative assessment of proposals against all selection criteria in the solicitation. While...
23 CFR 636.512 - What is the basis for the source selection decision?
Code of Federal Regulations, 2011 CFR
2011-04-01
... AND TRAFFIC OPERATIONS DESIGN-BUILD CONTRACTING Discussions, Proposal Revisions and Source Selection... decision on a comparative assessment of proposals against all selection criteria in the solicitation. While...
23 CFR 636.512 - What is the basis for the source selection decision?
Code of Federal Regulations, 2014 CFR
2014-04-01
... AND TRAFFIC OPERATIONS DESIGN-BUILD CONTRACTING Discussions, Proposal Revisions and Source Selection... decision on a comparative assessment of proposals against all selection criteria in the solicitation. While...
23 CFR 636.512 - What is the basis for the source selection decision?
Code of Federal Regulations, 2010 CFR
2010-04-01
... AND TRAFFIC OPERATIONS DESIGN-BUILD CONTRACTING Discussions, Proposal Revisions and Source Selection... decision on a comparative assessment of proposals against all selection criteria in the solicitation. While...
23 CFR 636.512 - What is the basis for the source selection decision?
Code of Federal Regulations, 2012 CFR
2012-04-01
... AND TRAFFIC OPERATIONS DESIGN-BUILD CONTRACTING Discussions, Proposal Revisions and Source Selection... decision on a comparative assessment of proposals against all selection criteria in the solicitation. While...
Azadmanjir, Zahra; Safdari, Reza; Ghazisaeedi, Marjan; Mokhtaran, Mehrshad; Kameli, Mohammad Esmail
2017-06-01
Accurate coded data in the healthcare are critical. Computer-Assisted Coding (CAC) is an effective tool to improve clinical coding in particular when a new classification will be developed and implemented. But determine the appropriate method for development need to consider the specifications of existing CAC systems, requirements for each type, our infrastructure and also, the classification scheme. The aim of the study was the development of a decision model for determining accurate code of each medical intervention in Iranian Classification of Health Interventions (IRCHI) that can be implemented as a suitable CAC system. first, a sample of existing CAC systems was reviewed. Then feasibility of each one of CAC types was examined with regard to their prerequisites for their implementation. The next step, proper model was proposed according to the structure of the classification scheme and was implemented as an interactive system. There is a significant relationship between the level of assistance of a CAC system and integration of it with electronic medical documents. Implementation of fully automated CAC systems is impossible due to immature development of electronic medical record and problems in using language for medical documenting. So, a model was proposed to develop semi-automated CAC system based on hierarchical relationships between entities in the classification scheme and also the logic of decision making to specify the characters of code step by step through a web-based interactive user interface for CAC. It was composed of three phases to select Target, Action and Means respectively for an intervention. The proposed model was suitable the current status of clinical documentation and coding in Iran and also, the structure of new classification scheme. Our results show it was practical. However, the model needs to be evaluated in the next stage of the research.
NASA Astrophysics Data System (ADS)
Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi
2017-07-01
The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.
Research on the use of data fusion technology to evaluate the state of electromechanical equipment
NASA Astrophysics Data System (ADS)
Lin, Lin
2018-04-01
Aiming at the problems of different testing information modes and the coexistence of quantitative and qualitative information in the state evaluation of electromechanical equipment, the paper proposes the use of data fusion technology to evaluate the state of electromechanical equipment. This paper introduces the state evaluation process of mechanical and electrical equipment in detail, uses the D-S evidence theory to fuse the decision-making layers of mechanical and electrical equipment state evaluation and carries out simulation tests. The simulation results show that it is feasible and effective to apply the data fusion technology to the state evaluation of the mechatronic equipment. After the multiple decision-making information provided by different evaluation methods are fused repeatedly and the useful information is extracted repeatedly, the fuzziness of judgment can be reduced and the state evaluation Credibility.
NASA Astrophysics Data System (ADS)
Loginov, E. L.; Raikov, A. N.
2015-04-01
The most large-scale accidents occurred as a consequence of network information attacks on the control systems of power facilities belonging to the United States' critical infrastructure are analyzed in the context of possibilities available in modern decision support systems. Trends in the development of technologies for inflicting damage to smart grids are formulated. A volume matrix of parameters characterizing attacks on facilities is constructed. A model describing the performance of a critical infrastructure's control system after an attack is developed. The recently adopted measures and legislation acts aimed at achieving more efficient protection of critical infrastructure are considered. Approaches to cognitive modeling and networked expertise of intricate situations for supporting the decision-making process, and to setting up a system of indicators for anticipatory monitoring of critical infrastructure are proposed.
A service oriented approach for guidelines-based clinical decision support using BPMN.
Rodriguez-Loya, Salvador; Aziz, Ayesha; Chatwin, Chris
2014-01-01
Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS).
USDA-ARS?s Scientific Manuscript database
A newly expanded digital resource exists for tracking decisions on all nomenclature proposals potentially contributing to Appendices II-VIII of the International Code of Nomenclature for algae, fungi, and plants. This resource originated with the Smithsonian Institution's Proposals and Disposals web...
12 CFR 508.12 - Proposed findings and conclusions and recommended decision.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Proposed findings and conclusions and recommended decision. 508.12 Section 508.12 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY REMOVALS, SUSPENSIONS, AND PROHIBITIONS WHERE A CRIME IS CHARGED OR PROVEN § 508.12 Proposed...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-03-04
... Part IV Department of Agriculture Agricultural Marketing Service 7 CFR Parts 1000, 1001, 1005, et al. Milk in the Northeast and Other Marketing Areas; Final Decision on Proposed Amendments to Tentative Marketing Agreements and Orders; Proposed Rule #0;#0;Federal Register / Vol. 75, No. 42 / Thursday...
Sun, Wei; Zhang, Xiaorui; Peeta, Srinivas; He, Xiaozheng; Li, Yongfu; Zhu, Senlai
2015-01-01
To improve the effectiveness and robustness of fatigue driving recognition, a self-adaptive dynamic recognition model is proposed that incorporates information from multiple sources and involves two sequential levels of fusion, constructed at the feature level and the decision level. Compared with existing models, the proposed model introduces a dynamic basic probability assignment (BPA) to the decision-level fusion such that the weight of each feature source can change dynamically with the real-time fatigue feature measurements. Further, the proposed model can combine the fatigue state at the previous time step in the decision-level fusion to improve the robustness of the fatigue driving recognition. An improved correction strategy of the BPA is also proposed to accommodate the decision conflict caused by external disturbances. Results from field experiments demonstrate that the effectiveness and robustness of the proposed model are better than those of models based on a single fatigue feature and/or single-source information fusion, especially when the most effective fatigue features are used in the proposed model. PMID:26393615
Dang, Yaoguo; Mao, Wenxin
2018-01-01
In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521
Sun, Huifang; Dang, Yaoguo; Mao, Wenxin
2018-03-03
In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.
A multimetric, map-aware routing protocol for VANETs in urban areas.
Tripp-Barba, Carolina; Urquiza-Aguiar, Luis; Aguilar Igartua, Mónica; Rebollo-Monedero, David; de la Cruz Llopis, Luis J; Mezher, Ahmad Mohamad; Aguilar-Calderón, José Alfonso
2014-01-28
In recent years, the general interest in routing for vehicular ad hoc networks (VANETs) has increased notably. Many proposals have been presented to improve the behavior of the routing decisions in these very changeable networks. In this paper, we propose a new routing protocol for VANETs that uses four different metrics. which are the distance to destination, the vehicles' density, the vehicles' trajectory and the available bandwidth, making use of the information retrieved by the sensors of the vehicle, in order to make forwarding decisions, minimizing packet losses and packet delay. Through simulation, we compare our proposal to other protocols, such as AODV (Ad hoc On-Demand Distance Vector), GPSR (Greedy Perimeter Stateless Routing), I-GPSR (Improvement GPSR) and to our previous proposal, GBSR-B (Greedy Buffer Stateless Routing Building-aware). Besides, we present a performance evaluation of the individual importance of each metric to make forwarding decisions. Experimental results show that our proposed forwarding decision outperforms existing solutions in terms of packet delivery.
Proposed RCRA Permit Decision for CNMI Remedial Action Plan
EPA requesting public comment on its proposed Remedial Action Plan permit decision for the detonation unit and storage cave located at Marpi Point, Saipan, approximately 1 mile north of the new Marpi Landfill.
Extending the Boundaries of Debate Theory: A Value-Bounded Policy Decision Making Paradigm.
ERIC Educational Resources Information Center
Thomas, David A.; Corsi, Jerome R.
The purpose of this paper is to propose a new, synthetic paradigm for debate analysis and decision making that features the policy systems approach within a context of values as boundaries for decision. As background for the proposed theory, the paper (1) summarizes the notions of paradigm formation and shifts initially presented by T. Kuhn; (2)…
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-17
...] Notice of Availability of Record of Decision for the Proposed Blackfoot Bridge Mine, Caribou County, ID... Bridge Mine. DATES: The ROD is now available. Implementation of this decision may begin at the close of...: Copies of the Blackfoot Bridge Mine ROD are available in the BLM Pocatello Field Office at the following...
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-28
... 13, 2011. EPA will post information regarding a hearing, if one is requested, on the Ozone Protection.... Proposed Critical Uses D. Proposed Critical Use Amounts E. The Criteria in Decisions IX/6 and Ex. I/4 F... issued several Decisions pertaining to the critical use exemption. These include Decisions IX/6 and Ex. I...
Staged decision making based on probabilistic forecasting
NASA Astrophysics Data System (ADS)
Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris
2016-04-01
Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in flood event management, the more damage can be reduced. And with decisions based on probabilistic forecasts, partial decisions can be made earlier in time (with a lower probability) and can be scaled up or down later in time when there is more certainty; whether the event takes place or not. Partial decisions are often more cheap, or shorten the final mitigation-time at the moment when there is more certainty. The proposed method is tested on Stonehaven, on the Carron River in Scotland. Decisions to implement demountable defences in the town are currently made based on a very short lead-time due to the absence of certainty. Application showed that staged decision making is possible and gives the decision maker more time to respond to a situation. The decision maker is able to take a lower regret decision with higher uncertainty and less related negative consequences. Although it is not possible to quantify intangible effects, it is part of the analysis to reduce these effects. Above all, the proposed approach has shown to be a possible improvement in economic terms and opens up possibilities of more flexible and robust decision making.
NASA Astrophysics Data System (ADS)
Budilova, E. V.; Terekhin, A. T.; Chepurnov, S. A.
1994-09-01
A hypothetical neural scheme is proposed that ensures efficient decision making by an animal searching for food in a maze. Only the general structure of the network is fixed; its quantitative characteristics are found by numerical optimization that simulates the process of natural selection. Selection is aimed at maximization of the expected number of descendants, which is directly related to the energy stored during the reproductive cycle. The main parameters to be optimized are the increments of the interneuronal links and the working-memory constants.
A two-phased fuzzy decision making procedure for IT supplier selection
NASA Astrophysics Data System (ADS)
Shohaimay, Fairuz; Ramli, Nazirah; Mohamed, Siti Rosiah; Mohd, Ainun Hafizah
2013-09-01
In many studies on fuzzy decision making, linguistic terms are usually represented by corresponding fixed triangular or trapezoidal fuzzy numbers. However, the fixed fuzzy numbers used in decision making process may not explain the actual respondents' opinions. Hence, a two-phased fuzzy decision making procedure is proposed. First, triangular fuzzy numbers were built based on respondents' opinions on the appropriate range (0-100) for each seven-scale linguistic terms. Then, the fuzzy numbers were integrated into fuzzy decision making model. The applicability of the proposed method is demonstrated in a case study of supplier selection in Information Technology (IT) department. The results produced via the developed fuzzy numbers were consistent with the results obtained using fixed fuzzy numbers. However, with different set of fuzzy numbers based on respondents, there is a difference in the ranking of suppliers based on criterion X1 (background of supplier). Hopefully the proposed model which incorporates fuzzy numbers based on respondents will provide a more significant meaning towards future decision making.
Assessing 15 proposals for promoting innovation and access to medicines globally.
Hoffman, Steven J; So, Karen
2014-01-01
There is widespread recognition that the existing global systems for innovation and access to medicines need reform. Billions of people do not have access to the medicines they need, and market failures prevent new drugs from being developed for diseases that primarily affect the global poor. The World Health Organization's Consultative Expert Working Group on Research and Development: Financing and Coordination (CEWG) analyzed numerous proposals for reform. The aim of this article is to build on these previous inquiries. We conducted a structured analysis that grouped proposals into five broad opportunities for global policy reform to help researchers and decision makers to meaningfully evaluate each proposal in comparison with similar proposals. Proposals were also analyzed along three important dimensions-potential health impact, financial implications, and political feasibility-further facilitating the comparison and application of this information. Upon analysis, no one solution was deemed a panacea, as many (often competing) considerations need to be taken into account. However, some proposals, particularly product development partnership and prizes, appeared more promising and feasible at this time and deserve further attention. More research is needed into the effectiveness of these mechanisms and their transferability across jurisdictions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Automatic wound infection interpretation for postoperative wound image
NASA Astrophysics Data System (ADS)
Hsu, Jui-Tse; Ho, Te-Wei; Shih, Hsueh-Fu; Chang, Chun-Che; Lai, Feipei; Wu, Jin-Ming
2017-02-01
With the growing demand for more efficient wound care after surgery, there is a necessity to develop a machine learning based image analysis approach to reduce the burden for health care professionals. The aim of this study was to propose a novel approach to recognize wound infection on the postsurgical site. Firstly, we proposed an optimal clustering method based on unimodal-rosin threshold algorithm to extract the feature points from a potential wound area into clusters for regions of interest (ROI). Each ROI was regarded as a suture site of the wound area. The automatic infection interpretation based on the support vector machine is available to assist physicians doing decision-making in clinical practice. According to clinical physicians' judgment criteria and the international guidelines for wound infection interpretation, we defined infection detector modules as the following: (1) Swelling Detector, (2) Blood Region Detector, (3) Infected Detector, and (4) Tissue Necrosis Detector. To validate the capability of the proposed system, a retrospective study using the confirmation wound pictures that were used for diagnosis by surgical physicians as the gold standard was conducted to verify the classification models. Currently, through cross validation of 42 wound images, our classifiers achieved 95.23% accuracy, 93.33% sensitivity, 100% specificity, and 100% positive predictive value. We believe this ability could help medical practitioners in decision making in clinical practice.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-02-07
... Vol. 78 Thursday, No. 26 February 7, 2013 Part IV Department of Agriculture Agricultural Marketing Service 7 CFR Part 1000 Milk in the Northeast and Other Marketing Areas; Final Decision on Proposed Amendments to Marketing Agreements and Orders and Termination of a Portion of the Proceeding; Proposed Rule...
MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging
NASA Astrophysics Data System (ADS)
Chen, Lei; Kamel, Mohamed S.
2016-01-01
In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.
NASA Astrophysics Data System (ADS)
Ahmadi, Mohammad H.; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah
2015-09-01
Developing new technologies like nano-technology improves the performance of the energy industries. Consequently, emerging new groups of thermal cycles in nano-scale can revolutionize the energy systems' future. This paper presents a thermo-dynamical study of a nano-scale irreversible Stirling engine cycle with the aim of optimizing the performance of the Stirling engine cycle. In the Stirling engine cycle the working fluid is an Ideal Maxwell-Boltzmann gas. Moreover, two different strategies are proposed for a multi-objective optimization issue, and the outcomes of each strategy are evaluated separately. The first strategy is proposed to maximize the ecological coefficient of performance (ECOP), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F . Furthermore, the second strategy is suggested to maximize the thermal efficiency ( η), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F). All the strategies in the present work are executed via a multi-objective evolutionary algorithms based on NSGA∥ method. Finally, to achieve the final answer in each strategy, three well-known decision makers are executed. Lastly, deviations of the outcomes gained in each strategy and each decision maker are evaluated separately.
Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.
Pecevski, Dejan; Maass, Wolfgang
2016-01-01
Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p (*) that generates the examples it receives. This holds even if p (*) contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference.
Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity123
Pecevski, Dejan
2016-01-01
Abstract Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p* that generates the examples it receives. This holds even if p* contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference. PMID:27419214
Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik
2016-01-01
Actually, a set of ETL software (Extract, Transform and Load) is available to constitute a major investment market. Each ETL uses its own techniques for extracting, transforming and loading data into data warehouse, which makes the task of evaluating ETL software very difficult. However, choosing the right software of ETL is critical to the success or failure of any Business Intelligence project. As there are many impacting factors in the selection of ETL software, the same process is considered as a complex multi-criteria decision making (MCDM) problem. In this study, an application of decision-making methodology that employs the two well-known MCDM techniques, namely Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods is designed. In this respect, the aim of using AHP is to analyze the structure of the ETL software selection problem and obtain weights of the selected criteria. Then, TOPSIS technique is used to calculate the alternatives' ratings. An example is given to illustrate the proposed methodology. Finally, a software prototype for demonstrating both methods is implemented.
Murphy, Kelly; Fafard, Patrick
2012-08-01
Knowledge translation (KT) is a growing movement in clinical and health services research, aimed to help make research more relevant and to move research into practice and policy. This paper examines the conventional model of policy change presented in KT and assesses its applicability for increasing the impact of urban health research on urban health policy. In general, KT conceptualizes research utilization in terms of the technical implementation of scientific findings, on the part of individual decision-makers who can be "targeted" for a KT intervention, in a context that is absent of political interests. However, complex urban health problems and interventions infrequently resemble this single decision, single decision-maker model posited by KT. In order to clarify the conditions under which urban health research is more likely or not to have an influence on public policy development, we propose to supplement the conventional model with three concepts drawn from the social science: policy stages, policy networks, and a discourse analysis approach for theorizing power in policy-making.
Empowering citizens in international governance of nanotechnologies.
Malsch, Ineke; Subramanian, Vrishali; Semenzin, Elena; Hristozov, Danail; Marcomini, Antonio; Mullins, Martin; Hester, Karena; McAlea, Eamonn; Murphy, Finbarr; Tofail, Syed A M
The international dialogue on responsible governance of nanotechnologies engages a wide range of actors with conflicting as well as common interests. It is also characterised by a lack of evidence-based data on uncertain risks of in particular engineered nanomaterials. The present paper aims at deepening understanding of the collective decision making context at international level using the grounded theory approach as proposed by Glaser and Strauss in "The Discovery of Grounded Theory" (1967). This starts by discussing relevant concepts from different fields including sociological and political studies of international relations as well as political philosophy and ethics. This analysis of current trends in international law making is taken as starting point for exploring the role that a software decision support tool could play in multi-stakeholder global governance of nanotechnologies. These theoretical ideas are then compared with the current design of the SUN Decision Support System (SUNDS) under development in the European project on Sustainable Nanotechnologies (SUN, www.sun-fp7.eu). Through constant comparison, the ideas are also compared with requirements of different stakeholders as expressed during a user workshop. This allows for highlighting discussion points for further consideration.
Love as a regulative ideal in surrogate decision making.
Stonestreet, Erica Lucast
2014-10-01
This discussion aims to give a normative theoretical basis for a "best judgment" model of surrogate decision making rooted in a regulative ideal of love. Currently, there are two basic models of surrogate decision making for incompetent patients: the "substituted judgment" model and the "best interests" model. The former draws on the value of autonomy and responds with respect; the latter draws on the value of welfare and responds with beneficence. It can be difficult to determine which of these two models is more appropriate for a given patient, and both approaches may seem inadequate for a surrogate who loves the patient. The proposed "best judgment" model effectively draws on the values incorporated in each of the traditional standards, but does so because these values are important to someone who loves a patient, since love responds to the patient as the specific person she is. © The Author 2014. Published by Oxford University Press, on behalf of the Journal of Medicine and Philosophy Inc. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Predictors of food decision making: A systematic interdisciplinary mapping (SIM) review.
Symmank, Claudia; Mai, Robert; Hoffmann, Stefan; Stok, F Marijn; Renner, Britta; Lien, Nanna; Rohm, Harald
2017-03-01
The number of publications on consumer food decision making and its predictors and correlates has been steadily increasing over the last three decades. Given that different scientific disciplines illuminate this topic from different perspectives, it is necessary to develop an interdisciplinary overview. The aim of this study is to conduct a systematic interdisciplinary mapping (SIM) review by using rapid review techniques to explore the state-of-the-art, and to identify hot topics and research gaps in this field. This interdisciplinary review includes 1,820 publications in 485 different journals and other types of publications from more than ten disciplines (including nutritional science, medicine/health science, psychology, food science and technology, business research, etc.) across a period of 60 years. The identified predictors of food decision making were categorized in line with the recently proposed DONE (Determinants Of Nutrition and Eating behavior) framework. After applying qualitative and quantitative analyses, this study reveals that most of the research emphasizes biological, psychological, and product-related predictors, whereas policy-related influences on food choice are scarcely considered. Copyright © 2016 Elsevier Ltd. All rights reserved.
Evaluating gambles using dynamics
NASA Astrophysics Data System (ADS)
Peters, O.; Gell-Mann, M.
2016-02-01
Gambles are random variables that model possible changes in wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes. Utility functions aim to capture individual psychological characteristics, but their generality limits predictive power. Expectation value maximizers are defined as rational in economics, but expectation values are only meaningful in the presence of ensembles or in systems with ergodic properties, whereas decision-makers have no access to ensembles, and the variables representing wealth in the usual growth models do not have the relevant ergodic properties. Simultaneously addressing the shortcomings of utility and those of expectations, we propose to evaluate gambles by averaging wealth growth over time. No utility function is needed, but a dynamic must be specified to compute time averages. Linear and logarithmic "utility functions" appear as transformations that generate ergodic observables for purely additive and purely multiplicative dynamics, respectively. We highlight inconsistencies throughout the development of decision theory, whose correction clarifies that our perspective is legitimate. These invalidate a commonly cited argument for bounded utility functions.
Empowering citizens in international governance of nanotechnologies
NASA Astrophysics Data System (ADS)
Malsch, Ineke; Subramanian, Vrishali; Semenzin, Elena; Hristozov, Danail; Marcomini, Antonio; Mullins, Martin; Hester, Karena; McAlea, Eamonn; Murphy, Finbarr; Tofail, Syed A. M.
2015-05-01
The international dialogue on responsible governance of nanotechnologies engages a wide range of actors with conflicting as well as common interests. It is also characterised by a lack of evidence-based data on uncertain risks of in particular engineered nanomaterials. The present paper aims at deepening understanding of the collective decision making context at international level using the grounded theory approach as proposed by Glaser and Strauss in "The Discovery of Grounded Theory" (1967). This starts by discussing relevant concepts from different fields including sociological and political studies of international relations as well as political philosophy and ethics. This analysis of current trends in international law making is taken as starting point for exploring the role that a software decision support tool could play in multi-stakeholder global governance of nanotechnologies. These theoretical ideas are then compared with the current design of the SUN Decision Support System (SUNDS) under development in the European project on Sustainable Nanotechnologies (SUN, www.sun-fp7.eu). Through constant comparison, the ideas are also compared with requirements of different stakeholders as expressed during a user workshop. This allows for highlighting discussion points for further consideration.
A SOMATIC-MARKER THEORY OF ADDICTION
Verdejo-García, Antonio; Bechara, Antoine
2009-01-01
Similar to patients with ventromedial prefrontal cortex (VMPC) lesions, substance abusers show altered decision-making, characterized by a tendency to choose the immediate reward, at the expense of negative future consequences. The somatic-marker model proposes that decision-making depends on neural substrates that regulate homeostasis, emotion and feeling. According to this model, there should be a link between alterations in processing emotions in substance abusers, and their impairments in decision-making. A growing evidence from neuroscientific studies indicate that core aspects of addiction may be explained in terms of abnormal emotional/homeostatic guidance of decision-making. Behavioural studies have revealed emotional processing and decision-making deficits in substance abusers. Neuroimaging studies have shown that altered decision-making in addiction is associated with abnormal functioning of a distributed neural network critical for the processing of emotional information, and the experience of “craving”, including the VMPC, the amygdala, the striatum, the anterior cingulate cortex, and the insular/somato-sensory cortices, as well as non-specific neurotransmitter systems that modulate activities of neural processes involved in decision-making. The aim of this paper is to review this growing evidence, and to examine the extent of which these studies support a somatic-marker theory of addiction. We conclude that there are at least two underlying types of dysfunctions where emotional signals (somatic-markers) turns in favor of immediate outcomes in addiction: (1) a hyperactivity in the amygdala or impulsive system, which exaggerates the rewarding impact of available incentives, and (2) hypoactivity in the prefrontal cortex or reflective system, which forecasts the long-term consequences of a given action. PMID:18722390
AdViSHE: A Validation-Assessment Tool of Health-Economic Models for Decision Makers and Model Users.
Vemer, P; Corro Ramos, I; van Voorn, G A K; Al, M J; Feenstra, T L
2016-04-01
A trade-off exists between building confidence in health-economic (HE) decision models and the use of scarce resources. We aimed to create a practical tool providing model users with a structured view into the validation status of HE decision models, to address this trade-off. A Delphi panel was organized, and was completed by a workshop during an international conference. The proposed tool was constructed iteratively based on comments from, and the discussion amongst, panellists. During the Delphi process, comments were solicited on the importance and feasibility of possible validation techniques for modellers, their relevance for decision makers, and the overall structure and formulation in the tool. The panel consisted of 47 experts in HE modelling and HE decision making from various professional and international backgrounds. In addition, 50 discussants actively engaged in the discussion at the conference workshop and returned 19 questionnaires with additional comments. The final version consists of 13 items covering all relevant aspects of HE decision models: the conceptual model, the input data, the implemented software program, and the model outcomes. Assessment of the Validation Status of Health-Economic decision models (AdViSHE) is a validation-assessment tool in which model developers report in a systematic way both on validation efforts performed and on their outcomes. Subsequently, model users can establish whether confidence in the model is justified or whether additional validation efforts should be undertaken. In this way, AdViSHE enhances transparency of the validation status of HE models and supports efficient model validation.
Health Care Decision Support System for the Pediatric Emeregency Department Management.
Ben Othman, Sarah; Hammadi, Slim; Quilliot, Alain; Martinot, Alain; Renard, Jean-Marie
2015-01-01
Health organization management is facing a high amount of complexity due to the inherent dynamics of the processes and the distributed organization of hospitals. It is therefore necessary for health care institutions to focus on this issue in order to deal with patients' requirements and satisfy their needs. The main objective of this study is to develop and implement a Decision Support System which can help physicians to better manage their organization, to anticipate the overcrowding feature, and to establish avoidance proposals for it. This work is a part of HOST project (Hospital: Optimization, Simulation, and Crowding Avoidance) of the French National Research Agency (ANR). It aims to optimize the functioning of the Pediatric Emergency Department characterized by stochastic arrivals of patients which leads to its overcrowding and services overload. Our study is a set of tools to smooth out patient flows, enhance care quality and minimize long waiting times and costs due to resources allocation. So we defined a decision aided tool based on Multi-agent Systems where actors negotiate and cooperate under some constraints in a dynamic environment. These entities which can be either physical agents representing real actors in the health care institution or software agents allowing the implementation of optimizing tools, cooperate to satisfy the demands of patients while respecting emergency degrees. This paper is concerned with agents' negotiation. It proposes a new approach for multi-skill tasks scheduling based on interactions between agents.
To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task
Lamb, Maurice; Kallen, Rachel W.; Harrison, Steven J.; Di Bernardo, Mario; Minai, Ali; Richardson, Michael J.
2017-01-01
Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the affordance related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of what, when, where and how to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning. PMID:28701975
A customisable framework for the assessment of therapies in the solution of therapy decision tasks.
Manjarrés Riesco, A; Martínez Tomás, R; Mira Mira, J
2000-01-01
In current medical research, a growing interest can be observed in the definition of a global therapy-evaluation framework which integrates considerations such as patients preferences and quality-of-life results. In this article, we propose the use of the research results in this domain as a source of knowledge in the design of support systems for therapy decision analysis, in particular with a view to application in oncology. We discuss the incorporation of these considerations in the definition of the therapy-assessment methods involved in the solution of a generic therapy decision task, described in the context of AI software development methodologies such as CommonKADS. The goal of the therapy decision task is to identify the ideal therapy, for a given patient, in accordance with a set of objectives of a diverse nature. The assessment methods applied are based either on data obtained from statistics or on the specific idiosyncrasies of each patient, as identified from their responses to a suite of psychological tests. In the analysis of the therapy decision task we emphasise the importance, from a methodological perspective, of using a rigorous approach to the modelling of domain ontologies and domain-specific data. To this aim we make extensive use of the semi-formal object oriented analysis notation UML to describe the domain level.
Preliminary Turkish study of psychiatric in-patients' competence to make treatment decisions.
Aydin Er, Rahime; Sehiralti, Mine; Aker, Ahmet Tamer
2013-03-01
Competence is a prerequisite for informed consent. Patients who are found to be competent are entitled to accept or refuse the proposed treatment. In recent years, there has been an increased interest in studies examining competence for treatment in psychiatric patients. In this study, we aimed to investigate the decision-making competencies of inpatients with a range of psychiatric diseases. This study was carried out at the psychiatry clinic of Kocaeli University Hospital in Turkey from June 2007 to February 2008. Decision-making competence was assessed in 83 patients using the MacArthur Competence Assessment Tool-Treatment (MacCAT-T). The study groups consisted of patients with mood (39.8%), psychotic (27.7%) and anxiety disorders (18.1%), and alcohol/substance addiction (14.5%). There was a significant relation between decision-making competence and demographic and clinical characteristics. Appreciation of the given information was more impaired in psychotic disorder patients than in other patients, but understanding and reasoning of the given information was similar in all groups. These results reveal the importance of evaluating decision-making competencies of psychiatric patients before any treatment or intervention is carried out to ascertain their ability to give informed consent to treatment. Institutional and national policies need to be determined and put into practice relating to the assessment and management of competence in patients with psychiatric disorders. Copyright © 2012 Wiley Publishing Asia Pty Ltd.
Life cycle assessment of a national policy proposal - the case of a Swedish waste incineration tax.
Björklund, Anna E; Finnveden, Göran
2007-01-01
At the core of EU and Swedish waste policy is the so-called waste hierarchy, according to which waste should first be prevented, but should otherwise be treated in the following order of prioritisation: reuse, recycling when environmentally motivated, energy recovery, and last landfilling. Some recent policy decisions in Sweden aim to influence waste management in the direction of the waste hierarchy. In 2001 a governmental commission assessed the economic and environmental impacts of introducing a weight-based tax on waste incineration, the purpose of which would be to encourage waste reduction and increase materials recycling and biological treatment. This paper presents the results of a life cycle assessment (LCA) of the waste incineration tax proposal. It was done in the context of a larger research project concerning the development and testing of a framework for Strategic Environmental Assessment (SEA). The aim of this paper is to assess the life cycle environmental impacts of the waste incineration tax proposal, and to investigate whether there are any possibilities of more optimal design of such a tax. The proposed design of the waste incineration tax results in increased recycling, but only in small environmental improvements. A more elaborate tax design is suggested, in which the tax level would partly be related to the fossil carbon content of the waste.
Analyzing Strategic Business Rules through Simulation Modeling
NASA Astrophysics Data System (ADS)
Orta, Elena; Ruiz, Mercedes; Toro, Miguel
Service Oriented Architecture (SOA) holds promise for business agility since it allows business process to change to meet new customer demands or market needs without causing a cascade effect of changes in the underlying IT systems. Business rules are the instrument chosen to help business and IT to collaborate. In this paper, we propose the utilization of simulation models to model and simulate strategic business rules that are then disaggregated at different levels of an SOA architecture. Our proposal is aimed to help find a good configuration for strategic business objectives and IT parameters. The paper includes a case study where a simulation model is built to help business decision-making in a context where finding a good configuration for different business parameters and performance is too complex to analyze by trial and error.
High-frequency health data and spline functions.
Martín-Rodríguez, Gloria; Murillo-Fort, Carlos
2005-03-30
Seasonal variations are highly relevant for health service organization. In general, short run movements of medical magnitudes are important features for managers in this field to make adequate decisions. Thus, the analysis of the seasonal pattern in high-frequency health data is an appealing task. The aim of this paper is to propose procedures that allow the analysis of the seasonal component in this kind of data by means of spline functions embedded into a structural model. In the proposed method, useful adaptions of the traditional spline formulation are developed, and the resulting procedures are capable of capturing periodic variations, whether deterministic or stochastic, in a parsimonious way. Finally, these methodological tools are applied to a series of daily emergency service demand in order to capture simultaneous seasonal variations in which periods are different.
USDA-ARS?s Scientific Manuscript database
The International Code of Nomenclature for algae, fungi and plants is revised every six years to incorporate decisions of the Nomenclature Section of successive International Botanical Congresses (IBC) on proposals to amend the Code. The proposals in this paper will be considered at the IBC in Shenz...
Advances in the Application of Decision Theory to Test-Based Decision Making.
ERIC Educational Resources Information Center
van der Linden, Wim J.
This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical Bayesian framework. Classification decisions with…
Ethical Frameworks in Public Health Decision-Making: Defending a Value-Based and Pluralist Approach.
Grill, Kalle; Dawson, Angus
2017-12-01
A number of ethical frameworks have been proposed to support decision-making in public health and the evaluation of public health policy and practice. This is encouraging, since ethical considerations are of paramount importance in health policy. However, these frameworks have various deficiencies, in part because they incorporate substantial ethical positions. In this article, we discuss and criticise a framework developed by James Childress and Ruth Bernheim, which we consider to be the state of the art in the field. Their framework distinguishes aims, such as the promotion of public health, from constraints on the pursuit of those aims, such as the requirement to avoid limitations to liberty, or the requirement to be impartial. We show how this structure creates both theoretical and practical problems. We then go on to present and defend a more practical framework, one that is neutral in avoiding precommitment to particular values and how they ought to be weighted. We believe ethics is at the very heart of such weightings and our framework is developed to reflect this belief. It is therefore both pluralist and value-based. We compare our new framework to Childress and Bernheim's and outline its advantages. It is justified by its impetus to consider a wide range of alternatives and its tendency to direct decisions towards the best alternatives, as well as by the information provided by the ranking of alternatives and transparent explication of the judgements that motivate this ranking. The new framework presented should be useful to decision-makers in public health, as well as being a means to stimulate further reflection on the role of ethics in public health.
Integration of PKPD relationships into benefit–risk analysis
Bellanti, Francesco; van Wijk, Rob C; Danhof, Meindert; Della Pasqua, Oscar
2015-01-01
Aim Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit–risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit–risk assessment. In addition, we propose the use of pharmacokinetic–pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents. Methods A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit–risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile. Results A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit–risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit–risk balance before extensive evidence is generated in clinical practice. Conclusions Benefit–risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials. PMID:25940398
De Lara, M; Martinet, V
2009-02-01
Managing natural resources in a sustainable way is a hard task, due to uncertainties, dynamics and conflicting objectives (ecological, social, and economical). We propose a stochastic viability approach to address such problems. We consider a discrete-time control dynamical model with uncertainties, representing a bioeconomic system. The sustainability of this system is described by a set of constraints, defined in practice by indicators - namely, state, control and uncertainty functions - together with thresholds. This approach aims at identifying decision rules such that a set of constraints, representing various objectives, is respected with maximal probability. Under appropriate monotonicity properties of dynamics and constraints, having economic and biological content, we characterize an optimal feedback. The connection is made between this approach and the so-called Management Strategy Evaluation for fisheries. A numerical application to sustainable management of Bay of Biscay nephrops-hakes mixed fishery is given.
Identifying Cost-Effective Dynamic Policies to Control Epidemics
Yaesoubi, Reza; Cohen, Ted
2016-01-01
We describe a mathematical decision model for identifying dynamic health policies for controlling epidemics. These dynamic policies aim to select the best current intervention based on accumulating epidemic data and the availability of resources at each decision point. We propose an algorithm to approximate dynamic policies that optimize the population’s net health benefit, a performance measure which accounts for both health and monetary outcomes. We further illustrate how dynamic policies can be defined and optimized for the control of a novel viral pathogen, where a policy maker must decide (i) when to employ or lift a transmission-reducing intervention (e.g. school closure) and (ii) how to prioritize population members for vaccination when a limited quantity of vaccines first become available. Within the context of this application, we demonstrate that dynamic policies can produce higher net health benefit than more commonly described static policies that specify a pre-determined sequence of interventions to employ throughout epidemics. PMID:27449759
Methodological Challenges to Economic Evaluations of Vaccines: Is a Common Approach Still Possible?
Jit, Mark; Hutubessy, Raymond
2016-06-01
Economic evaluation of vaccination is a key tool to inform effective spending on vaccines. However, many evaluations have been criticised for failing to capture features of vaccines which are relevant to decision makers. These include broader societal benefits (such as improved educational achievement, economic growth and political stability), reduced health disparities, medical innovation, reduced hospital beds pressures, greater peace of mind and synergies in economic benefits with non-vaccine interventions. Also, the fiscal implications of vaccination programmes are not always made explicit. Alternative methodological frameworks have been proposed to better capture these benefits. However, any broadening of the methodology for economic evaluation must also involve evaluations of non-vaccine interventions, and hence may not always benefit vaccines given a fixed health-care budget. The scope of an economic evaluation must consider the budget from which vaccines are funded, and the decision-maker's stated aims for that spending to achieve.
Efficient Verification of Holograms Using Mobile Augmented Reality.
Hartl, Andreas Daniel; Arth, Clemens; Grubert, Jens; Schmalstieg, Dieter
2016-07-01
Paper documents such as passports, visas and banknotes are frequently checked by inspection of security elements. In particular, optically variable devices such as holograms are important, but difficult to inspect. Augmented Reality can provide all relevant information on standard mobile devices. However, hologram verification on mobiles still takes long and provides lower accuracy than inspection by human individuals using appropriate reference information. We aim to address these drawbacks by automatic matching combined with a special parametrization of an efficient goal-oriented user interface which supports constrained navigation. We first evaluate a series of similarity measures for matching hologram patches to provide a sound basis for automatic decisions. Then a re-parametrized user interface is proposed based on observations of typical user behavior during document capture. These measures help to reduce capture time to approximately 15 s with better decisions regarding the evaluated samples than what can be achieved by untrained users.
Yun, Seokhwa; Takeuchi, Riki; Liu, Wei
2007-05-01
This study examined the effects of employee self-enhancement motives on job performance behaviors (organizational citizenship behaviors and task performance) and the value of these behaviors to them. The authors propose that employees display job performance behaviors in part to enhance their self-image, especially when their role is not clearly defined. They further argue that the effects of these behaviors on managerial reward recommendation decisions should be stronger when managers believe the employees to be more committed. The results from a sample of 84 working students indicate that role ambiguity moderated the effects of self-enhancement motives on job performance behaviors and that managerial perceptions of an employee's commitment moderated the effects of those organizational citizenship behaviors that are aimed at other individuals on managers' reward allocation decisions. 2007 APA, all rights reserved
NASA Astrophysics Data System (ADS)
Fatrias, D.; Kamil, I.; Meilani, D.
2018-03-01
Coordinating business operation with suppliers becomes increasingly important to survive and prosper under the dynamic business environment. A good partnership with suppliers not only increase efficiency, but also strengthen corporate competitiveness. Associated with such concern, this study aims to develop a practical approach of multi-criteria supplier evaluation using combined methods of Taguchi loss function (TLF), best-worst method (BWM) and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR). A new framework of integrative approach adopting these methods is our main contribution for supplier evaluation in literature. In this integrated approach, a compromised supplier ranking list based on the loss score of suppliers is obtained using efficient steps of a pairwise comparison based decision making process. Implemetation to the case problem with real data from crumb rubber industry shows the usefulness of the proposed approach. Finally, a suitable managerial implication is presented.
Recommendation System for Adaptive Learning.
Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang
2018-01-01
An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.
Richert, Laura; Doussau, Adélaïde; Lelièvre, Jean-Daniel; Arnold, Vincent; Rieux, Véronique; Bouakane, Amel; Lévy, Yves; Chêne, Geneviève; Thiébaut, Rodolphe
2014-02-26
Many candidate vaccine strategies against human immunodeficiency virus (HIV) infection are under study, but their clinical development is lengthy and iterative. To accelerate HIV vaccine development optimised trial designs are needed. We propose a randomised multi-arm phase I/II design for early stage development of several vaccine strategies, aiming at rapidly discarding those that are unsafe or non-immunogenic. We explored early stage designs to evaluate both the safety and the immunogenicity of four heterologous prime-boost HIV vaccine strategies in parallel. One of the vaccines used as a prime and boost in the different strategies (vaccine 1) has yet to be tested in humans, thus requiring a phase I safety evaluation. However, its toxicity risk is considered minimal based on data from similar vaccines. We newly adapted a randomised phase II trial by integrating an early safety decision rule, emulating that of a phase I study. We evaluated the operating characteristics of the proposed design in simulation studies with either a fixed-sample frequentist or a continuous Bayesian safety decision rule and projected timelines for the trial. We propose a randomised four-arm phase I/II design with two independent binary endpoints for safety and immunogenicity. Immunogenicity evaluation at trial end is based on a single-stage Fleming design per arm, comparing the observed proportion of responders in an immunogenicity screening assay to an unacceptably low proportion, without direct comparisons between arms. Randomisation limits heterogeneity in volunteer characteristics between arms. To avoid exposure of additional participants to an unsafe vaccine during the vaccine boost phase, an early safety decision rule is imposed on the arm starting with vaccine 1 injections. In simulations of the design with either decision rule, the risks of erroneous conclusions were controlled <15%. Flexibility in trial conduct is greater with the continuous Bayesian rule. A 12-month gain in timelines is expected by this optimised design. Other existing designs such as bivariate or seamless phase I/II designs did not offer a clear-cut alternative. By combining phase I and phase II evaluations in a multi-arm trial, the proposed optimised design allows for accelerating early stage clinical development of HIV vaccine strategies.
Gather, Jakov
2018-01-01
It is widely accepted among medical ethicists that competence is a necessary condition for informed consent. In this view, if a patient is incompetent to make a particular treatment decision, the decision must be based on an advance directive or made by a substitute decision-maker on behalf of the patient. We call this the competence model. According to a recent report of the United Nations (UN) High Commissioner for Human Rights, article 12 of the UN Convention on the Rights of Persons with Disabilities (CRPD) presents a wholesale rejection of the competence model. The High Commissioner here adopts the interpretation of article 12 proposed by the Committee on the Rights of Persons with Disabilities. On this interpretation, CRPD article 12 renders it impermissible to deny persons with mental disabilities the right to make treatment decisions on the basis of impaired decision-making capacity and demands the replacement of all regimes of substitute decision-making by supported decision-making. In this paper, we explicate six adverse consequences of CRPD article 12 for persons with mental disabilities and propose an alternative way forward. The proposed model combines the strengths of the competence model and supported decision-making. PMID:29070707
Impaired social decision making in patients with major depressive disorder.
Wang, Yun; Zhou, Yuan; Li, Shu; Wang, Peng; Wu, Guo-Wei; Liu, Zhe-Ning
2014-01-23
Abnormal decision-making processes have been observed in patients with major depressive disorder (MDD). However, it is unresolved whether MDD patients show abnormalities in decision making in a social interaction context, in which decisions have actual influences on both the self-interests of the decision makers per se and those of their partners. Using a well-studied ultimatum game (UG), which is frequently used to investigate social interaction behavior, we examined whether MDD can be associated with abnormalities in social decision-making behavior by comparing the acceptance rates of MDD patients (N = 14) with those of normal controls (N = 19). The acceptance rates of the patients were lower than those of the normal controls. Additionally, unfair proposals were accepted at similar rates from computer partners and human partners in the MDD patients, unlike the acceptance rates in the normal controls, who were able to discriminatively treat unfair proposals from computer partners and human partners. Depressed patients show abnormal decision-making behavior in a social interaction context. Several possible explanations, such as increased sensitivity to fairness, negative emotional state and disturbed affective cognition, have been proposed to account for the abnormal social decision-making behavior in patients with MDD. This aberrant social decision-making behavior may provide a new perspective in the search to find biomarkers for the diagnosis and prognosis of MDD.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhan, Yiduo; Zheng, Qipeng P.; Wang, Jianhui
Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined future uncertainties (i.e., fixed random outcomes with given probabilities). In several recent studies of generation assets' planning (e.g., thermal versus renewable), new findings show that the investment decisions could affect the future uncertainties as well. To this end, this paper proposes a multistage decision-dependent stochastic optimization model for long-term large-scale generation expansion planning, where large amounts of windmore » power are involved. In the decision-dependent model, the future uncertainties are not only affecting but also affected by the current decisions. In particular, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming model. The wind penetration, investment decisions, and the optimality of the decision-dependent model are evaluated in a series of multistage case studies. The results show that the proposed decision-dependent model provides effective optimization solutions for long-term generation expansion planning.« less
Validation of educational assessments: a primer for simulation and beyond.
Cook, David A; Hatala, Rose
2016-01-01
Simulation plays a vital role in health professions assessment. This review provides a primer on assessment validation for educators and education researchers. We focus on simulation-based assessment of health professionals, but the principles apply broadly to other assessment approaches and topics. Validation refers to the process of collecting validity evidence to evaluate the appropriateness of the interpretations, uses, and decisions based on assessment results. Contemporary frameworks view validity as a hypothesis, and validity evidence is collected to support or refute the validity hypothesis (i.e., that the proposed interpretations and decisions are defensible). In validation, the educator or researcher defines the proposed interpretations and decisions, identifies and prioritizes the most questionable assumptions in making these interpretations and decisions (the "interpretation-use argument"), empirically tests those assumptions using existing or newly-collected evidence, and then summarizes the evidence as a coherent "validity argument." A framework proposed by Messick identifies potential evidence sources: content, response process, internal structure, relationships with other variables, and consequences. Another framework proposed by Kane identifies key inferences in generating useful interpretations: scoring, generalization, extrapolation, and implications/decision. We propose an eight-step approach to validation that applies to either framework: Define the construct and proposed interpretation, make explicit the intended decision(s), define the interpretation-use argument and prioritize needed validity evidence, identify candidate instruments and/or create/adapt a new instrument, appraise existing evidence and collect new evidence as needed, keep track of practical issues, formulate the validity argument, and make a judgment: does the evidence support the intended use? Rigorous validation first prioritizes and then empirically evaluates key assumptions in the interpretation and use of assessment scores. Validation science would be improved by more explicit articulation and prioritization of the interpretation-use argument, greater use of formal validation frameworks, and more evidence informing the consequences and implications of assessment.
24 CFR 55.20 - Decision making process.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Decision making process. 55.20... Decision making process. The decision making process for compliance with this part contains eight steps... decision making process are: (a) Step 1. Determine whether the proposed action is located in a 100-year...
Decision making and coping in healthcare: the Coping in Deliberation (CODE) framework.
Witt, Jana; Elwyn, Glyn; Wood, Fiona; Brain, Kate
2012-08-01
To develop a framework of decision making and coping in healthcare that describes the twin processes of appraisal and coping faced by patients making preference-sensitive healthcare decisions. We briefly review the literature for decision making theories and coping theories applicable to preference-sensitive decisions in healthcare settings. We describe first decision making, then coping and finally attempt to integrate these processes by building on current theory. Deliberation in healthcare may be described as a six step process, comprised of the presentation of a health threat, choice, options, preference construction, the decision itself and consolidation post-decision. Coping can be depicted in three stages, beginning with a threat, followed by primary and secondary appraisal and ultimately resulting in a coping effort. Drawing together concepts from prominent decision making theories and coping theories, we propose a multidimensional, interactive framework which integrates both processes and describes coping in deliberation. The proposed framework offers an insight into the complexity of decision making in preference-sensitive healthcare contexts from a patient perspective and may act as theoretical basis for decision support. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
2018-01-01
Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956
Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan
2018-01-01
Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.
Lateral OFC activity predicts decision bias due to first impressions during ultimatum games.
Kim, Hackjin; Choi, Min-Jo; Jang, In-Ji
2012-02-01
Despite the prevalence and potentially harmful consequences of first impression bias during social decision-making, its precise neural underpinnings remain unclear. Here, on the basis of the fMRI study using ultimatum games, the authors show that the responders' decisions to accept or reject offers were significantly affected by facial trustworthiness of proposers. Analysis using a model-based fMRI method revealed that activity in the right lateral OFC (lOFC) of responders increased as a function of negative decision bias, indicating a greater likelihood of rejecting otherwise fair offers, possibly because of the facial trustworthiness of proposers. In addition, lOFC showed changes in functional connectivity strength with amygdala and insula as a function of decision bias, and individual differences in the strengths of connectivities between lOFC and bilateral insula were also found to predict the likelihood of responders to reject offers from untrustworthy-looking proposers. The present findings emphasize that the lOFC plays a pivotal role in integrating signals related to facial impression and creating signal biasing decisions during social interactions.
Advanced Information Technology in Simulation Based Life Cycle Design
NASA Technical Reports Server (NTRS)
Renaud, John E.
2003-01-01
In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.
Fuzzy bilevel programming with multiple non-cooperative followers: model, algorithm and application
NASA Astrophysics Data System (ADS)
Ke, Hua; Huang, Hu; Ralescu, Dan A.; Wang, Lei
2016-04-01
In centralized decision problems, it is not complicated for decision-makers to make modelling technique selections under uncertainty. When a decentralized decision problem is considered, however, choosing appropriate models is no longer easy due to the difficulty in estimating the other decision-makers' inconclusive decision criteria. These decision criteria may vary with different decision-makers because of their special risk tolerances and management requirements. Considering the general differences among the decision-makers in decentralized systems, we propose a general framework of fuzzy bilevel programming including hybrid models (integrated with different modelling methods in different levels). Specially, we discuss two of these models which may have wide applications in many fields. Furthermore, we apply the proposed two models to formulate a pricing decision problem in a decentralized supply chain with fuzzy coefficients. In order to solve these models, a hybrid intelligent algorithm integrating fuzzy simulation, neural network and particle swarm optimization based on penalty function approach is designed. Some suggestions on the applications of these models are also presented.
Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing
2015-01-01
A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.
Understanding clinical work practices for cross-boundary decision support in e-health.
Tawfik, Hissam; Anya, Obinna; Nagar, Atulya K
2012-07-01
One of the major concerns of research in integrated healthcare information systems is to enable decision support among clinicians across boundaries of organizations and regional workgroups. A necessary precursor, however, is to facilitate the construction of appropriate awareness of local clinical practices, including a clinician's actual cognitive capabilities, peculiar workplace circumstances, and specific patient-centered needs based on real-world clinical contexts across work settings. In this paper, a user-centered study aimed to investigate clinical practices across three different geographical areas-the U.K., the UAE and Nigeria-is presented. The findings indicate that differences in clinical practices among clinicians are associated with differences in local work contexts across work settings, but are moderated by adherence to best practice guidelines and the need for patient-centered care. The study further reveals that an awareness especially of the ontological, stereotypical, and situated practices plays a crucial role in adapting knowledge for cross-boundary decision support. The paper then outlines a set of design guidelines for the development of enterprise information systems for e-health. Based on the guidelines, the paper proposes the conceptual design of CaDHealth, a practice-centered framework for making sense of clinical practices across work settings for effective cross-boundary e-health decision support.
Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith
2015-01-01
Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.
How do strategic decisions and operative practices affect operating room productivity?
Peltokorpi, Antti
2011-12-01
Surgical operating rooms are cost-intensive parts of health service production. Managing operating units efficiently is essential when hospitals and healthcare systems aim to maximize health outcomes with limited resources. Previous research about operating room management has focused on studying the effect of management practices and decisions on efficiency by utilizing mainly modeling approach or before-after analysis in single hospital case. The purpose of this research is to analyze the synergic effect of strategic decisions and operative management practices on operating room productivity and to use a multiple case study method enabling statistical hypothesis testing with empirical data. 11 hypotheses that propose connections between the use of strategic and operative practices and productivity were tested in a multi-hospital study that included 26 units. The results indicate that operative practices, such as personnel management, case scheduling and performance measurement, affect productivity more remarkably than do strategic decisions that relate to, e.g., units' size, scope or academic status. Units with different strategic positions should apply different operative practices: Focused hospital units benefit most from sophisticated case scheduling and parallel processing whereas central and ambulatory units should apply flexible working hours, incentives and multi-skilled personnel. Operating units should be more active in applying management practices which are adequate for their strategic orientation.
A Decision-Support System for Sustainable Water Distribution System Planning.
Freund, Alina; Aydin, Nazli Yonca; Zeckzer, Dirk; Hagen, Hans
2017-01-01
An interactive decision-support system (DSS) can help experts prepare water resource management plans for decision makers and stakeholders. The design of the proposed prototype incorporates visualization techniques such as circle views, grid layout, small multiple maps, and node simplification to improve the data readability of water distribution systems. A case study with three urban water management and sanitary engineering experts revealed that the proposed DSS is satisfactory, efficient, and effective.
Surrogate decision making and intellectual virtue.
Bock, Gregory L
2014-01-01
Patients can be harmed by a religiously motivated surrogate decision maker whose decisions are contrary to the standard of care; therefore, surrogate decision making should be held to a high standard. Stewart Eskew and Christopher Meyers proposed a two-part rule for deciding which religiously based decisions to honor: (1) a secular reason condition and (2) a rationality condition. The second condition is based on a coherence theory of rationality, which they claim is accessible, generous, and culturally sensitive. In this article, I will propose strengthening the rationality condition by grounding it in a theory of intellectual virtue, which is both rigorous and culturally sensitive. Copyright 2014 The Journal of Clinical Ethics. All rights reserved.
Hou, Kun-Mean; Zhang, Zhan
2017-01-01
Cyber Physical Systems (CPSs) need to interact with the changeable environment under various interferences. To provide continuous and high quality services, a self-managed CPS should automatically reconstruct itself to adapt to these changes and recover from failures. Such dynamic adaptation behavior introduces systemic challenges for CPS design, advice evaluation and decision process arrangement. In this paper, a formal compositional framework is proposed to systematically improve the dependability of the decision process. To guarantee the consistent observation of event orders for causal reasoning, this work first proposes a relative time-based method to improve the composability and compositionality of the timing property of events. Based on the relative time solution, a formal reference framework is introduced for self-managed CPSs, which includes a compositional FSM-based actor model (subsystems of CPS), actor-based advice and runtime decomposable decisions. To simplify self-management, a self-similar recursive actor interface is proposed for decision (actor) composition. We provide constraints and seven patterns for the composition of reliability and process time requirements. Further, two decentralized decision process strategies are proposed based on our framework, and we compare the reliability with the static strategy and the centralized processing strategy. The simulation results show that the one-order feedback strategy has high reliability, scalability and stability against the complexity of decision and random failure. This paper also shows a way to simplify the evaluation for dynamic system by improving the composability and compositionality of the subsystem. PMID:29120357
Zhou, Peng; Zuo, Decheng; Hou, Kun-Mean; Zhang, Zhan
2017-11-09
Cyber Physical Systems (CPSs) need to interact with the changeable environment under various interferences. To provide continuous and high quality services, a self-managed CPS should automatically reconstruct itself to adapt to these changes and recover from failures. Such dynamic adaptation behavior introduces systemic challenges for CPS design, advice evaluation and decision process arrangement. In this paper, a formal compositional framework is proposed to systematically improve the dependability of the decision process. To guarantee the consistent observation of event orders for causal reasoning, this work first proposes a relative time-based method to improve the composability and compositionality of the timing property of events. Based on the relative time solution, a formal reference framework is introduced for self-managed CPSs, which includes a compositional FSM-based actor model (subsystems of CPS), actor-based advice and runtime decomposable decisions. To simplify self-management, a self-similar recursive actor interface is proposed for decision (actor) composition. We provide constraints and seven patterns for the composition of reliability and process time requirements. Further, two decentralized decision process strategies are proposed based on our framework, and we compare the reliability with the static strategy and the centralized processing strategy. The simulation results show that the one-order feedback strategy has high reliability, scalability and stability against the complexity of decision and random failure. This paper also shows a way to simplify the evaluation for dynamic system by improving the composability and compositionality of the subsystem.
Code of Federal Regulations, 2010 CFR
2010-07-01
... decision, the debarring official shall consider the seriousness of the purchaser's acts or omissions and any mitigating factors. (b) Effect of proposed debarment. (1) Upon issuance of a notice of proposed debarment by the debarring official and until the final debarment decision is rendered, the Forest Service...
Kawamoto, Kensaku; Lobach, David F
2007-01-01
Despite their demonstrated effectiveness, clinical decision support (CDS) systems are not widely used within the U.S. The Roadmap for National Action on Clinical Decision Support, published in June 2006 by the American Medical Informatics Association, identifies six strategic objectives for achieving widespread adoption of effective CDS capabilities. In this manuscript, we propose a Service-Oriented Architecture (SOA) for CDS that facilitates achievement of these six objectives. Within the proposed framework, CDS capabilities are implemented through the orchestration of independent software services whose interfaces are being standardized by Health Level 7 and the Object Management Group through their joint Healthcare Services Specification Project (HSSP). Core services within this framework include the HSSP Decision Support Service, the HSSP Common Terminology Service, and the HSSP Retrieve, Locate, and Update Service. Our experiences, and those of others, indicate that the proposed SOA approach to CDS could enable the widespread adoption of effective CDS within the U.S. health care system.
Ryterska, Agata; Jahanshahi, Marjan; Osman, Magda
2014-01-01
Studies examining decision-making in people with Parkinson's disease (PD) show impaired performance on a variety of tasks. However, there are also demonstrations that patients with PD can make optimal decisions just like healthy age-matched controls. We propose that the reason for these mixed findings is that PD does not produce a generalized impairment of decision-making, but rather affects sub-components of this process. In this review we evaluate this hypothesis by considering the empirical evidence examining decision-making in PD. We suggest that of the various stages of the decision-making process, the most affected in PD are (1) the cost-benefit analysis stage and (2) the outcome evaluation stage. We consider the implications of this proposal for research in this area.
Self-management interventions: Proposal and validation of a new operational definition.
Jonkman, Nini H; Schuurmans, Marieke J; Jaarsma, Tiny; Shortridge-Baggett, Lillie M; Hoes, Arno W; Trappenburg, Jaap C A
2016-12-01
Systematic reviews on complex interventions like self-management interventions often do not explicitly state an operational definition of the intervention studied, which may impact the review's conclusions. This study aimed to propose an operational definition of self-management interventions and determine its discriminative performance compared with other operational definitions. Systematic review of definitions of self-management interventions and consensus meetings with self-management research experts and practitioners. Self-management interventions were defined as interventions that aim to equip patients with skills to actively participate and take responsibility in the management of their chronic condition in order to function optimally through at least knowledge acquisition and a combination of at least two of the following: stimulation of independent sign/symptom monitoring, medication management, enhancing problem-solving and decision-making skills for medical treatment management, and changing their physical activity, dietary, and/or smoking behavior. This definition substantially reduced the number of selected studies (255 of 750). In two preliminary expert meetings (n = 6), the proposed definition was identifiable for self-management research experts and practitioners (80% and 60% agreement, respectively). Future systematic reviews must carefully consider the operational definition of the intervention studied because the definition influences the selection of studies on which conclusions and recommendations for clinical practice are based. Copyright © 2016 Elsevier Inc. All rights reserved.
Optical identification of two nearby Isolated Neutron Stars through proper motion measuremnt.
NASA Astrophysics Data System (ADS)
Zane, Silvia
2004-07-01
Aim of this proposal is to perform high-resolution imaging of the proposed optical counterparts of the two, radio silent, isolated neutron stars RXJ1308.6+2127 and RX J1605.3+3249 with the STIS/50CCD. Imaging both fields with the same instrumental configuration used in mid 2001 by Kaplan et al {2002; 2003}, will allow us to measure the objects' position and to determine their proper motions over a time base of nearly four years. The measurement of proper motions at the level of at least few tens mas/yr, expected for relatively nearby neutron stars, would unambigouosly secure the proposed optical identifications, not achievable otherwise. In addition, the knowledge of the proper motion will provide useful indications on the space velocity and distance of these neutrons stars, as well as on the radius. Constraining these parameters is of paramount importance to discriminate between the variety of emission mechanisms invoked to explain their observed thermal X-ray spectra and to probe the neutron star equation of state {EOS}. The determination of the proper motion is a decisive step toward a dedicated follow-up program aimed at measuring the objects' optical parallax, thus providing much firmer constrains on the star properties, again to be performed with the STIS/50CCD.
Wortley, Sally; Tong, Allison; Lancsar, Emily; Salkeld, Glenn; Howard, Kirsten
2015-07-14
Much attention in recent years has been given to the topic of public engagement in health technology assessment (HTA) decision-making. HTA organizations spend substantial resources and time on undertaking public engagement, and numerous studies have examined challenges and barriers to engagement in the decision-making process however uncertainty remains as to optimal methods to incorporate the views of the public in HTA decision-making. Little research has been done to ascertain whether current engagement processes align with public preferences and to what extent their desire for engagement is dependent on the question being asked by decision-makers or the characteristics of the decision. This study will examine public preferences for engagement in Australian HTA decision-making using an exploratory mixed methods design. The aims of this study are to: 1) identify characteristics about HTA decisions that are important to the public in determining whether public engagement should be undertaken on a particular topic, 2) determine which decision characteristics influence public preferences for the extent, or type of public engagement, and 3) describe reasons underpinning these preferences. Focus group participants from the general community, aged 18-70 years, will be purposively sampled from the Australian population to ensure a wide range of demographic groups. Each focus group will include a general discussion on public engagement as well as a ranking exercise using a modified nominal group technique (NGT). The NGT will inform the design of a discrete choice study to quantitatively assess public preferences for engagement in HTA decision-making. The proposed research seeks to investigate under what circumstances and how the public would like their views and preferences to be considered in health technology assessments. HTA organizations regularly make decisions about when and how public engagement should occur but without consideration of the public's preferences on the method and extent of engagement. This information has the potential to assist decision-makers in tailoring engagement approaches, and may be particularly useful in decisions with potential for conflict where clarification of public values and preferences could strengthen the decision-making process.
Muirhead, William
2012-04-01
Medical ethical analysis remains dominated by the principlist account first proposed by Beauchamp and Childress. This paper argues that the principlist model is unreflective of how ethical decisions are taken in clinical practice. Two kinds of medical ethical decisions are distinguished: biosocial ethics and clinical ethics. It is argued that principlism is an inappropriate model for clinical ethics as it is neither sufficiently action-guiding nor does it emphasise the professional integrity of the clinician. An alternative model is proposed for decision making in the realm of clinical ethics.
Ling, J; Payne, S; Connaire, K; McCarron, M
2016-01-01
Respite in children's palliative care aims to provide a break for family's from the routine of caring. Parental decision-making regarding the utilisation of out-of-home respite is dependent on many interlinking factors including the child's age, diagnosis, geographical location and the family's capacity to meet their child's care needs. A proposed model for out-of-home respite has been developed based on the findings of qualitative case study research. Utilising multiple, longitudinal, qualitative case study design, the respite needs and experiences of parents caring for a child with a life-limiting condition were explored. Multiple, in-depth interviews were undertaken with the parents identified by a hospital-based children's palliative care team. Data were analysed using thematic analysis. Each individual case consists of a whole study. Cross-case comparison was also conducted. Nine families were recruited and followed for two years. A total of 19 in-depth interviews were conducted with mothers and fathers (one or both) caring for a child with a life-limiting condition in Ireland. Each family reported vastly different needs and experiences of respite from their own unique perspective. Cross-case comparison showed that for all parents utilising respite care, regardless of their child's age and condition, home was the location of choice. Many interlinking factors influencing these decisions included: past experience of in-patient care, and trust and confidence in care providers. Issues were raised regarding the impact of care provision in the home on family life, siblings and the concept of home. Respite is an essential element of children's palliative care. Utilisation of out-of-home respite is heavily dependent on a number of interlinked and intertwined factors. The proposed model of care offers an opportunity to identify how these decisions are made and may ultimately assist in identifying the elements of responsive and family-focused respite that are important to families of children with life-limiting conditions. © 2015 John Wiley & Sons Ltd.
Ye, Jun
2016-01-01
Based on the concept of neutrosophic linguistic numbers (NLNs) in symbolic neutrosophic theory presented by Smarandache in 2015, the paper firstly proposes basic operational laws of NLNs and the expected value of a NLN to rank NLNs. Then, we propose the NLN weighted arithmetic average (NLNWAA) and NLN weighted geometric average (NLNWGA) operators and discuss their properties. Further, we establish a multiple attribute group decision-making (MAGDM) method by using the NLNWAA and NLNWGA operators under NLN environment. Finally, an illustrative example on a decision-making problem of manufacturing alternatives in the flexible manufacturing system is given to show the application of the proposed MAGDM method.
Approach of Decision Making Based on the Analytic Hierarchy Process for Urban Landscape Management
NASA Astrophysics Data System (ADS)
Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan
2013-03-01
This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.
Enhanced decision making through neuroscience
NASA Astrophysics Data System (ADS)
Szu, Harold; Jung, TP; Makeig, Scott
2012-06-01
We propose to enhance the decision making of pilot, co-pilot teams, over a range of vehicle platforms, with the aid of neuroscience. The goal is to optimize this collaborative decision making interplay in time-critical, stressful situations. We will research and measure human facial expressions, personality typing, and brainwave measurements to help answer questions related to optimum decision-making in group situations. Further, we propose to examine the nature of intuition in this decision making process. The brainwave measurements will be facilitated by a University of California, San Diego (UCSD) developed wireless Electroencephalography (EEG) sensing cap. We propose to measure brainwaves covering the whole head area with an electrode density of N=256, and yet keep within the limiting wireless bandwidth capability of m=32 readouts. This is possible because solving Independent Component Analysis (ICA) and finding the hidden brainwave sources allow us to concentrate selective measurements with an organized sparse source -->s sensing matrix [Φs], rather than the traditional purely random compressive sensing (CS) matrix[Φ].
Approach of decision making based on the analytic hierarchy process for urban landscape management.
Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan
2013-03-01
This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.
Zhang, Wenyu; Zhang, Zhenjiang
2015-01-01
Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399
An interval programming model for continuous improvement in micro-manufacturing
NASA Astrophysics Data System (ADS)
Ouyang, Linhan; Ma, Yizhong; Wang, Jianjun; Tu, Yiliu; Byun, Jai-Hyun
2018-03-01
Continuous quality improvement in micro-manufacturing processes relies on optimization strategies that relate an output performance to a set of machining parameters. However, when determining the optimal machining parameters in a micro-manufacturing process, the economics of continuous quality improvement and decision makers' preference information are typically neglected. This article proposes an economic continuous improvement strategy based on an interval programming model. The proposed strategy differs from previous studies in two ways. First, an interval programming model is proposed to measure the quality level, where decision makers' preference information is considered in order to determine the weight of location and dispersion effects. Second, the proposed strategy is a more flexible approach since it considers the trade-off between the quality level and the associated costs, and leaves engineers a larger decision space through adjusting the quality level. The proposed strategy is compared with its conventional counterparts using an Nd:YLF laser beam micro-drilling process.
Zero-block mode decision algorithm for H.264/AVC.
Lee, Yu-Ming; Lin, Yinyi
2009-03-01
In the previous paper , we proposed a zero-block intermode decision algorithm for H.264 video coding based upon the number of zero-blocks of 4 x 4 DCT coefficients between the current macroblock and the co-located macroblock. The proposed algorithm can achieve significant improvement in computation, but the computation performance is limited for high bit-rate coding. To improve computation efficiency, in this paper, we suggest an enhanced zero-block decision algorithm, which uses an early zero-block detection method to compute the number of zero-blocks instead of direct DCT and quantization (DCT/Q) calculation and incorporates two adequate decision methods into semi-stationary and nonstationary regions of a video sequence. In addition, the zero-block decision algorithm is also applied to the intramode prediction in the P frame. The enhanced zero-block decision algorithm brings out a reduction of average 27% of total encoding time compared to the zero-block decision algorithm.
Decisions Concerning Directional Dependence
ERIC Educational Resources Information Center
von Eye, Alexander; DeShon, Richard P.
2012-01-01
In this rejoinder, von Eye and DeShon discuss the decision strategies proposed in their original article ("Directional Dependence in Developmental Research," this issue), as well as the ones proposed by the authors of the commentary (Pornprasertmanit and Little, "Determining Directional Dependency in Causal Associations," this issue). In addition,…
A conceptual and computational model of moral decision making in human and artificial agents.
Wallach, Wendell; Franklin, Stan; Allen, Colin
2010-07-01
Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors. Copyright © 2010 Cognitive Science Society, Inc.
Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks
Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu
2015-01-01
Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908
Code of Federal Regulations, 2014 CFR
2014-04-01
... 25 Indians 2 2014-04-01 2014-04-01 false How do I appeal a notice of violation, proposed civil fine assessment, order of temporary closure, the Chair's decision to void or modify a management contract, the Commission's proposal to remove a certificate of self-regulation, the Chair's decision to approve or object to a tribal gaming regulatory...
Code of Federal Regulations, 2014 CFR
2014-04-01
... 25 Indians 2 2014-04-01 2014-04-01 false How do I appeal a notice of violation, proposed civil fine assessment, order of temporary closure, the Chair's decision to void or modify a management contract, the Commission's proposal to remove a certificate of self regulation, the Chair's decision to approve or object to a tribal gaming regulatory...
Epidemiology of dental professional liability.
Montagna, F; Cortesini, C; Manca, R; Montagna, L; Piras, A; Manfredini, D
2011-04-01
The aim of this article is to collect data relating to dental professional liability in Italy and provide a common platform for discussions among clinicians, legal medicine practitioners, and experts in law. On the basis of two different dental-legal statistical samples (1,670 reports of legal dental experts and 320 civil court decisions) we analyzed the dental professional liability lawsuit in the areas of distribution of lawsuits among the different dental specialties, recurrence and type of errors, outcome of civil suits, parameters of compensation. Some ideas are also proposed for possible strategies in the management of clinical risk (prevention of errors) and court proceedings.
Analysis and Modeling of Ground Operations at Hub Airports
NASA Technical Reports Server (NTRS)
Atkins, Stephen (Technical Monitor); Andersson, Kari; Carr, Francis; Feron, Eric; Hall, William D.
2000-01-01
Building simple and accurate models of hub airports can considerably help one understand airport dynamics, and may provide quantitative estimates of operational airport improvements. In this paper, three models are proposed to capture the dynamics of busy hub airport operations. Two simple queuing models are introduced to capture the taxi-out and taxi-in processes. An integer programming model aimed at representing airline decision-making attempts to capture the dynamics of the aircraft turnaround process. These models can be applied for predictive purposes. They may also be used to evaluate control strategies for improving overall airport efficiency.
Electronic labelling in recycling of manufactured articles.
Olejnik, Lech; Krammer, Alfred
2002-12-01
The concept of a recycling system aiming at the recovery of resources from manufactured articles is proposed. The system integrates electronic labels for product identification and internet for global data exchange. A prototype for the recycling of electric motors has been developed, which implements a condition-based recycling decision system to automatically select the environmentally and economically appropriate recycling strategy, thereby opening a potential market for second-hand motors and creating a profitable recycling process itself. The project has been designed to evaluate the feasibility of electronic identification applied on a large number of motors and to validate the system in real field conditions.
USDA-ARS?s Scientific Manuscript database
A new expanded digital resource exists for tracking decisions on all nomenclature proposals potentially contributing to Appendices II-VIII of the International Code of Nomenclature. This system owes its origins to the Smithsonian Institution's Proposals and Disposals website created by Dan Nicolson ...
Performance Evaluation of Multimodal Multifeature Authentication System Using KNN Classification.
Rajagopal, Gayathri; Palaniswamy, Ramamoorthy
2015-01-01
This research proposes a multimodal multifeature biometric system for human recognition using two traits, that is, palmprint and iris. The purpose of this research is to analyse integration of multimodal and multifeature biometric system using feature level fusion to achieve better performance. The main aim of the proposed system is to increase the recognition accuracy using feature level fusion. The features at the feature level fusion are raw biometric data which contains rich information when compared to decision and matching score level fusion. Hence information fused at the feature level is expected to obtain improved recognition accuracy. However, information fused at feature level has the problem of curse in dimensionality; here PCA (principal component analysis) is used to diminish the dimensionality of the feature sets as they are high dimensional. The proposed multimodal results were compared with other multimodal and monomodal approaches. Out of these comparisons, the multimodal multifeature palmprint iris fusion offers significant improvements in the accuracy of the suggested multimodal biometric system. The proposed algorithm is tested using created virtual multimodal database using UPOL iris database and PolyU palmprint database.
Performance Evaluation of Multimodal Multifeature Authentication System Using KNN Classification
Rajagopal, Gayathri; Palaniswamy, Ramamoorthy
2015-01-01
This research proposes a multimodal multifeature biometric system for human recognition using two traits, that is, palmprint and iris. The purpose of this research is to analyse integration of multimodal and multifeature biometric system using feature level fusion to achieve better performance. The main aim of the proposed system is to increase the recognition accuracy using feature level fusion. The features at the feature level fusion are raw biometric data which contains rich information when compared to decision and matching score level fusion. Hence information fused at the feature level is expected to obtain improved recognition accuracy. However, information fused at feature level has the problem of curse in dimensionality; here PCA (principal component analysis) is used to diminish the dimensionality of the feature sets as they are high dimensional. The proposed multimodal results were compared with other multimodal and monomodal approaches. Out of these comparisons, the multimodal multifeature palmprint iris fusion offers significant improvements in the accuracy of the suggested multimodal biometric system. The proposed algorithm is tested using created virtual multimodal database using UPOL iris database and PolyU palmprint database. PMID:26640813
Pieterse, Arwen H; de Vries, Marieke; Kunneman, Marleen; Stiggelbout, Anne M; Feldman-Stewart, Deb
2013-01-01
Healthcare decisions, particularly those involving weighing benefits and harms that may significantly affect quality and/or length of life, should reflect patients' preferences. To support patients in making choices, patient decision aids and values clarification methods (VCM) in particular have been developed. VCM intend to help patients to determine the aspects of the choices that are important to their selection of a preferred option. Several types of VCM exist. However, they are often designed without clear reference to theory, which makes it difficult for their development to be systematic and internally coherent. Our goal was to provide theory-informed recommendations for the design of VCM. Process theories of decision making specify components of decision processes, thus, identify particular processes that VCM could aim to facilitate. We conducted a review of the MEDLINE and PsycINFO databases and of references to theories included in retrieved papers, to identify process theories of decision making. We selected a theory if (a) it fulfilled criteria for a process theory; (b) provided a coherent description of the whole process of decision making; and (c) empirical evidence supports at least some of its postulates. Four theories met our criteria: Image Theory, Differentiation and Consolidation theory, Parallel Constraint Satisfaction theory, and Fuzzy-trace Theory. Based on these, we propose that VCM should: help optimize mental representations; encourage considering all potentially appropriate options; delay selection of an initially favoured option; facilitate the retrieval of relevant values from memory; facilitate the comparison of options and their attributes; and offer time to decide. In conclusion, our theory-based design recommendations are explicit and transparent, providing an opportunity to test each in a systematic manner. Copyright © 2012 Elsevier Ltd. All rights reserved.
Woudstra, Anke J; Timmermans, Daniëlle R M; Uiters, Ellen; Dekker, Evelien; Smets, Ellen M A; Fransen, Mirjam P
2018-06-01
The process of informed decision making (IDM) requires an adequate level of health literacy. To ensure that all individuals have equal opportunity to make an informed decision in colorectal cancer (CRC) screening, it is essential to gain more insight into which health literacy skills are needed for IDM. Our aims were (i) to explore how individuals make a decision about CRC screening and (ii) to explore which skills are needed for IDM in CRC screening and (iii) to integrate these findings within a conceptual framework. We conducted 3 focus groups with individuals eligible for CRC screening (n = 22) and 2 focus groups with experts in the field of health literacy, oncology and decision making, including scientific researchers and health-care professionals (n = 17). We used framework analysis to analyse our data. We identified and specified ten health literacy skills, which varied from the ability to read and understand CRC screening information to the ability to weigh up pros and cons of screening for personal relevance. The skills were linked to 8 decision-making stages in CRC screening within a conceptual framework. We found differences in perceptions between screening invitees and experts, especially in the perceived importance of CRC screening information for IDM. This study provides insight into the decision-making stages and health literacy skills that are essential for IDM in CRC screening. The proposed conceptual framework can be used to inform the development of context-based measurement of health literacy and interventions to support IDM in cancer screening. © 2017 The Authors Health Expectations published by John Wiley & Sons Ltd.
Wong, Carlos King Ho; Wu, Olivia; Cheung, Bernard M Y
2018-02-01
The aim of this article is to describe the process, evaluation criteria, and possible outcomes of decision-making for new drugs listed in the Hong Kong Hospital Authority Drug Formulary in comparison to the health technology assessment (HTA) policy overseas. Details of decision-making processes including the new drug listing submission, Drug Advisory Committee (DAC) meeting, and procedures prior to and following the meeting, were extracted from the official Hong Kong Hospital Authority drug formulary management website and manual. Publicly-available information related to the new drug decision-making process for five HTA agencies [the National Institute of Health and Care Excellence (NICE), the Scottish Medicines Consortium (SMC), the Australia Pharmaceutical Benefits Advisory Committee (PBAC), the Canadian Agency for Drugs and Technologies in Health (CADTH), and the New Zealand Pharmaceutical Management Agency (PHARMAC)] were reviewed and retrieved from official documents from public domains. The DAC is in charge of systemically and critically appraising new drugs before they are listed on the formulary, reviewing submitted applications, and making the decision to list the drug based on scientific evidence to which safety, efficacy, and cost-effectiveness are the primary considerations. When compared with other HTA agencies, transparency of the decision-making process of the DAC, the relevance of clinical and health economic evidence, and the lack of health economic and methodological input of submissions are the major challenges to the new-drug listing policy in Hong Kong. Despite these challenges, this review provides suggestions for the establishment of a more transparent, credible, and evidence-based decision-making process in the Hong Kong Hospital Authority Drug Formulary. Proposals for improvement in the listing of new drugs in the formulary should be a priority of healthcare reforms.
Tsoi, B; O'Reilly, D; Jegathisawaran, J; Tarride, J-E; Blackhouse, G; Goeree, R
2015-06-17
In constructing or appraising a health economic model, an early consideration is whether the modelling approach selected is appropriate for the given decision problem. Frameworks and taxonomies that distinguish between modelling approaches can help make this decision more systematic and this study aims to identify and compare the decision frameworks proposed to date on this topic area. A systematic review was conducted to identify frameworks from peer-reviewed and grey literature sources. The following databases were searched: OVID Medline and EMBASE; Wiley's Cochrane Library and Health Economic Evaluation Database; PubMed; and ProQuest. Eight decision frameworks were identified, each focused on a different set of modelling approaches and employing a different collection of selection criterion. The selection criteria can be categorized as either: (i) structural features (i.e. technical elements that are factual in nature) or (ii) practical considerations (i.e. context-dependent attributes). The most commonly mentioned structural features were population resolution (i.e. aggregate vs. individual) and interactivity (i.e. static vs. dynamic). Furthermore, understanding the needs of the end-users and stakeholders was frequently incorporated as a criterion within these frameworks. There is presently no universally-accepted framework for selecting an economic modelling approach. Rather, each highlights different criteria that may be of importance when determining whether a modelling approach is appropriate. Further discussion is thus necessary as the modelling approach selected will impact the validity of the underlying economic model and have downstream implications on its efficiency, transparency and relevance to decision-makers.
The role of justice in team member satisfaction with the leader and attachment to the team.
Phillips, J M; Douthitt, E A; Hyland, M M
2001-04-01
This study examined the effects of team decision accuracy, team member decision influence, leader consideration behaviors, and justice perceptions on staff members' satisfaction with the leader and attachment to the team in hierarchical decision-making teams. The authors proposed that staff members' justice perceptions would mediate the relationship between (a) team decision accuracy, (b) the amount of influence a staff member has in the team leader's decision, and (c) the leader's consideration behaviors and staff attachment to the team and satisfaction with the leader. The results of an experiment involving 128 participants in a total of 64 teams, who made recommendations to a confederate acting as the team leader, generally support the proposed model.
Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar
2017-03-01
In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.
NASA Astrophysics Data System (ADS)
Chiadamrong, N.; Piyathanavong, V.
2017-12-01
Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.
Medical photography: principles for orthopedics.
Uzun, Metin; Bülbül, Murat; Toker, Serdar; Beksaç, Burak; Kara, Adnan
2014-04-05
Medical photography is used clinically for patient evaluation, treatment decisions, and scientific documentation. Although standards for medical photography exist in many branches of medicine, we have not encountered such criteria in publications in the area of orthopedics. This study aims to (1) assess the quality of medical images used in an orthopedic publication and (2) to propose standards for medical photography in this area. Clinical photographs were reviewed from all issues of a journal published between the years 2008 and 2012. A quality of clinical images was developed based on the criteria published for the specialties of dermatology and cosmetic surgery. All images were reviewed on the appropriateness of background, patient preparation, and technique. In this study, only 44.9% of clinical images in an orthopedic publication adhered to the proposed conventions. Standards have not been established for medical photography in orthopedics as in other specialty areas. Our results suggest that photographic clinical information in orthopedic publications may be limited by inadequate presentation. We propose that formal conventions for clinical images should be established.
Behavior Knowledge Space-Based Fusion for Copy-Move Forgery Detection.
Ferreira, Anselmo; Felipussi, Siovani C; Alfaro, Carlos; Fonseca, Pablo; Vargas-Munoz, John E; Dos Santos, Jefersson A; Rocha, Anderson
2016-07-20
The detection of copy-move image tampering is of paramount importance nowadays, mainly due to its potential use for misleading the opinion forming process of the general public. In this paper, we go beyond traditional forgery detectors and aim at combining different properties of copy-move detection approaches by modeling the problem on a multiscale behavior knowledge space, which encodes the output combinations of different techniques as a priori probabilities considering multiple scales of the training data. Afterwards, the conditional probabilities missing entries are properly estimated through generative models applied on the existing training data. Finally, we propose different techniques that exploit the multi-directionality of the data to generate the final outcome detection map in a machine learning decision-making fashion. Experimental results on complex datasets, comparing the proposed techniques with a gamut of copy-move detection approaches and other fusion methodologies in the literature show the effectiveness of the proposed method and its suitability for real-world applications.
Giannoli, Jean-Marc; Szymanowicz, Anton
2011-01-01
We propose a set of recommendations and practices to optimize the use of quality control of medical biology examinations. The fundamentals are reviewed: definition of a series of analysis, IQC at one or more level, Westgard alert rules and rejection, practical remedial actions to take for the technician, corrective and preventive actions to be implemented by the biologist. We have also formalized three flowcharts to guide the technician in their daily practice to ensure analytical quality of investigations carried out. These decision trees are the result of the experience submitted by an accredited and professional laboratory attentive to the ongoing improvement of IQC. This article can provide useful assistance to biologists for accreditation but also aims to foster collaboration reliable medical biology laboratory at the appropriate management of patients.
Gådin, Katja Gillander; Weiner, Gaby; Ahlgren, Christina
2009-12-01
The aim was to analyse if young students could be substantive participants in a health-promoting school project. The specific aims were to analyse the changes the students proposed in their school environment, how these changes were prioritized by a school health committee and to discuss the students' proposals and the changes from a health and gender perspective. An intervention project was carried out in an elementary school with students (about 150) in Grades 1 through 6. The intervention included small-group discussions about health promoting factors, following a health education model referred to as "It's your decision." At the last of 6 discussions, the students made suggestions for health-promoting changes in their school environment. A health committee was established with students and staff for the purpose of initiating changes based on the proposals. A content analysis was used to analyse the proposals and the protocols developed by the health committee. The analysis showed 6 categories of the students' proposals: social climate, influence on schoolwork, structure and orderliness, security, physical environment and food for well-being. Their priorities corresponded to the students' categories, but had an additional category regarding health education. Principles that guide promoting good health in schools can be put into action among students as young as those in Grades 1 through 6. Future challenges include how to convey experiences and knowledge to other schools and how to evaluate if inequalities in health because of gender, class and ethnicity can be reduced through the focus on empowerment and participation.
Code of Federal Regulations, 2010 CFR
2010-10-01
... after the time allowed for presenting proposed findings and conclusions, the administrative law judge... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Findings and conclusions; decision by... Findings and conclusions; decision by administrative law judge; submission to Board for decision. (a) At...
43 CFR 2450.4 - Protests: Initial classification decision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Protests: Initial classification decision... CLASSIFICATION SYSTEM Petition-Application Procedures § 2450.4 Protests: Initial classification decision. (a) For a period of 30 days after the proposed classification decision has been served upon the parties...
36 CFR 220.4 - General requirements.
Code of Federal Regulations, 2010 CFR
2010-07-01
... agency decisionmaking by: (1) Completing the environmental document review before making a decision on...(s) before rendering a decision on the proposal; and (5) Making a decision encompassed within the... preparing to make a decision on one or more alternative means of accomplishing that goal and the effects can...
The breakdown of coordinated decision making in distributed systems.
Bearman, Christopher; Paletz, Susannah B F; Orasanu, Judith; Thomas, Matthew J W
2010-04-01
This article aims to explore the nature and resolution of breakdowns in coordinated decision making in distributed safety-critical systems. In safety-critical domains, people with different roles and responsibilities often must work together to make coordinated decisions while geographically distributed. Although there is likely to be a large degree of overlap in the shared mental models of these people on the basis of procedures and experience, subtle differences may exist. Study 1 involves using Aviation Safety Reporting System reports to explore the ways in which coordinated decision making breaks down between pilots and air traffic controllers and the way in which the breakdowns are resolved. Study 2 replicates and extends those findings with the use of transcripts from the Apollo 13 National Aeronautics and Space Administration space mission. Across both studies, breakdowns were caused in part by different types of lower-level breakdowns (or disconnects), which are labeled as operational, informational, or evaluative. Evaluative disconnects were found to be significantly harder to resolve than other types of disconnects. Considering breakdowns according to the type of disconnect involved appears to capture useful information that should assist accident and incident investigators. The current trend in aviation of shifting responsibilities and providing increasingly more information to pilots may have a hidden cost of increasing evaluative disconnects. The proposed taxonomy facilitates the investigation of breakdowns in coordinated decision making and draws attention to the importance of considering subtle differences between participants' mental models when considering complex distributed systems.
Motivation and effort in individuals with social anhedonia
McCarthy, Julie M.; Treadway, Michael T.; Blanchard, Jack J.
2015-01-01
It has been proposed that anhedonia may, in part, reflect difficulties in reward processing and effortful decision-making. The current study aimed to replicate previous findings of effortful decision-making deficits associated with elevated anhedonia and expand upon these findings by investigating whether these decision-making deficits are specific to elevated social anhedonia or are also associated with elevated positive schizotypy characteristics. The current study compared controls (n = 40) to individuals elevated on social anhedonia (n = 30), and individuals elevated on perceptual aberration/magical ideation (n = 30) on the Effort Expenditure for Rewards Task (EEfRT). Across groups, participants chose a higher proportion of hard tasks with increasing probability of reward and reward magnitude, demonstrating sensitivity to probability and reward values. Contrary to our expectations, when the probability of reward was most uncertain (50% probability), at low and medium reward values, the social anhedonia group demonstrated more effortful decision-making than either individuals high in positive schizotypy or controls. The positive schizotypy group only differed from controls (making less effortful choices than controls) when reward probability was lowest (12%) and the magnitude of reward was the smallest. Our results suggest that social anhedonia is related to intact motivation and effort for monetary rewards, but that individuals with this characteristic display a unique and perhaps inefficient pattern of effort allocation when the probability of reward is most uncertain. Future research is needed to better understand effortful decision-making and the processing of reward across a range of individual difference characteristics. PMID:25888337
Parental Moral Distress and Moral Schism in the Neonatal ICU.
Foe, Gabriella; Hellmann, Jonathan; Greenberg, Rebecca A
2018-05-25
Ethical dilemmas in critical care may cause healthcare practitioners to experience moral distress: incoherence between what one believes to be best and what occurs. Given that paediatric decision-making typically involves parents, we propose that parents can also experience moral distress when faced with making value-laden decisions in the neonatal intensive care unit. We propose a new concept-that parents may experience "moral schism"-a genuine uncertainty regarding a value-based decision that is accompanied by emotional distress. Schism, unlike moral distress, is not caused by barriers to making and executing a decision that is deemed to be best by the decision-makers but rather an encounter of significant internal struggle. We explore factors that appear to contribute to both moral distress and "moral schism" for parents: the degree of available support, a sense of coherence of the situation, and a sense of responsibility. We propose that moral schism is an underappreciated concept that needs to be explicated and may be more prevalent than moral distress when exploring decision-making experiences for parents. We also suggest actions of healthcare providers that may help minimize parental "moral schism" and moral distress.
Audenet, F; Lejay, V; Mejean, A; De La Taille, A; Abbou, C-C; Lebret, T; Botto, H; Bitker, M-O; Roupret, M
2012-06-01
One of the priorities of the "Plan against the Cancer" in France is to ensure the discussion of all cancer cases in a multidisciplinary meeting staff (RCP). The multidisciplinary collaboration is proposed to guarantee a discussion between specialists in every cases, particularly in complex cases. The aim of this study was to compare the therapeutic decision taken in four RCP in Paris Île-de-France academic centres for three identical cases. Three cases of urological oncology (prostate cancer [PCa], renal cell carcinoma [RCC] and bladder tumour) were selected by a single urologist, not involved in further discussion. These cases were blindly presented in four academic urology department from Paris: Pitié-Salpêtrière Hospital, Mondor Hospital, the Georges-Pompidou European Hospital and Foch Hospital. The four centres met the criteria of quality of RCP in terms of multidisciplinarity, frequency and standardization. The therapeutic suggestions were similar in the RCC cases, there were differences in the surgical approaches and preoperative work-up in the PCa case and, lastly, the proposals were different for the bladder cancer case. The decisions relies on clinical data and preoperative work-up but also on the experience and habits of the centre of excellence. For complex cases that does not fit with current guidelines, the panel discussion can lead to different therapeutic options from a centre to another and is largely influenced by the local organisation of the RCP. Copyright © 2012 Elsevier Masson SAS. All rights reserved.
NASA Astrophysics Data System (ADS)
Gonzales, Patricia; Ajami, Newsha; Sun, Yujie
2017-09-01
Water utilities are increasingly relying on water efficiency and conservation to extend the availability of supplies. Despite spatial and institutional interdependency of many utilities, these demand-side management initiatives have traditionally been tackled by individual utilities operating in isolation. In this study, we introduce a policy framework for water conservation credits that enables collaboration at the regional scale. Under the proposed approach, utilities have the flexibility to invest in water conservation measures that are appropriate for their specific service area. When utilities have insufficient capacity for local cost-effective measures, they may opt to purchase credits, contributing to fund subsidies for utilities that do have that capacity and can provide the credits, while the region as a whole benefits from more reliable water supplies. This work aims to provide insights on the potential impacts of a water conservation credit policy framework when utilities are given the option to collaborate in their efforts. We model utility decisions as rational cost-minimizing actors subject to different decision-making dynamics and water demand scenarios, and demonstrate the institutional characteristics needed for the proposed policy to be effective. We apply this model to a counterfactual case study of water utility members of the Bay Area Water Supply and Conservation Agency in California during the drought period of June 2015 to May 2016. Our scenario analysis indicates that when the institutional structure and incentives are appropriately defined, water agencies can achieve economic benefits from collaborating in their conservation efforts, especially if they coordinate more closely in their decision-making.
Gascón, Fernando; de la Fuente, David; Puente, Javier; Lozano, Jesús
2007-11-01
The aim of this paper is to develop a methodology that is useful for analyzing, from a macroeconomic perspective, the aggregate demand and the aggregate supply features of the market of pharmaceutical generics. In order to determine the potential consumption and the potential production of pharmaceutical generics in different countries, two fuzzy decision support systems are proposed. Two fuzzy decision support systems, both based on the Mamdani model, were applied in this paper. These systems, generated by Matlab Toolbox 'Fuzzy' (v. 2.0), are able to determine the potential of a country for the manufacturing or the consumption of pharmaceutical generics. The systems make use of three macroeconomic input variables. In an empirical application of our proposed methodology, the potential towards consumption and manufacturing in Holland, Sweden, Italy and Spain has been estimated from national indicators. Cross-country comparisons are made and graphical surfaces are analyzed in order to interpret the results. The main contribution of this work is the development of a methodology that is useful for analyzing aggregate demand and aggregate supply characteristics of pharmaceutical generics. The methodology is valid for carrying out a systematic analysis of the potential generics have at a macrolevel in different countries. The main advantages of the use of fuzzy decision support systems in the context of pharmaceutical generics are the flexibility in the construction of the system, the speed in interpreting the results offered by the inference and surface maps and the ease with which a sensitivity analysis of the potential behavior of a given country may be performed.
NASA Astrophysics Data System (ADS)
Liu, Bingsheng; Fu, Meiqing; Zhang, Shuibo; Xue, Bin; Zhou, Qi; Zhang, Shiruo
2018-01-01
The Choquet integral (IL) operator is an effective approach for handling interdependence among decision attributes in complex decision-making problems. However, the fuzzy measures of attributes and attribute sets required by IL are difficult to achieve directly, which limits the application of IL. This paper proposes a new method for determining fuzzy measures of attributes by extending Marichal's concept of entropy for fuzzy measure. To well represent the assessment information, interval-valued 2-tuple linguistic context is utilised to represent information. Then, we propose a Choquet integral operator in an interval-valued 2-tuple linguistic environment, which can effectively handle the correlation between attributes. In addition, we apply these methods to solve multi-attribute group decision-making problems. The feasibility and validity of the proposed operator is demonstrated by comparisons with other models in illustrative example part.
A Decision Support System for Evaluating and Selecting Information Systems Projects
NASA Astrophysics Data System (ADS)
Deng, Hepu; Wibowo, Santoso
2009-01-01
This chapter presents a decision support system (DSS) for effectively solving the information systems (IS) project selection problem. The proposed DSS recognizes the multidimensional nature of the IS project selection problem, the availability of multicriteria analysis (MA) methods, and the preferences of the decision-maker (DM) on the use of specific MA methods in a given situation. A knowledge base consisting of IF-THEN production rules is developed for assisting the DM with a systematic adoption of the most appropriate method with the efficient use of the powerful reasoning and explanation capabilities of intelligent DSS. The idea of letting the problem to be solved determines the method to be used is incorporated into the proposed DSS. As a result, effective decisions can be made for solving the IS project selection problem. An example is presented to demonstrate the applicability of the proposed DSS for solving the problem of selecting IS projects in real world situations.
The Relations between Decision Making in Social Relationships and Decision Making Styles
ERIC Educational Resources Information Center
Sari, Enver
2008-01-01
The research reported in this paper aimed to examine the relationships between decisiveness in social relationships, and the decision-making styles of a group of university students and to investigate the contributions of decision-making styles in predicting decisiveness in social relationship (conflict resolution, social relationship selection…
NASA Astrophysics Data System (ADS)
Yu, Yang; Zeng, Zheng
2009-10-01
By discussing the causes behind the high amendments ratio in the implementation of urban regulatory detailed plans in China despite its law-ensured status, the study aims to reconcile conflict between the legal authority of regulatory detailed planning and the insufficient scientific support in its decision-making and compilation by introducing into the process spatial analysis based on GIS technology and 3D modeling thus present a more scientific and flexible approach to regulatory detailed planning in China. The study first points out that the current compilation process of urban regulatory detailed plan in China employs mainly an empirical approach which renders it constantly subjected to amendments; the study then discusses the need and current utilization of GIS in the Chinese system and proposes the framework of a GIS-assisted 3D spatial analysis process from the designer's perspective which can be regarded as an alternating processes between the descriptive codes and physical design in the compilation of regulatory detailed planning. With a case study of the processes and results from the application of the framework, the paper concludes that the proposed framework can be an effective instrument which provides more rationality, flexibility and thus more efficiency to the compilation and decision-making process of urban regulatory detailed plan in China.
Ferrández-Pastor, Francisco Javier; García-Chamizo, Juan Manuel; Nieto-Hidalgo, Mario; Mora-Martínez, José
2018-05-28
The Internet of Things (IoT) has opened productive ways to cultivate soil with the use of low-cost hardware (sensors/actuators) and communication (Internet) technologies. Remote equipment and crop monitoring, predictive analytic, weather forecasting for crops or smart logistics and warehousing are some examples of these new opportunities. Nevertheless, farmers are agriculture experts but, usually, do not have experience in IoT applications. Users who use IoT applications must participate in its design, improving the integration and use. In this work, different industrial agricultural facilities are analysed with farmers and growers to design new functionalities based on IoT paradigms deployment. User-centred design model is used to obtain knowledge and experience in the process of introducing technology in agricultural applications. Internet of things paradigms are used as resources to facilitate the decision making. IoT architecture, operating rules and smart processes are implemented using a distributed model based on edge and fog computing paradigms. A communication architecture is proposed using these technologies. The aim is to help farmers to develop smart systems both, in current and new facilities. Different decision trees to automate the installation, designed by the farmer, can be easily deployed using the method proposed in this document.
Capacitated location of collection sites in an urban waste management system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ghiani, Gianpaolo, E-mail: gianpaolo.ghiani@unisalento.it; Itaca S.r.l., via P. Bucci 41C, 87036 Rende; Lagana, Demetrio, E-mail: dlagana@deis.unical.it
2012-07-15
Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the location of waste collection sites. In this paper, we propose an integer programming model that helps decision makers in choosing the sites where to locate the unsorted waste collection bins in a residential town, as well as the capacities of the bins to be located at each collection site. This model helps in assessing tactical decisions through constraints that forcemore » each collection area to be capacitated enough to fit the expected waste to be directed to that area, while taking into account Quality of Service constraints from the citizens' point of view. Moreover, we propose an effective constructive heuristic approach whose aim is to provide a good solution quality in an extremely reduced computational time. Computational results on data related to the city of Nardo, in the south of Italy, show that both exact and heuristic approaches provide consistently better solutions than that currently implemented, resulting in a lower number of activated collection sites, and a lower number of bins to be used.« less
Si, Guangsen; Xu, Zeshui
2018-01-01
Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers’ subjective cognition. In general, different decision-makers’ sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method. PMID:29614019
Liao, Huchang; Si, Guangsen; Xu, Zeshui; Fujita, Hamido
2018-04-03
Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers' subjective cognition. In general, different decision-makers' sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method.
Control, Contingency and Delegation in Decision-Making.
ERIC Educational Resources Information Center
Michael, Stephen R.
1979-01-01
Proposes a model which emphasizes the delegation of decision-making authority and managerial control of operations. Suggests that risks can be reduced by using (1) a contingency approach to delegation, (2) decision rules for consistency, (3) decision models for specific situations, (4) vital indicator reports, (5) management by objectives, and (6)…
Research on web-based decision support system for sports competitions
NASA Astrophysics Data System (ADS)
Huo, Hanqiang
2010-07-01
This paper describes the system architecture and implementation technology of the decision support system for sports competitions, discusses the design of decision-making modules, management modules and security of the system, and proposes the development idea of building a web-based decision support system for sports competitions.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-11-15
...-FXES11170900000-B3] Proposed Information Collection; Policy for Evaluation of Conservation Efforts When Making... under the ESA. The Policy for Evaluation of Conservation Efforts When Making Listing Decisions (PECE... contributes to forming a basis for making a decision about the listing of a species. PECE applies to...
You, Hongzhi; Wang, Da-Hui
2017-01-01
Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913
You, Hongzhi; Wang, Da-Hui
2017-01-01
Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.
Liu, Jie; Guo, Liang; Jiang, Jiping; Jiang, Dexun; Wang, Peng
2018-04-13
Aiming to minimize the damage caused by river chemical spills, efficient emergency material allocation is critical for an actual emergency rescue decision-making in a quick response. In this study, an emergency material allocation framework based on time-varying supply-demand constraint is developed to allocate emergency material, minimize the emergency response time, and satisfy the dynamic emergency material requirements in post-accident phases dealing with river chemical spills. In this study, the theoretically critical emergency response time is firstly obtained for the emergency material allocation system to select a series of appropriate emergency material warehouses as potential supportive centers. Then, an enumeration method is applied to identify the practically critical emergency response time, the optimum emergency material allocation and replenishment scheme. Finally, the developed framework is applied to a computational experiment based on south-to-north water transfer project in China. The results illustrate that the proposed methodology is a simple and flexible tool for appropriately allocating emergency material to satisfy time-dynamic demands during emergency decision-making. Therefore, the decision-makers can identify an appropriate emergency material allocation scheme in a balance between time-effective and cost-effective objectives under the different emergency pollution conditions.
NASA Astrophysics Data System (ADS)
Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie; Chang, Kyung Hwan
2018-01-01
The aim of this study was to derive a new plan-scoring index using normal tissue complication probabilities to verify different plans in the selection of personalized treatment. Plans for 12 patients treated with tomotherapy were used to compare scoring for ranking. Dosimetric and biological indexes were analyzed for the plans for a clearly distinguishable group ( n = 7) and a similar group ( n = 12), using treatment plan verification software that we developed. The quality factor ( QF) of our support software for treatment decisions was consistent with the final treatment plan for the clearly distinguishable group (average QF = 1.202, 100% match rate, n = 7) and the similar group (average QF = 1.058, 33% match rate, n = 12). Therefore, we propose a normal tissue complication probability (NTCP) based on the plan scoring index for verification of different plans for personalized treatment-plan selection. Scoring using the new QF showed a 100% match rate (average NTCP QF = 1.0420). The NTCP-based new QF scoring method was adequate for obtaining biological verification quality and organ risk saving using the treatment-planning decision-support software we developed for prostate cancer.
Predicting species distributions for conservation decisions
Guisan, Antoine; Tingley, Reid; Baumgartner, John B; Naujokaitis-Lewis, Ilona; Sutcliffe, Patricia R; Tulloch, Ayesha I T; Regan, Tracey J; Brotons, Lluis; McDonald-Madden, Eve; Mantyka-Pringle, Chrystal; Martin, Tara G; Rhodes, Jonathan R; Maggini, Ramona; Setterfield, Samantha A; Elith, Jane; Schwartz, Mark W; Wintle, Brendan A; Broennimann, Olivier; Austin, Mike; Ferrier, Simon; Kearney, Michael R; Possingham, Hugh P; Buckley, Yvonne M
2013-01-01
Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. PMID:24134332
Hesitant Fuzzy Thermodynamic Method for Emergency Decision Making Based on Prospect Theory.
Ren, Peijia; Xu, Zeshui; Hao, Zhinan
2017-09-01
Due to the timeliness of emergency response and much unknown information in emergency situations, this paper proposes a method to deal with the emergency decision making, which can comprehensively reflect the emergency decision making process. By utilizing the hesitant fuzzy elements to represent the fuzziness of the objects and the hesitant thought of the experts, this paper introduces the negative exponential function into the prospect theory so as to portray the psychological behaviors of the experts, which transforms the hesitant fuzzy decision matrix into the hesitant fuzzy prospect decision matrix (HFPDM) according to the expectation-levels. Then, this paper applies the energy and the entropy in thermodynamics to take the quantity and the quality of the decision values into account, and defines the thermodynamic decision making parameters based on the HFPDM. Accordingly, a whole procedure for emergency decision making is conducted. What is more, some experiments are designed to demonstrate and improve the validation of the emergency decision making procedure. Last but not the least, this paper makes a case study about the emergency decision making in the firing and exploding at Port Group in Tianjin Binhai New Area, which manifests the effectiveness and practicability of the proposed method.
Cost-benefit decision circuitry: proposed modulatory role for acetylcholine.
Fobbs, Wambura C; Mizumori, Sheri J Y
2014-01-01
In order to select which action should be taken, an animal must weigh the costs and benefits of possible outcomes associate with each action. Such decisions, called cost-benefit decisions, likely involve several cognitive processes (including memory) and a vast neural circuitry. Rodent models have allowed research to begin to probe the neural basis of three forms of cost-benefit decision making: effort-, delay-, and risk-based decision making. In this review, we detail the current understanding of the functional circuits that subserve each form of decision making. We highlight the extensive literature by detailing the ability of dopamine to influence decisions by modulating structures within these circuits. Since acetylcholine projects to all of the same important structures, we propose several ways in which the cholinergic system may play a local modulatory role that will allow it to shape these behaviors. A greater understanding of the contribution of the cholinergic system to cost-benefit decisions will permit us to better link the decision and memory processes, and this will help us to better understand and/or treat individuals with deficits in a number of higher cognitive functions including decision making, learning, memory, and language. © 2014 Elsevier Inc. All rights reserved.
Adamkovič, Matúš; Martončik, Marcel
2017-01-01
This review focuses on the issue of poverty affecting economic decision-making. By critically evaluating existing studies, the authors propose a structural model detailing the cognitive mechanism involved in how poverty negatively impacts economic decision-making, and explores evidence supporting the basis for the formation of this model. The suggested mechanism consists of a relationship between poverty and four other factors: (1) cognitive load (e.g., experiencing negative affect and stress); (2) executive functions (e.g., attention, working memory, and self-control); (3) intuition/deliberation in decision-making; and (4) economic decision-making (e.g., time-discounting and risk preference), with a final addition of financial literacy as a covariate. This paper focuses on shortfalls in published research, and delves further into the proposed model.
One lens optical correlation: application to face recognition.
Jridi, Maher; Napoléon, Thibault; Alfalou, Ayman
2018-03-20
Despite its extensive use, the traditional 4f Vander Lugt Correlator optical setup can be further simplified. We propose a lightweight correlation scheme where the decision is taken in the Fourier plane. For this purpose, the Fourier plane is adapted and used as a decision plane. Then, the offline phase and the decision metric are re-examined in order to keep a reasonable recognition rate. The benefits of the proposed approach are numerous: (1) it overcomes the constraints related to the use of a second lens; (2) the optical correlation setup is simplified; (3) the multiplication with the correlation filter can be done digitally, which offers a higher adaptability according to the application. Moreover, the digital counterpart of the correlation scheme is lightened since with the proposed scheme we get rid of the inverse Fourier transform (IFT) calculation (i.e., decision directly in the Fourier domain without resorting to IFT). To assess the performance of the proposed approach, an insight into digital hardware resources saving is provided. The proposed method involves nearly 100 times fewer arithmetic operators. Moreover, from experimental results in the context of face verification-based correlation, we demonstrate that the proposed scheme provides comparable or better accuracy than the traditional method. One interesting feature of the proposed scheme is that it could greatly outperform the traditional scheme for face identification application in terms of sensitivity to face orientation. The proposed method is found to be digital/optical implementation-friendly, which facilitates its integration on a very broad range of scenarios.
NASA Astrophysics Data System (ADS)
Şahin, Rıdvan; Liu, Peide
2017-07-01
Simplified neutrosophic set (SNS) is an appropriate tool used to express the incompleteness, indeterminacy and uncertainty of the evaluation objects in decision-making process. In this study, we define the concept of possibility SNS including two types of information such as the neutrosophic performance provided from the evaluation objects and its possibility degree using a value ranging from zero to one. Then by extending the existing neutrosophic information, aggregation models for SNSs that cannot be used effectively to fusion the two different information described above, we propose two novel neutrosophic aggregation operators considering possibility, which are named as a possibility-induced simplified neutrosophic weighted arithmetic averaging operator and possibility-induced simplified neutrosophic weighted geometric averaging operator, and discuss their properties. Moreover, we develop a useful method based on the proposed aggregation operators for solving a multi-criteria group decision-making problem with the possibility simplified neutrosophic information, in which the weights of decision-makers and decision criteria are calculated based on entropy measure. Finally, a practical example is utilised to show the practicality and effectiveness of the proposed method.
Scholten, Matthé; Gather, Jakov
2018-04-01
It is widely accepted among medical ethicists that competence is a necessary condition for informed consent. In this view, if a patient is incompetent to make a particular treatment decision, the decision must be based on an advance directive or made by a substitute decision-maker on behalf of the patient. We call this the competence model. According to a recent report of the United Nations (UN) High Commissioner for Human Rights, article 12 of the UN Convention on the Rights of Persons with Disabilities (CRPD) presents a wholesale rejection of the competence model. The High Commissioner here adopts the interpretation of article 12 proposed by the Committee on the Rights of Persons with Disabilities. On this interpretation, CRPD article 12 renders it impermissible to deny persons with mental disabilities the right to make treatment decisions on the basis of impaired decision-making capacity and demands the replacement of all regimes of substitute decision-making by supported decision-making. In this paper, we explicate six adverse consequences of CRPD article 12 for persons with mental disabilities and propose an alternative way forward. The proposed model combines the strengths of the competence model and supported decision-making. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Leveraging consumer's behaviour to promote generic drugs in Italy.
Zerbini, Cristina; Luceri, Beatrice; Vergura, Donata Tania
2017-04-01
The aim of this study was to fill the lack of knowledge regarding a more grounded exploration of the consumer's decision-making process in the context of generic drugs. In this perspective, a model, within the theoretical framework of the Theory of Planned Behaviour (TPB), for studying the consumers' purchase intention of generic drugs was developed. An online survey on 2,222 Italian people who bought drugs in the past was conducted. The proposed model was tested through structural equation modelling (SEM). Almost all the constructs considered in the model, except the perceived behavioural control, contribute to explain the consumer's purchase intention of generic drugs, after controlling for demographic variables (age, income, education). Specifically, attitude, subjective norm, past behaviour, self-identity and trust in the pharmacist have a positive influence on the intention to buy generic drugs. On the contrary, perceived risk towards products and brand sensitivity act negatively. The results of the present study could be useful to public policy makers in developing effective policies and educational campaigns aimed at promoting generic drugs. Specifically, marketing efforts should be directed to inform consumers about the generic drugs' characteristics to mitigate the perceived risk towards these products and to raise awareness during their decision-making process. Copyright © 2017 Elsevier B.V. All rights reserved.
Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith
2015-01-01
Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541
Sonuga-Barke, Edmund J S; Fairchild, Graeme
2012-07-15
Psychiatric neuroeconomics offers an alternative approach to understanding mental disorders by studying the way disorder-related neurobiological alterations constrain economic agency, as revealed through decisions about choices between future goods. In this article, we apply this perspective to understand suboptimal decision making in attention-deficit/hyperactivity disorder (ADHD) by integrating recent advances in the neuroscience of decision making and studies of the pathophysiology of ADHD. We identify three brain networks as candidates for further study and develop specific hypotheses about how these could be implicated in ADHD. First, we postulate that altered patterns of connectivity within a network linking medial prefrontal cortex and posterior cingulate cortex (i.e., the default mode network) disrupts ordering of utilities, prospection about desired future states, setting of future goals, and implementation of aims. Second, we hypothesize that deficits in dorsal frontostriatal networks, including the dorsolateral prefrontal cortex and dorsal striatum, produce executive dysfunction-mediated impairments in the ability to compare outcome options and make choices. Third, we propose that dopaminergic dysregulation in a ventral frontostriatal network encompassing the orbitofrontal cortex, ventral striatum, and amygdala disrupts processing of cues of future utility, evaluation of experienced outcomes (feedback), and learning of associations between cues and outcomes. Finally, we extend this perspective to consider three contemporary themes in ADHD research. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Modifying Evaluations and Decisions in Risky Situations.
Maldonado, Antonio; Serra, Sara; Catena, Andrés; Cándido, Antonio; Megías, Alberto
2016-09-20
The main aim of this research was to investigate the decision making process in risky situations. We studied how different types of feedback on risky driving behaviors modulate risk evaluation and risk-taking. For a set of risky traffic situations, participants had to make evaluative judgments (judge the situation as risky or not) and urgent decisions (brake or not). In Experiment 1, participants received feedback with and without negative emotional content when they made risky behaviors. In Experiment 2 we investigated the independent effects of feedback and negative emotional stimuli. The results showed three important findings: First, urgent decisions were faster [F(1, 92) = 6.76, p = .01] and more cautious [F(1, 92) = 17.16, p < .001] than evaluative judgments. These results suggest that evaluative judgments of risk and actual risk-taking may not always coincide, and that they seem to be controlled by two different processing systems as proposed by dual process theories. Second, feedback made participants' responses even faster [F(1, 111) = 71.53, p < .001], allowing greater risk sensitivity [F(1, 111) = 22.12, p < .001] and skewing towards more cautious responses [F(1, 111) = 14.09, p < .001]. Finally, emotional stimuli had an effect only when they were presented as feedback. The results of this research increase our understanding of the processes involved in risky driving behavior and suggest efficient ways to control risk taking through the use of feedback.
Stubelj Ars, Mojca; Bohanec, Marko
2010-12-01
This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists. Copyright © 2010 Elsevier Ltd. All rights reserved.
A multicriteria-based methodology for site prioritisation in sediment management.
Alvarez-Guerra, Manuel; Viguri, Javier R; Voulvoulis, Nikolaos
2009-08-01
Decision-making for sediment management is a complex task that incorporates the selections of areas for remediation and the assessment of options for any mitigation required. The application of Multicriteria Analysis (MCA) to rank different areas, according to their need for sediment management, provides a great opportunity for prioritisation, a first step in an integrated methodology that finally aims to assess and select suitable alternatives for managing the identified priority sites. This paper develops a methodology that starts with the delimitation of management units within areas of study, followed by the application of MCA methods that allows ranking of these management units, according to their need for remediation. This proposed process considers not only scientific evidence on sediment quality, but also other relevant aspects such as social and economic criteria associated with such decisions. This methodology is illustrated with its application to the case study area of the Bay of Santander, in northern Spain, highlighting some of the implications of utilising different MCA methods in the process. It also uses site-specific data to assess the subjectivity in the decision-making process, mainly reflected through the assignment of the criteria weights and uncertainties in the criteria scores. Analysis of the sensitivity of the results to these factors is used as a way to assess the stability and robustness of the ranking as a first step of the sediment management decision-making process.
The Just War Tradition: A Model for Healthcare Ethics.
Connolly, Chaplain John D
2018-06-01
Healthcare ethics committees, physicians, surgeons, nurses, families, and patients themselves are constantly under pressure to make appropriate medically ethical decisions concerning patient care. Various models for healthcare ethics decisions have been proposed throughout the years, but by and large they are focused on making the initial ethical decision. What follows is a proposed model for healthcare ethics that considers the most appropriate decisions before, during, and after any intervention. The Just War Tradition is a model that is thorough in its exploration of the ethics guiding a nation to either engage in or refuse to engage in combatant actions. In recent years, the Just War Tradition has expanded beyond the simple consideration of going to war or not to include how the war is conducted and what the post-war phase would look like ethically. This paper is an exploration of a healthcare ethics decision making model using the tenets of the Just War Tradition as a framework. It discusses the initial consult level of decision making prior to any medical intervention, then goes further in considering the ongoing ethical paradigm during medical intervention and post intervention. Thus, this proposal is a more holistic approach to healthcare ethics decision making that encourages healthcare ethics committees to consider alternate models and ways of processing so that ultimately what is best for patient, family, staff, and the environment is all taken into consideration.
Indicators of Informal and Formal Decision-Making about a Socioscientific Issue
ERIC Educational Resources Information Center
Dauer, Jenny M.; Lute, Michelle L.; Straka, Olivia
2017-01-01
We propose two contrasting types of student decision-making based on social and cognitive psychology models of separate mental processes for problem solving. Informal decision-making uses intuitive reasoning and is subject to cognitive biases, whereas formal decision-making uses effortful, logical reasoning. We explored indicators of students'…
10 CFR 900.6 - Coordination of permitting and related environmental reviews.
Code of Federal Regulations, 2010 CFR
2010-01-01
... display the information utilized by the permitting entities as the basis for their decisions on the... to all permitting entities for making their agency decisions in order to ensure that each permitting... final agency decision, and all other analyses used as the basis for all decisions on a proposed...
A Multi-criterial Decision Support System for Forest Management
Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch
1999-01-01
We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...
The neural basis of economic decision-making in the Ultimatum Game.
Sanfey, Alan G; Rilling, James K; Aronson, Jessica A; Nystrom, Leigh E; Cohen, Jonathan D
2003-06-13
The nascent field of neuroeconomics seeks to ground economic decision making in the biological substrate of the brain. We used functional magnetic resonance imaging of Ultimatum Game players to investigate neural substrates of cognitive and emotional processes involved in economic decision-making. In this game, two players split a sum of money;one player proposes a division and the other can accept or reject this. We scanned players as they responded to fair and unfair proposals. Unfair offers elicited activity in brain areas related to both emotion (anterior insula) and cognition (dorsolateral prefrontal cortex). Further, significantly heightened activity in anterior insula for rejected unfair offers suggests an important role for emotions in decision-making.
The Neural Basis of Economic Decision-Making in the Ultimatum Game
NASA Astrophysics Data System (ADS)
Sanfey, Alan G.; Rilling, James K.; Aronson, Jessica A.; Nystrom, Leigh E.; Cohen, Jonathan D.
2003-06-01
The nascent field of neuroeconomics seeks to ground economic decision- making in the biological substrate of the brain. We used functional magnetic resonance imaging of Ultimatum Game players to investigate neural substrates of cognitive and emotional processes involved in economic decision-making. In this game, two players split a sum of money; one player proposes a division and the other can accept or reject this. We scanned players as they responded to fair and unfair proposals. Unfair offers elicited activity in brain areas related to both emotion (anterior insula) and cognition (dorsolateral prefrontal cortex). Further, significantly heightened activity in anterior insula for rejected unfair offers suggests an important role for emotions in decision-making.
In Search of an Identity: Air Force Core Competencies
1997-06-01
for connecting core competencies to both inside and outside the service . Core competencies have become a decision making framework for the Air Force...Proposed Intra– Service Relationship ................................................................. 76 Figure 2. Proposed Inter- service and Joint...connecting core competencies to both inside and outside the service . Core competencies have become a decision making framework for the Air Force. They
Dynamical crossover in a stochastic model of cell fate decision
NASA Astrophysics Data System (ADS)
Yamaguchi, Hiroki; Kawaguchi, Kyogo; Sagawa, Takahiro
2017-07-01
We study the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation. We propose a model of a self-replicating Langevin system, where cells choose their fate (i.e., proliferation or differentiation) depending on local cell density. Based on this model, we propose a scenario for multicellular organisms to maintain the density of cells (i.e., homeostasis) through finite-ranged cell-cell interactions. Furthermore, we numerically show that the distribution of the number of descendant cells changes over time, thus unifying the previously proposed two models regarding homeostasis: the critical birth death process and the voter model. Our results provide a general platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical mechanics.
Harris, Claire; Allen, Kelly; Ramsey, Wayne; King, Richard; Green, Sally
2018-05-30
This is the final paper in a thematic series reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was established to explore a systematic, integrated, evidence-based organisation-wide approach to disinvestment in a large Australian health service network. This paper summarises the findings, discusses the contribution of the SHARE Program to the body of knowledge and understanding of disinvestment in the local healthcare setting, and considers implications for policy, practice and research. The SHARE program was conducted in three phases. Phase One was undertaken to understand concepts and practices related to disinvestment and the implications for a local health service and, based on this information, to identify potential settings and methods for decision-making about disinvestment. The aim of Phase Two was to implement and evaluate the proposed methods to determine which were sustainable, effective and appropriate in a local health service. A review of the current literature incorporating the SHARE findings was conducted in Phase Three to contribute to the understanding of systematic approaches to disinvestment in the local healthcare context. SHARE differed from many other published examples of disinvestment in several ways: by seeking to identify and implement disinvestment opportunities within organisational infrastructure rather than as standalone projects; considering disinvestment in the context of all resource allocation decisions rather than in isolation; including allocation of non-monetary resources as well as financial decisions; and focusing on effective use of limited resources to optimise healthcare outcomes. The SHARE findings provide a rich source of new information about local health service decision-making, in a level of detail not previously reported, to inform others in similar situations. Multiple innovations related to disinvestment were found to be acceptable and feasible in the local setting. Factors influencing decision-making, implementation processes and final outcomes were identified; and methods for further exploration, or avoidance, in attempting disinvestment in this context are proposed based on these findings. The settings, frameworks, models, methods and tools arising from the SHARE findings have potential to enhance health care and patient outcomes.
Larsen, Louise Pape; Biering, Karin; Johnsen, Soren Paaske; Riiskjær, Erik; Schougaard, Liv Marit
2014-01-01
Background Patient-reported outcome (PRO) measures may be used at a group level for research and quality improvement and at the individual patient level to support clinical decision making and ensure efficient use of resources. The challenges involved in implementing PRO measures are mostly the same regardless of aims and diagnostic groups and include logistic feasibility, high response rates, robustness, and ability to adapt to the needs of patient groups and settings. If generic PRO systems can adapt to specific needs, advanced technology can be shared between medical specialties and for different aims. Objective We describe methodological, organizational, and practical experiences with a generic PRO system, WestChronic, which is in use among a range of diagnostic groups and for a range of purposes. Methods The WestChronic system supports PRO data collection, with integration of Web and paper PRO questionnaires (mixed-mode) and automated procedures that enable adherence to implementation-specific schedules for the collection of PRO. For analysis, we divided functionalities into four elements: basic PRO data collection and logistics, PRO-based clinical decision support, PRO-based automated decision algorithms, and other forms of communication. While the first element is ubiquitous, the others are optional and only applicable at a patient level. Methodological and organizational experiences were described according to each element. Results WestChronic has, to date, been implemented in 22 PRO projects within 18 diagnostic groups, including cardiology, neurology, rheumatology, nephrology, orthopedic surgery, gynecology, oncology, and psychiatry. The aims of the individual projects included epidemiological research, quality improvement, hospital evaluation, clinical decision support, efficient use of outpatient clinic resources, and screening for side effects and comorbidity. In total 30,174 patients have been included, and 59,232 PRO assessments have been collected using 92 different PRO questionnaires. Response rates of up to 93% were achieved for first-round questionnaires and up to 99% during follow-up. For 6 diagnostic groups, PRO data were displayed graphically to the clinician to facilitate flagging of important symptoms and decision support, and in 5 diagnostic groups PRO data were used for automatic algorithm-based decisions. Conclusions WestChronic has allowed the implementation of all proposed protocol for data collection and processing. The system has achieved high response rates, and longitudinal attrition is limited. The relevance of the questions, the mixed-mode principle, and automated procedures has contributed to the high response rates. Furthermore, development and implementation of a number of approaches and methods for clinical use of PRO has been possible without challenging the generic property. Generic multipurpose PRO systems may enable sharing of automated and efficient logistics, optimal response rates, and other advanced options for PRO data collection and processing, while still allowing adaptation to specific aims and patient groups. PMID:24518281
How users adopt healthcare information: An empirical study of an online Q&A community.
Jin, Jiahua; Yan, Xiangbin; Li, Yijun; Li, Yumei
2016-02-01
The emergence of social media technology has led to the creation of many online healthcare communities, where patients can easily share and look for healthcare-related information from peers who have experienced a similar problem. However, with increased user-generated content, there is a need to constantly analyse which content should be trusted as one sifts through enormous amounts of healthcare information. This study aims to explore patients' healthcare information seeking behavior in online communities. Based on dual-process theory and the knowledge adoption model, we proposed a healthcare information adoption model for online communities. This model highlights that information quality, emotional support, and source credibility are antecedent variables of adoption likelihood of healthcare information, and competition among repliers and involvement of recipients moderate the relationship between the antecedent variables and adoption likelihood. Empirical data were collected from the healthcare module of China's biggest Q&A community-Baidu Knows. Text mining techniques were adopted to calculate the information quality and emotional support contained in each reply text. A binary logistics regression model and hierarchical regression approach were employed to test the proposed conceptual model. Information quality, emotional support, and source credibility have significant and positive impact on healthcare information adoption likelihood, and among these factors, information quality has the biggest impact on a patient's adoption decision. In addition, competition among repliers and involvement of recipients were tested as moderating effects between these antecedent factors and the adoption likelihood. Results indicate competition among repliers positively moderates the relationship between source credibility and adoption likelihood, and recipients' involvement positively moderates the relationship between information quality, source credibility, and adoption decision. In addition to information quality and source credibility, emotional support has significant positive impact on individuals' healthcare information adoption decisions. Moreover, the relationships between information quality, source credibility, emotional support, and adoption decision are moderated by competition among repliers and involvement of recipients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Internet censorship: Congress moves toward final decision.
Mirken, B
1995-12-01
The House and the Senate have passed proposals restricting the online access to obscene or indecent information. AIDS activists and service organizations fear that the proposals will restrict the distribution of HIV/AIDS information. A House/Senate conference committee soon will meet for a final decision. Religious right organizations are pressing for additional restrictions, while civil liberties, arts, and libertarian groups have expressed opposition on freedom-of-speech grounds. Some conservatives, including Newt Gingrich (R-GA), believe that the proposals may retard the growth of online communication.
ERIC Educational Resources Information Center
Jones, Dennis P.
1993-01-01
An approach to college budgeting that encompasses strategic as well as operational decisions is proposed. Strategic decisions focus on creation and maintenance of institutional capacity, whereas operational decisions focus on use of that capacity to accomplish specific purposes. Strategic budgeting must emphasize institutional assets and their…
76 FR 77230 - Agency Information Collection Activities; Proposed Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-12
... consumers in making informed purchasing decisions, and recordkeeping requirements that assist the Commission... Rules establish disclosure requirements that assist consumers in making informed purchasing decisions... consumers in making informed purchasing decisions, and recordkeeping requirements that assist the Commission...
Career Decision-Making Characteristics of Primary Education Students in Greece
ERIC Educational Resources Information Center
Sidiropoulou-Dimakakou, Despina; Mylonas, Kostas; Argyropoulou, Katerina; Drosos, Nikos
2013-01-01
The present study aims at investigating career decision-making process of 6th grade students with the use of the Childhood Career Decision-Making Questionnaire (CCDMQ). CCDMQ offers scores for the following three decision-making dimensions: (a) "Concerns/fears regarding career future", (b) "Investment ?n decision-making…
ERIC Educational Resources Information Center
Parmigiani, Davide
2012-01-01
This research was aimed at highlighting the decision-making processes of Italian teachers; in particular, we have focused on individual and collaborative decisions developed both during meetings and in the classroom. The study has underlined the features of teachers' decisions when decisions are made in groups and individually. A questionnaire was…
PCA based feature reduction to improve the accuracy of decision tree c4.5 classification
NASA Astrophysics Data System (ADS)
Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.
2018-03-01
Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.
Elwyn, Glyn; Burstin, Helen; Barry, Michael J; Corry, Maureen P; Durand, Marie Anne; Lessler, Daniel; Saigal, Christopher
2018-04-27
Efforts to implement the use of patient decision aids to stimulate shared decision making are gaining prominence. Patient decision aids have been designed to help patients participate in making specific choices among health care options. Because these tools clearly influence decisions, poor quality, inaccurate or unbalanced presentations or misleading tools are a risk to patients. As payer interest in these tools increases, so does the risk that patients are harmed by the use of tools that are described as patient decision aids yet fail to meet established standards. To address this problem, the National Quality Forum (NQF) in the USA convened a multi-stakeholder expert panel in 2016 to propose national standards for a patient decision aid certification process. In 2017, NQF established an Action Team to foster shared decision making, and to call for a national certification process as one recommendation among others to stimulate improvement. A persistent barrier to the setup of a national patient decision aids certification process is the lack of a sustainable financial model to support the work. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.
Cooke, Mary; Hurley, Ciarán
2008-05-01
We aimed to identify policy, process and ethical issues related to allocation of National Health Service resources when patients with end-of-life illness are referred to acute care services. Sharing healthcare decisions denotes a different partnership between professionals and patients when patients are empowered to define their needs. Implementation of a transition from professional to patient decision-making appears to be dependent upon its interpretation by personnel delivering care using the local trust policy. The outcome of this is a reformation of responsibility for budget allocation, choice of acute care provider and selecting services, currently in the realm of primary care; be it the general practitioner, community practitioners, or the patient. We used a 'lens' approach to case study analysis in which the lens is constructed of a model of policy analysis and four principles of biomedical ethics. A patient's decision to decline care proposed by an Accident and Emergency department nurse and the nurse's response to that decision expose a policy that restricts the use of ambulance transport and with that, flexibility in responses to patients' decisions. End-of-life care partnership decisions require sensitivity and flexibility from all healthcare practitioners. We found that policy-based systems currently used to deliver care across the primary care - hospital care border are far from seamless and can lead to foreseeable problems. Health professionals responsible for the care of a patient at the end of life should consider the holistic outcomes of resource allocation decisions for patients. Government and health professional agenda suggest that patients should be given a greater element of control over their healthcare than has historically been the case. When patients take responsibility for their decisions, healthcare personnel should recognize that this signals a shift in the nature of the professional-patient relationship to one of partnership.
A Collaborative Knowledge Plane for Autonomic Networks
NASA Astrophysics Data System (ADS)
Mbaye, Maïssa; Krief, Francine
Autonomic networking aims to give network components self-managing capabilities. Several autonomic architectures have been proposed. Each of these architectures includes sort of a knowledge plane which is very important to mimic an autonomic behavior. Knowledge plane has a central role for self-functions by providing suitable knowledge to equipment and needs to learn new strategies for more accuracy.However, defining knowledge plane's architecture is still a challenge for researchers. Specially, defining the way cognitive supports interact each other in knowledge plane and implementing them. Decision making process depends on these interactions between reasoning and learning parts of knowledge plane. In this paper we propose a knowledge plane's architecture based on machine learning (inductive logic programming) paradigm and situated view to deal with distributed environment. This architecture is focused on two self-functions that include all other self-functions: self-adaptation and self-organization. Study cases are given and implemented.
Guikema, Seth
2012-07-01
Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.
Management of local economic and ecological system of coal processing company
NASA Astrophysics Data System (ADS)
Kiseleva, T. V.; Mikhailov, V. G.; Karasev, V. A.
2016-10-01
The management issues of local ecological and economic system of coal processing company - coal processing plant - are considered in the article. The objectives of the research are the identification and the analysis of local ecological and economic system (coal processing company) performance and the proposals for improving the mechanism to support the management decision aimed at improving its environmental safety. The data on the structure of run-of-mine coal processing products are shown. The analysis of main ecological and economic indicators of coal processing enterprises, characterizing the state of its environmental safety, is done. The main result of the study is the development of proposals to improve the efficiency of local enterprise ecological and economic system management, including technical, technological and business measures. The results of the study can be recommended to industrial enterprises to improve their ecological and economic efficiency.
Collective and decentralized management model in public hospitals: perspective of the nursing team.
Bernardes, Andrea; Cecilio, Luiz Carlos de Oliveira; Evora, Yolanda Dora Martinez; Gabriel, Carmen Silvia; Carvalho, Mariana Bernardes de
2011-01-01
This research aims to present the implementation of the collective and decentralized management model in functional units of a public hospital in the city of Ribeirão Preto, state of São Paulo, according to the view of the nursing staff and the health technical assistant. This historical and organizational case study used qualitative thematic content analysis proposed by Bardin for data analysis. The institution started the decentralization of its administrative structure in 1999, through collective management, which permitted several internal improvements, with positive repercussion for the care delivered to users. The top-down implementation of the process seems to have jeopardized workers adherence, although collective management has intensified communication and the sharing of power and decision. The study shows that there is still much work to be done to concretize this innovative management proposal, despite the advances regarding the quality of care.
Managing Decisions on Changes in the Virtual Enterprise Evolution
NASA Astrophysics Data System (ADS)
Drissen-Silva, Marcus Vinicius; Rabelo, Ricardo José
VE evolution deals with problems that happen during the VE operation and that put on risk planned results. This requires the application of problem-solving mechanisms to guarantee the construction of a new but feasible VE plan. Grounded on Project Management and Decision Support Systems foundations, this paper proposes a distributed collaborative decision support system to manage the VE evolution. Its main rationale is that VE’s members are autonomous and hence that all the affected partners should discuss about the necessary changes on the current VE’s plan. In the proposed approach, this discussion is guided by a decision protocol, and the impact of decisions can be evaluated. Results of a first prototype implementation are presented and discussed, with a special focus on the part which regulates the argumentation, voting and comparison of possible solutions.
Present-value analysis: A systems approach to public decisionmaking for cost effectiveness
NASA Technical Reports Server (NTRS)
Herbert, T. T.
1971-01-01
Decision makers within Governmental agencies and Congress must evaluate competing (and sometimes conflicting) proposals which seek funding and implementation. Present value analysis can be an effective decision making tool by enabling the formal evaluation of the effects of competing proposals on efficient national resource utilization. A project's costs are not only its direct disbursements, but its social costs as well. How much does it cost to have those funds diverted from their use and economic benefit by the private sector to the public project? Comparisons of competing projects' social costs allow decision makers to expand their decision bases by quantifying the projects' impacts upon the economy and the efficient utilization of the country's limited national resources. A conceptual model is established for the choosing of the appropriate discount rate to be used in evaluation decisions through the technique.
Adamkovič, Matúš; Martončik, Marcel
2017-01-01
This review focuses on the issue of poverty affecting economic decision-making. By critically evaluating existing studies, the authors propose a structural model detailing the cognitive mechanism involved in how poverty negatively impacts economic decision-making, and explores evidence supporting the basis for the formation of this model. The suggested mechanism consists of a relationship between poverty and four other factors: (1) cognitive load (e.g., experiencing negative affect and stress); (2) executive functions (e.g., attention, working memory, and self-control); (3) intuition/deliberation in decision-making; and (4) economic decision-making (e.g., time-discounting and risk preference), with a final addition of financial literacy as a covariate. This paper focuses on shortfalls in published research, and delves further into the proposed model. PMID:29075221
Logistics Response to the Industry 4.0: the Physical Internet
NASA Astrophysics Data System (ADS)
Maslarić, Marinko; Nikoličić, Svetlana; Mirčetić, Dejan
2016-11-01
Today's mankind and all human activities are constantly changing and evolving in response to changes in technology, social and economic environments and climate. Those changes drive a "new" way of manufacturing industry. That novelty could be described as the organization of production processes based on technology and devices autonomously communicating with each other along the value chain. Decision-makers have to address this novelty (usually named as Industry 4.0) and try to develop appropriate information systems, physical facilities, and different kind of technologies capable of meeting the future needs of economy. As a consequence, there is a need for new paradigms of the way freight is move, store, realize, and supply through the world (logistics system). One of the proposed solutions is the Physical Internet, concept of open global logistics system which completely redefines current supply chain configuration, business models, and value-creation patterns.However, further detailed research on this topic is much needed. This paper aims to provide a balanced review of the variety of views considered among professionals in the field of Physical Internet with the final aim to identify the biggest challenges (technological, societal, business paradigm) of proposed new logistics paradigm as a practical solution in supporting Industry 4.0.
Cloud-based mobility management in heterogeneous wireless networks
NASA Astrophysics Data System (ADS)
Kravchuk, Serhii; Minochkin, Dmytro; Omiotek, Zbigniew; Bainazarov, Ulan; Weryńska-Bieniasz, RóŻa; Iskakova, Aigul
2017-08-01
Mobility management is the key feature that supports the roaming of users between different systems. Handover is the essential aspect in the development of solutions supporting mobility scenarios. The handover process becomes more complex in a heterogeneous environment compared to the homogeneous one. Seamlessness and reduction of delay in servicing the handover calls, which can reduce the handover dropping probability, also require complex algorithms to provide a desired QoS for mobile users. A challenging problem to increase the scalability and availability of handover decision mechanisms is discussed. The aim of the paper is to propose cloud based handover as a service concept to cope with the challenges that arise.
Zhou, Li; Hongsermeier, Tonya; Boxwala, Aziz; Lewis, Janet; Kawamoto, Kensaku; Maviglia, Saverio; Gentile, Douglas; Teich, Jonathan M; Rocha, Roberto; Bell, Douglas; Middleton, Blackford
2013-01-01
At present, there are no widely accepted, standard approaches for representing computer-based clinical decision support (CDS) intervention types and their structural components. This study aimed to identify key requirements for the representation of five widely utilized CDS intervention types: alerts and reminders, order sets, infobuttons, documentation templates/forms, and relevant data presentation. An XML schema was proposed for representing these interventions and their core structural elements (e.g., general metadata, applicable clinical scenarios, CDS inputs, CDS outputs, and CDS logic) in a shareable manner. The schema was validated by building CDS artifacts for 22 different interventions, targeted toward guidelines and clinical conditions called for in the 2011 Meaningful Use criteria. Custom style sheets were developed to render the XML files in human-readable form. The CDS knowledge artifacts were shared via a public web portal. Our experience also identifies gaps in existing standards and informs future development of standards for CDS knowledge representation and sharing.
Multi-stage methodology to detect health insurance claim fraud.
Johnson, Marina Evrim; Nagarur, Nagen
2016-09-01
Healthcare costs in the US, as well as in other countries, increase rapidly due to demographic, economic, social, and legal changes. This increase in healthcare costs impacts both government and private health insurance systems. Fraudulent behaviors of healthcare providers and patients have become a serious burden to insurance systems by bringing unnecessary costs. Insurance companies thus develop methods to identify fraud. This paper proposes a new multistage methodology for insurance companies to detect fraud committed by providers and patients. The first three stages aim at detecting abnormalities among providers, services, and claim amounts. Stage four then integrates the information obtained in the previous three stages into an overall risk measure. Subsequently, a decision tree based method in stage five computes risk threshold values. The final decision stating whether the claim is fraudulent is made by comparing the risk value obtained in stage four with the risk threshold value from stage five. The research methodology performs well on real-world insurance data.
Bond, V
1997-01-01
Fieldwork on a commercial farm in southern Zambia, which was aimed at designing an HIV prevention program for farm workers, gradually exposed the nature of sexual liaisons between young girls, coming to work on the farm from the surrounding villages, and older migrant men workers. Before completing fieldwork, the anthropologist voiced her concern about the implications of these liaisons for the spread of STDs and HIV with the local rural community, farm management and farm workers. The immediate outcome of her intercessions was the decision by management to sack under-age workers. Although some members of the local community, including local research assistants, and some managers and workers welcomed this decision, others were angered by it. Caught between interest groups and conflicting guidelines, the anthropologist, it is argued, was in a no-win situation, 'between a rock and a hard place'. The paper proposes that the application of anthropological ethics in AIDS research needs some re-evaluation.
Strategy on energy saving reconstruction of distribution networks based on life cycle cost
NASA Astrophysics Data System (ADS)
Chen, Xiaofei; Qiu, Zejing; Xu, Zhaoyang; Xiao, Chupeng
2017-08-01
Because the actual distribution network reconstruction project funds are often limited, the cost-benefit model and the decision-making method are crucial for distribution network energy saving reconstruction project. From the perspective of life cycle cost (LCC), firstly the research life cycle is determined for the energy saving reconstruction of distribution networks with multi-devices. Then, a new life cycle cost-benefit model for energy-saving reconstruction of distribution network is developed, in which the modification schemes include distribution transformers replacement, lines replacement and reactive power compensation. In the operation loss cost and maintenance cost area, the operation cost model considering the influence of load season characteristics and the maintenance cost segmental model of transformers are proposed. Finally, aiming at the highest energy saving profit per LCC, a decision-making method is developed while considering financial and technical constraints as well. The model and method are applied to a real distribution network reconstruction, and the results prove that the model and method are effective.
Attention control learning in the decision space using state estimation
NASA Astrophysics Data System (ADS)
Gharaee, Zahra; Fatehi, Alireza; Mirian, Maryam S.; Nili Ahmadabadi, Majid
2016-05-01
The main goal of this paper is modelling attention while using it in efficient path planning of mobile robots. The key challenge in concurrently aiming these two goals is how to make an optimal, or near-optimal, decision in spite of time and processing power limitations, which inherently exist in a typical multi-sensor real-world robotic application. To efficiently recognise the environment under these two limitations, attention of an intelligent agent is controlled by employing the reinforcement learning framework. We propose an estimation method using estimated mixture-of-experts task and attention learning in perceptual space. An agent learns how to employ its sensory resources, and when to stop observing, by estimating its perceptual space. In this paper, static estimation of the state space in a learning task problem, which is examined in the WebotsTM simulator, is performed. Simulation results show that a robot learns how to achieve an optimal policy with a controlled cost by estimating the state space instead of continually updating sensory information.
Ristić, Vladica; Maksin, Marija; Nenković-Riznić, Marina; Basarić, Jelena
2018-01-15
The process of making decisions on sustainable development and construction begins in spatial and urban planning when defining the suitability of using land for sustainable construction in a protected area (PA) and its immediate and regional surroundings. The aim of this research is to propose and assess a model for evaluating land-use suitability for sustainable construction in a PA and its surroundings. The methodological approach of Multi-Criteria Decision Analysis was used in the formation of this model and adapted for the research; it was combined with the adapted Analytical hierarchy process and the Delphi process, and supported by a geographical information system (GIS) within the framework of ESRI ArcGIS software - Spatial analyst. The model is applied to the case study of Sara mountain National Park in Kosovo. The result of the model is a "map of integrated assessment of land-use suitability for sustainable construction in a PA for the natural factor". Copyright © 2017 Elsevier Ltd. All rights reserved.
Liu, Peide; Li, Dengfeng
2017-01-01
Muirhead mean (MM) is a well-known aggregation operator which can consider interrelationships among any number of arguments assigned by a variable vector. Besides, it is a universal operator since it can contain other general operators by assigning some special parameter values. However, the MM can only process the crisp numbers. Inspired by the MM' advantages, the aim of this paper is to extend MM to process the intuitionistic fuzzy numbers (IFNs) and then to solve the multi-attribute group decision making (MAGDM) problems. Firstly, we develop some intuitionistic fuzzy Muirhead mean (IFMM) operators by extending MM to intuitionistic fuzzy information. Then, we prove some properties and discuss some special cases with respect to the parameter vector. Moreover, we present two new methods to deal with MAGDM problems with the intuitionistic fuzzy information based on the proposed MM operators. Finally, we verify the validity and reliability of our methods by using an application example, and analyze the advantages of our methods by comparing with other existing methods.
ERIC Educational Resources Information Center
Hilbig, Benjamin E.; Pohl, Rudiger F.
2009-01-01
According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-01
... separate Decision Record (DR) for this project. As part of the BLM decision-making process, certain..., the BLM will present its own conclusions and recommendations in its respective Record of Decision for... considered prior to a Commission decision on the proposal, it is important that we receive your comments in...
Comparing perceptual and preferential decision making.
Dutilh, Gilles; Rieskamp, Jörg
2016-06-01
Perceptual and preferential decision making have been studied largely in isolation. Perceptual decisions are considered to be at a non-deliberative cognitive level and have an outside criterion that defines the quality of decisions. Preferential decisions are considered to be at a higher cognitive level and the quality of decisions depend on the decision maker's subjective goals. Besides these crucial differences, both types of decisions also have in common that uncertain information about the choice situation has to be processed before a decision can be made. The present work aims to acknowledge the commonalities of both types of decision making to lay bare the crucial differences. For this aim we examine perceptual and preferential decisions with a novel choice paradigm that uses the identical stimulus material for both types of decisions. This paradigm allows us to model the decisions and response times of both types of decisions with the same sequential sampling model, the drift diffusion model. The results illustrate that the different incentive structure in both types of tasks changes people's behavior so that they process information more efficiently and respond more cautiously in the perceptual as compared to the preferential task. These findings set out a perspective for further integration of perceptual and preferential decision making in a single ramework.
DOT National Transportation Integrated Search
2010-09-01
Tools are proposed for carbon footprint estimation of transportation construction projects and decision support : for construction firms that must make equipment choice and usage decisions that affect profits, project duration : and greenhouse gas em...
Goal-Proximity Decision-Making
ERIC Educational Resources Information Center
Veksler, Vladislav D.; Gray, Wayne D.; Schoelles, Michael J.
2013-01-01
Reinforcement learning (RL) models of decision-making cannot account for human decisions in the absence of prior reward or punishment. We propose a mechanism for choosing among available options based on goal-option association strengths, where association strengths between objects represent previously experienced object proximity. The proposed…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-06-02
... Impact (FONSI) and Record of Decision (ROD) on a Final Environmental Assessment (FEA) for the Proposed.../ROD on an FEA for a proposed Federal action at the Macon County Airport, Franklin, NC. The FONSI/ROD... will not significantly affect the quality of the environment. The FEA evaluated Macon County Airport's...
C-fuzzy variable-branch decision tree with storage and classification error rate constraints
NASA Astrophysics Data System (ADS)
Yang, Shiueng-Bien
2009-10-01
The C-fuzzy decision tree (CFDT), which is based on the fuzzy C-means algorithm, has recently been proposed. The CFDT is grown by selecting the nodes to be split according to its classification error rate. However, the CFDT design does not consider the classification time taken to classify the input vector. Thus, the CFDT can be improved. We propose a new C-fuzzy variable-branch decision tree (CFVBDT) with storage and classification error rate constraints. The design of the CFVBDT consists of two phases-growing and pruning. The CFVBDT is grown by selecting the nodes to be split according to the classification error rate and the classification time in the decision tree. Additionally, the pruning method selects the nodes to prune based on the storage requirement and the classification time of the CFVBDT. Furthermore, the number of branches of each internal node is variable in the CFVBDT. Experimental results indicate that the proposed CFVBDT outperforms the CFDT and other methods.
The online community based decision making support system for mitigating biased decision making
NASA Astrophysics Data System (ADS)
Kang, Sunghyun; Seo, Jiwan; Choi, Seungjin; Kim, Junho; Han, Sangyong
2016-10-01
As the Internet technology and social media advance, various information and opinions are shared and distributed through the online communities. However, the existence of implicit and explicit bias of opinions may have a potential influence on the outcomes. Compared to the importance of mitigating biased information, the study in this field is relatively young and does not address many important issues. In this paper we propose the noble approach to mitigate the biased opinions using conventional machine learning methods. The proposed method extracts the useful features such as inclination and sentiment of the community members. They are classified based on their previous behavior, and the propensity of the members is understood. This information on each community and its members is very useful and improve the ability to make an unbiased decision. The proposed method presented in this paper is shown to have the ability to assist optimal, fair and good decision making while also reducing the influence of implicit bias.
Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.
Naso, David; Turchiano, Biagio
2005-04-01
In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.
Vanstone, Meredith; Kinsella, Elizabeth Anne; Nisker, Jeff
2012-03-01
The 2011 SOGC clinical practice guideline "Prenatal Screening for Fetal Aneuploidy in Singleton Pregnancies" recommends that clinicians offer prenatal screening to all pregnant women and provide counselling in a non-directive manner. Non-directive counselling is intended to facilitate autonomous decision-making and remove the clinician's views regarding a particular course of action. However, recent research in genetic counselling raises concerns that non-directive counselling is neither possible nor desirable, and that it may not be the best way to facilitate informed choice. We propose an alternative model of information-sharing specific to prenatal screening that combines attributes of the models of informative decision-making and shared decision-making. Our proposed model is intended to provide clinicians with a strategy to communicate information about prenatal screening in a way that facilitates a shared deliberative process and autonomous decision-making. Our proposed model may better prepare a pregnant woman to make an informed choice about participating in prenatal screening on the basis of her consideration of the medical information provided by her clinician and her particular circumstances and values.
A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.
Cao, Peng; Liu, Xiaoli; Zhang, Jian; Li, Wei; Zhao, Dazhe; Huang, Min; Zaiane, Osmar
2017-03-01
The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD). In this paper, we describes a new CT lung CAD method which aims to detect solid nodules. Specially, we proposed a multi-kernel classifier with a ℓ 2, 1 norm regularizer for heterogeneous feature fusion and selection from the feature subset level, and designed two efficient strategies to optimize the parameters of kernel weights in non-smooth ℓ 2, 1 regularized multiple kernel learning algorithm. The first optimization algorithm adapts a proximal gradient method for solving the ℓ 2, 1 norm of kernel weights, and use an accelerated method based on FISTA; the second one employs an iterative scheme based on an approximate gradient descent method. The results demonstrates that the FISTA-style accelerated proximal descent method is efficient for the ℓ 2, 1 norm formulation of multiple kernel learning with the theoretical guarantee of the convergence rate. Moreover, the experimental results demonstrate the effectiveness of the proposed methods in terms of Geometric mean (G-mean) and Area under the ROC curve (AUC), and significantly outperforms the competing methods. The proposed approach exhibits some remarkable advantages both in heterogeneous feature subsets fusion and classification phases. Compared with the fusion strategies of feature-level and decision level, the proposed ℓ 2, 1 norm multi-kernel learning algorithm is able to accurately fuse the complementary and heterogeneous feature sets, and automatically prune the irrelevant and redundant feature subsets to form a more discriminative feature set, leading a promising classification performance. Moreover, the proposed algorithm consistently outperforms the comparable classification approaches in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping
NASA Astrophysics Data System (ADS)
Yousefi, Mahyar; Carranza, Emmanuel John M.
2015-01-01
Complexities of geological processes portrayed as certain feature in a map (e.g., faults) are natural sources of uncertainties in decision-making for exploration of mineral deposits. Besides natural sources of uncertainties, knowledge-driven (e.g., fuzzy logic) mineral prospectivity mapping (MPM) is also plagued and incurs further uncertainty in subjective judgment of analyst when there is no reliable proven value of evidential scores corresponding to relative importance of geological features that can directly be measured. In this regard, analysts apply expert opinion to assess relative importance of spatial evidences as meaningful decision support. This paper aims for fuzzification of continuous spatial data used as proxy evidence to facilitate and to support fuzzy MPM to generate exploration target areas for further examination of undiscovered deposits. In addition, this paper proposes to adapt the concept of expected value to further improve fuzzy logic MPM because the analysis of uncertain variables can be presented in terms of their expected value. The proposed modified expected value approach to MPM is not only a multi-criteria approach but it also treats uncertainty of geological processes a depicted by maps or spatial data in term of biased weighting more realistically in comparison with classified evidential maps because fuzzy membership scores are defined continuously whereby, for example, there is no need to categorize distances from evidential features to proximity classes using arbitrary intervals. The proposed continuous weighting approach and then integrating the weighted evidence layers by using modified expected value function, described in this paper can be used efficiently in either greenfields or brownfields.
Mathematical Analysis of Vehicle Delivery Scale of Bike-Sharing Rental Nodes
NASA Astrophysics Data System (ADS)
Zhai, Y.; Liu, J.; Liu, L.
2018-04-01
Aiming at the lack of scientific and reasonable judgment of vehicles delivery scale and insufficient optimization of scheduling decision, based on features of the bike-sharing usage, this paper analyses the applicability of the discrete time and state of the Markov chain, and proves its properties to be irreducible, aperiodic and positive recurrent. Based on above analysis, the paper has reached to the conclusion that limit state (steady state) probability of the bike-sharing Markov chain only exists and is independent of the initial probability distribution. Then this paper analyses the difficulty of the transition probability matrix parameter statistics and the linear equations group solution in the traditional solving algorithm of the bike-sharing Markov chain. In order to improve the feasibility, this paper proposes a "virtual two-node vehicle scale solution" algorithm which considered the all the nodes beside the node to be solved as a virtual node, offered the transition probability matrix, steady state linear equations group and the computational methods related to the steady state scale, steady state arrival time and scheduling decision of the node to be solved. Finally, the paper evaluates the rationality and accuracy of the steady state probability of the proposed algorithm by comparing with the traditional algorithm. By solving the steady state scale of the nodes one by one, the proposed algorithm is proved to have strong feasibility because it lowers the level of computational difficulty and reduces the number of statistic, which will help the bike-sharing companies to optimize the scale and scheduling of nodes.
Morales, Dinora Araceli; Bengoetxea, Endika; Larrañaga, Pedro; García, Miguel; Franco, Yosu; Fresnada, Mónica; Merino, Marisa
2008-05-01
In vitro fertilization (IVF) is a medically assisted reproduction technique that enables infertile couples to achieve successful pregnancy. Given the uncertainty of the treatment, we propose an intelligent decision support system based on supervised classification by Bayesian classifiers to aid to the selection of the most promising embryos that will form the batch to be transferred to the woman's uterus. The aim of the supervised classification system is to improve overall success rate of each IVF treatment in which a batch of embryos is transferred each time, where the success is achieved when implantation (i.e. pregnancy) is obtained. Due to ethical reasons, different legislative restrictions apply in every country on this technique. In Spain, legislation allows a maximum of three embryos to form each transfer batch. As a result, clinicians prefer to select the embryos by non-invasive embryo examination based on simple methods and observation focused on morphology and dynamics of embryo development after fertilization. This paper proposes the application of Bayesian classifiers to this embryo selection problem in order to provide a decision support system that allows a more accurate selection than with the actual procedures which fully rely on the expertise and experience of embryologists. For this, we propose to take into consideration a reduced subset of feature variables related to embryo morphology and clinical data of patients, and from this data to induce Bayesian classification models. Results obtained applying a filter technique to choose the subset of variables, and the performance of Bayesian classifiers using them, are presented.
The Career Decision-Making Competence: A New Construct for the Career Realm
ERIC Educational Resources Information Center
Ceschi, Andrea; Costantini, Arianna; Phillips, Susan D.; Sartori, Riccardo
2017-01-01
Purpose: This paper aims to link findings from laboratory-based decision-making research and decision-making competence (DMC) aspects that may be central for career-related decision-making processes. Past research has identified individual differences in rational responses in decision situations, which the authors refer to as DMC. Although there…
Goenka, Anu; Jeena, Prakash M; Mlisana, Koleka; Solomon, Tom; Spicer, Kevin; Stephenson, Rebecca; Verma, Arpana; Dhada, Barnesh; Griffiths, Michael J
2018-03-01
Early diagnosis of tuberculous meningitis (TBM) is crucial to achieve optimum outcomes. There is no effective rapid diagnostic test for use in children. We aimed to develop a clinical decision tool to facilitate the early diagnosis of childhood TBM. Retrospective case-control study was performed across 7 hospitals in KwaZulu-Natal, South Africa (2010-2014). We identified the variables most predictive of microbiologically confirmed TBM in children (3 months to 15 years) by univariate analysis. These variables were modelled into a clinical decision tool and performance tested on an independent sample group. Of 865 children with suspected TBM, 3% (25) were identified with microbiologically confirmed TBM. Clinical information was retrieved for 22 microbiologically confirmed cases of TBM and compared with 66 controls matched for age, ethnicity, sex and geographical origin. The 9 most predictive variables among the confirmed cases were used to develop a clinical decision tool (CHILD TB LP): altered Consciousness; caregiver HIV infected; Illness length >7 days; Lethargy; focal neurologic Deficit; failure to Thrive; Blood/serum sodium <132 mmol/L; CSF >10 Lymphocytes ×10/L; CSF Protein >0.65 g/L. This tool successfully classified an independent sample of 7 cases and 21 controls with a sensitivity of 100% and specificity of 90%. The CHILD TB LP decision tool accurately classified microbiologically confirmed TBM. We propose that CHILD TB LP is prospectively evaluated as a novel rapid diagnostic tool for use in the initial evaluation of children with suspected neurologic infection presenting to hospitals in similar settings.
The Effects of Alcohol and Dosage-Set on Risk-Seeking Behavior in Groups and Individuals
Sayette, Michael A.; Dimoff, John D.; Levine, John M.; Moreland, Richard L.; Votruba-Drzal, Elizabeth
2011-01-01
A great deal of risky activity occurs in social contexts, yet only recently have studies begun to examine the impact of drinking on risk-seeking behavior in groups. The present study sought to extend this work by examining both pharmacological and expectancy (dosage-set) effects of drinking. In addition, by using a much larger sample than in prior studies we aimed to increase the power to examine how drinking affects the decision making process (i.e., Does the initial proposed decision stand, or does it shift during discussion to a safer or riskier final decision?). Seven hundred twenty unacquainted social drinkers (half female) were randomly assigned to 3-person groups that consumed alcohol (0.82 g/kg males; 0.74 g/kg females), a placebo, or a noalcohol control beverage. After drinking, participants decided whether to complete a 30-min questionnaire battery (the less risky choice) or toss a coin and, pending the outcome of that toss, complete either no questionnaires or a 60-min battery (the riskier choice). Neither drinking nor believing one had been drinking affected the decision to toss the coin when participants deliberated in isolation. In contrast, when the decision occurred in a group context, groups led to believe they were drinking alcohol (i.e. groups administered alcohol or placebo beverages) were significantly more likely than groups knowing they had consumed a nonalcoholic beverage (i.e., groups administered a no-alcohol control beverage) to choose the coin toss. Results extend prior findings highlighting the effects of alcohol dosage-set in social contexts. PMID:21639596
An Ecosystem Service Evaluation Tool to Support Ridge-to-Reef Management and Conservation in Hawaii
NASA Astrophysics Data System (ADS)
Oleson, K.; Callender, T.; Delevaux, J. M. S.; Falinski, K. A.; Htun, H.; Jin, G.
2014-12-01
Faced with increasing anthropogenic stressors and diverse stakeholders, local managers are adopting a ridge-to-reef and multi-objective management approach to restore declining coral reef health state. An ecosystem services framework, which integrates ecological indicators and stakeholder values, can foster more applied and integrated research, data collection, and modeling, and thus better inform the decision-making process and realize decision outcomes grounded in stakeholders' values. Here, we describe a research program that (i) leverages remotely sensed and empirical data to build an ecosystem services-based decision-support tool geared towards ridge-to-reef management; and (ii) applies it as part of a structured, value-based decision-making process to inform management in west Maui, a NOAA coral reef conservation priority site. The tool links terrestrial and marine biophysical models in a spatially explicit manner to quantify and map changes in ecosystem services delivery resulting from management actions, projected climate change impacts, and adaptive responses. We couple model outputs with localized valuation studies to translate ecosystem service outcomes into benefits and their associated socio-cultural and/or economic values. Managers can use this tool to run scenarios during their deliberations to evaluate trade-offs, cost-effectiveness, and equity implications of proposed policies. Ultimately, this research program aims at improving the effectiveness, efficiency, and equity outcomes of ecosystem-based management. This presentation will describe our approach, summarize initial results from the terrestrial modeling and economic valuations for west Maui, and highlight how this decision support tool benefits managers in west Maui.
Brien, Sarah; Dibb, Bridget; Burch, Alex
2011-01-01
While intuition plays a role in clinical decision making within conventional medicine, little is understood about its use in complementary and alternative medicine (CAM). The aim of this qualitative study was to investigate intuition from the perspective of homeopathic practitioners; its' manifestation, how it was recognized, its origins and when it was used within daily clinical practice. Semi-structured interviews were carried out with clinically experienced non-National Health Service (NHS) UK homeopathic practitioners. Interpretative phenomenological analysis was used to analyze the data. Homeopaths reported many similarities with conventional medical practitioner regarding the nature, perceived origin and manifestation of their intuitions in clinical practice. Intuition was used in two key aspects of the consultation: (i) to enhance the practitioner-patient relationship, these were generally trusted; and (ii) intuitions relating to the prescribing decision. Homeopaths were cautious about these latter intuitions, testing any intuitive thoughts through deductive reasoning before accepting them. Their reluctance is not surprising given the consequences for patient care, but we propose this also reflects homeopaths' sensitivity to the academic and medical mistrust of both homeopathy and intuition. This study is the first to explore the use of intuition in decision making in any form of complementary medicine. The similarities with conventional practitioners may provide confidence in validating intuition as a legitimate part of the decision making process for these specific practitioners. Further work is needed to elucidate if these findings reflect intuitive use in clinical practice of other CAM practitioners in both private and NHS (i.e., time limited) settings. PMID:19773389
Motivation and effort in individuals with social anhedonia.
McCarthy, Julie M; Treadway, Michael T; Blanchard, Jack J
2015-06-01
It has been proposed that anhedonia may, in part, reflect difficulties in reward processing and effortful decision making. The current study aimed to replicate previous findings of effortful decision making deficits associated with elevated anhedonia and expand upon these findings by investigating whether these decision making deficits are specific to elevated social anhedonia or are also associated with elevated positive schizotypy characteristics. The current study compared controls (n=40) to individuals elevated on social anhedonia (n=30), and individuals elevated on perceptual aberration/magical ideation (n=30) on the Effort Expenditure for Rewards Task (EEfRT). Across groups, participants chose a higher proportion of hard tasks with increasing probability of reward and reward magnitude, demonstrating sensitivity to probability and reward values. Contrary to our expectations, when the probability of reward was most uncertain (50% probability), at low and medium reward values, the social anhedonia group demonstrated more effortful decision making than either individuals high in positive schizotypy or controls. The positive schizotypy group only differed from controls (making less effortful choices than controls) when reward probability was lowest (12%) and the magnitude of reward was the smallest. Our results suggest that social anhedonia is related to intact motivation and effort for monetary rewards, but that individuals with this characteristic display a unique and perhaps inefficient pattern of effort allocation when the probability of reward is most uncertain. Future research is needed to better understand effortful decision making and the processing of reward across a range of individual difference characteristics. Copyright © 2015 Elsevier B.V. All rights reserved.
Navas, Juan F; Torres, Ana; Vilar, Raquel; Verdejo-García, Antonio; Catena, Andrés; Perales, José C
2015-12-01
Recent research has proposed that altered reward and punishment sensitivity, heightened impulsivity, and faulty dynamic decision-making are at the core of disordered gambling. However, each of these traits and cognitive aspects dimensionally vary in the normal population, such that the link between individual differences in these dimensions and gambling use can be ultimately informative to explain disordered gambling. The main aim of the present study was to investigate the contribution of such decision-making-related indices to gambling use parameters in a community sample of college students. Assessment included punishment and reward sensitivity (as measured by the shortened Sensitivity to Punishment and Sensitivity to Reward Questionnaire), impulsivity (as measured by the UPPS-P model and a motor inhibition Go/No-go task), and dynamic decision-making [as measured by the probabilistic reversal learning task (PRLT)]. A structured interview was conducted to explore quantitative aspects of the participants gambling habits (gambling presence, gambling frequency, and average amount of money spent in gambling per unit of time). Our results showed the existence of a decision-making profile of gambling, as it naturally occurs in college students, in which sensation seeking is directly and specifically related to gambling presence (gambling, or not gambling at all), punishment sensitivity is inversely related to gambling frequency, and inflexibility in the PRLT specifically predicts the losses accrued because of gambling. These results are compatible with the idea that sensation seeking and punishment insensitivity could increase exposure to gambling activities, whereas reversal learning inflexibility, in people who already gamble, could boost the risk to accumulate losses.
A decision support system using combined-classifier for high-speed data stream in smart grid
NASA Astrophysics Data System (ADS)
Yang, Hang; Li, Peng; He, Zhian; Guo, Xiaobin; Fong, Simon; Chen, Huajun
2016-11-01
Large volume of high-speed streaming data is generated by big power grids continuously. In order to detect and avoid power grid failure, decision support systems (DSSs) are commonly adopted in power grid enterprises. Among all the decision-making algorithms, incremental decision tree is the most widely used one. In this paper, we propose a combined classifier that is a composite of a cache-based classifier (CBC) and a main tree classifier (MTC). We integrate this classifier into a stream processing engine on top of the DSS such that high-speed steaming data can be transformed into operational intelligence efficiently. Experimental results show that our proposed classifier can return more accurate answers than other existing ones.
NASA Astrophysics Data System (ADS)
Şahin, Rıdvan; Zhang, Hong-yu
2018-03-01
Induced Choquet integral is a powerful tool to deal with imprecise or uncertain nature. This study proposes a combination process of the induced Choquet integral and neutrosophic information. We first give the operational properties of simplified neutrosophic numbers (SNNs). Then, we develop some new information aggregation operators, including an induced simplified neutrosophic correlated averaging (I-SNCA) operator and an induced simplified neutrosophic correlated geometric (I-SNCG) operator. These operators not only consider the importance of elements or their ordered positions, but also take into account the interactions phenomena among decision criteria or their ordered positions under multiple decision-makers. Moreover, we present a detailed analysis of I-SNCA and I-SNCG operators, including the properties of idempotency, commutativity and monotonicity, and study the relationships among the proposed operators and existing simplified neutrosophic aggregation operators. In order to handle the multi-criteria group decision-making (MCGDM) situations where the weights of criteria and decision-makers usually correlative and the criterion values are considered as SNNs, an approach is established based on I-SNCA operator. Finally, a numerical example is presented to demonstrate the proposed approach and to verify its effectiveness and practicality.
NASA Astrophysics Data System (ADS)
Hollmann, Maurice; Mönch, Tobias; Müller, Charles; Bernarding, Johannes
2009-02-01
A major field in cognitive neuroscience investigates neuronal correlates of human decision-making processes [1, 2]. Is it possible to predict a decision before it is actually revealed by the volunteer? In the presented manuscript we use a standard paradigm from economic behavioral research that proved emotional influences on human decision making: the Ultimatum Game (UG). In the UG, two players have the opportunity to split a sum of money. One player is deemed the proposer and the other, the responder. The proposer makes an offer as to how this money should be split between the two. The second player can either accept or reject this offer. If it is accepted, the money is split as proposed. If rejected, then neither player receives anything. In the presented study a real-time fMRI system was used to derive the brain activation of the responder. Using a Relevance-Vector-Machine classifier it was possible to predict if the responder will accept or reject an offer. The classification result was presented to the operator 1-2 seconds before the volunteer pressed a button to convey his decision. The classification accuracy reached about 70% averaged over six subjects.
78 FR 2961 - Proposed Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2013-01-15
... inform or improve consumer financial decision-making. The Bureau expects to collect qualitative data on... education and empowerment programs, leading to better financial decision-making outcomes for adult consumers... financial decisions. DATES: Written comments are encouraged and must be received on or before March 18, 2013...
43 CFR 46.20 - How to use this part.
Code of Federal Regulations, 2010 CFR
2010-10-01
....4501505.2 (b) The Responsible Official will ensure that the decision making process for proposals subject to this part includes appropriate NEPA review. (c) During the decision making process for each... the relevant environmental document. The Responsible Official's decision may combine elements of...
Code of Federal Regulations, 2010 CFR
2010-07-01
... PUBLIC CONTRACTS, DEPARTMENT OF LABOR 203-RULES OF PRACTICE Minimum Wage Determinations Under the Walsh..., and (2) any proposed wage determination. Any tentative decision shall be published in the Federal... wage determination. Any final decision shall be published in the Federal Register. [26 FR 8945, Sept...
Competence, practical rationality and what a patient values.
Craigie, Jillian
2011-07-01
According to the principle of patient autonomy, patients have the right to be self-determining in decisions about their own medical care, which includes the right to refuse treatment. However, a treatment refusal may legitimately be overridden in cases where the decision is judged to be incompetent. It has recently been proposed that in assessments of competence, attention should be paid to the evaluative judgments that guide patients' treatment decisions. In this paper I examine this claim in light of theories of practical rationality, focusing on the difficult case of an anorexic person who is judged to be competent and refuses treatment, thereby putting themselves at risk of serious harm. I argue that the standard criteria for competence assess whether a treatment decision satisfies the goals of practical decision-making, and that this same criterion can be applied to a patient's decision-guiding commitments. As a consequence I propose that a particular understanding of practical rationality offers a theoretical framework for justifying involuntary treatment in the anorexia case. © 2009 Blackwell Publishing Ltd.
A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context
NASA Astrophysics Data System (ADS)
Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul
Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.
Tewary, S; Arun, I; Ahmed, R; Chatterjee, S; Chakraborty, C
2017-11-01
In prognostic evaluation of breast cancer Immunohistochemical (IHC) markers namely, oestrogen receptor (ER) and progesterone receptor (PR) are widely used. The expert pathologist investigates qualitatively the stained tissue slide under microscope to provide the Allred score; which is clinically used for therapeutic decision making. Such qualitative judgment is time-consuming, tedious and more often suffers from interobserver variability. As a result, it leads to imprecise IHC score for ER and PR. To overcome this, there is an urgent need of developing a reliable and efficient IHC quantifier for high throughput decision making. In view of this, our study aims at developing an automated IHC profiler for quantitative assessment of ER and PR molecular expression from stained tissue images. We propose here to use CMYK colour space for positively and negatively stained cell extraction for proportion score. Also colour features are used for quantitative assessment of intensity scoring among the positively stained cells. Five different machine learning models namely artificial neural network, Naïve Bayes, K-nearest neighbours, decision tree and random forest are considered for learning the colour features using average red, green and blue pixel values of positively stained cell patches. Fifty cases of ER- and PR-stained tissues have been evaluated for validation with the expert pathologist's score. All five models perform adequately where random forest shows the best correlation with the expert's score (Pearson's correlation coefficient = 0.9192). In the proposed approach the average variation of diaminobenzidine (DAB) to nuclear area from the expert's score is found to be 7.58%, as compared to 27.83% for state-of-the-art ImmunoRatio software. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.
Légaré, France; Stacey, Dawn; Gagnon, Susie; Dunn, Sandy; Pluye, Pierre; Frosch, Dominick; Kryworuchko, Jennifer; Elwyn, Glyn; Gagnon, Marie-Pierre; Graham, Ian D
2011-01-01
Rationale, aims and objectives Following increased interest in having inter-professional (IP) health care teams engage patients in decision making, we developed a conceptual model for an IP approach to shared decision making (SDM) in primary care. We assessed the validity of the model with stakeholders in Canada. Methods In 15 individual interviews and 7 group interviews with 79 stakeholders, we asked them to: (1) propose changes to the IP-SDM model; (2) identify barriers and facilitators to the model's implementation in clinical practice; and (3) assess the model using a theory appraisal questionnaire. We performed a thematic analysis of the transcripts and a descriptive analysis of the questionnaires. Results Stakeholders suggested placing the patient at its centre; extending the concept of family to include significant others; clarifying outcomes; highlighting the concept of time; merging the micro, meso and macro levels in one figure; and recognizing the influence of the environment and emotions. The most common barriers identified were time constraints, insufficient resources and an imbalance of power among health professionals. The most common facilitators were education and training in inter-professionalism and SDM, motivation to achieve an IP approach to SDM, and mutual knowledge and understanding of disciplinary roles. Most stakeholders considered that the concepts and relationships between the concepts were clear and rated the model as logical, testable, having clear schematic representation, and being relevant to inter-professional collaboration, SDM and primary care. Conclusions Stakeholders validated the new IP-SDM model for primary care settings and proposed few modifications. Future research should assess if the model helps implement SDM in IP clinical practice. PMID:20695950
Hebebrand, Johannes; Holm, Jens-Christian; Woodward, Euan; Baker, Jennifer Lyn; Blaak, Ellen; Schutz, Dominique Durrer; Farpour-Lambert, Nathalie J.; Frühbeck, Gema; Halford, Jason G.C.; Lissner, Lauren; Micic, Dragan; Mullerova, Dana; Roman, Gabriela; Schindler, Karin; Toplak, Hermann; Visscher, Tommy L.S.; Yumuk, Volkan
2017-01-01
Diagnostic criteria for complex medical conditions caused by a multitude of both genetic and environmental factors should be descriptive and avoid any attribution of causality. Furthermore, the wording used to describe a disorder should be evidence-based and avoid stigmatization of the affected individuals. Both terminology and categorizations should be readily comprehensible for healthcare professionals and guide clinical decision making. Uncertainties with respect to diagnostic issues and their implications may be addressed to direct future clinical research. In this context, the European Association of the Study of Obesity (EASO) considers it an important endeavor to review the current ICD-11 Beta Draft for the definition of overweight and obesity and to propose a substantial revision. We aim to provide an overview of the key issues that we deem relevant for the discussion of the diagnostic criteria. We first discuss the current ICD-10 criteria and those proposed in the ICD 11 Beta Draft. We conclude with our own proposal for diagnostic criteria, which we believe will improve the assessment of patients with obesity in a clinically meaningful way. PMID:28738325
NASA Astrophysics Data System (ADS)
Subagadis, Y. H.; Schütze, N.; Grundmann, J.
2014-09-01
The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.
Shame in decision making under risk conditions: Understanding the effect of transparency.
Bonavia, Tomas; Brox-Ponce, Josué
2018-01-01
The role played by the emotion of shame in the area of decision-making in situations of risk has hardly been studied. In this article, we show how the socio-moral emotions and the anticipated feeling of shame associated with different options can determine our decisions, even overriding the cognitive choice tendency proposed by the certainty effect. To do so, we carried out an experiment with university students as participants, dividing them into four experimental conditions. Our findings suggest that people avoid making unethical decisions, both when these decisions are made public to others and when they remain in the private sphere. This result seems to indicate that the main factor in not making unethical decisions is related to the need to avoid transgressing an internal moral standard of behavior, and that the role of transparency is less relevant than expected. However, we propose that, although the effect of transparency is limited in reducing unethical economic decisions, it should continue to be taken into account in theoretical models that address the reasons people behave unethically.
Coleman, C Norman; Blumenthal, Daniel J; Casto, Charles A; Alfant, Michael; Simon, Steven L; Remick, Alan L; Gepford, Heather J; Bowman, Thomas; Telfer, Jana L; Blumenthal, Pamela M; Noska, Michael A
2013-04-01
Resilience after a nuclear power plant or other radiation emergency requires response and recovery activities that are appropriately safe, timely, effective, and well organized. Timely informed decisions must be made, and the logic behind them communicated during the evolution of the incident before the final outcome is known. Based on our experiences in Tokyo responding to the Fukushima Daiichi nuclear power plant crisis, we propose a real-time, medical decision model by which to make key health-related decisions that are central drivers to the overall incident management. Using this approach, on-site decision makers empowered to make interim decisions can act without undue delay using readily available and high-level scientific, medical, communication, and policy expertise. Ongoing assessment, consultation, and adaption to the changing conditions and additional information are additional key features. Given the central role of health and medical issues in all disasters, we propose that this medical decision model, which is compatible with the existing US National Response Framework structure, be considered for effective management of complex, large-scale, and large-consequence incidents.
Shame in decision making under risk conditions: Understanding the effect of transparency
2018-01-01
The role played by the emotion of shame in the area of decision-making in situations of risk has hardly been studied. In this article, we show how the socio-moral emotions and the anticipated feeling of shame associated with different options can determine our decisions, even overriding the cognitive choice tendency proposed by the certainty effect. To do so, we carried out an experiment with university students as participants, dividing them into four experimental conditions. Our findings suggest that people avoid making unethical decisions, both when these decisions are made public to others and when they remain in the private sphere. This result seems to indicate that the main factor in not making unethical decisions is related to the need to avoid transgressing an internal moral standard of behavior, and that the role of transparency is less relevant than expected. However, we propose that, although the effect of transparency is limited in reducing unethical economic decisions, it should continue to be taken into account in theoretical models that address the reasons people behave unethically. PMID:29444107
Regret and the rationality of choices.
Bourgeois-Gironde, Sacha
2010-01-27
Regret helps to optimize decision behaviour. It can be defined as a rational emotion. Several recent neurobiological studies have confirmed the interface between emotion and cognition at which regret is located and documented its role in decision behaviour. These data give credibility to the incorporation of regret in decision theory that had been proposed by economists in the 1980s. However, finer distinctions are required in order to get a better grasp of how regret and behaviour influence each other. Regret can be defined as a predictive error signal but this signal does not necessarily transpose into a decision-weight influencing behaviour. Clinical studies on several types of patients show that the processing of an error signal and its influence on subsequent behaviour can be dissociated. We propose a general understanding of how regret and decision-making are connected in terms of regret being modulated by rational antecedents of choice. Regret and the modification of behaviour on its basis will depend on the criteria of rationality involved in decision-making. We indicate current and prospective lines of research in order to refine our views on how regret contributes to optimal decision-making.
Harris, Claire; Green, Sally; Elshaug, Adam G
2017-09-08
This is the tenth in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. After more than a decade of research, there is little published evidence of active and successful disinvestment. The paucity of frameworks, methods and tools is reported to be a factor in the lack of success. However there are clear and consistent messages in the literature that can be used to inform development of a framework for operationalising disinvestment. This paper, along with the conceptual review of disinvestment in Paper 9 of this series, aims to integrate the findings of the SHARE Program with the existing disinvestment literature to address the lack of information regarding systematic organisation-wide approaches to disinvestment at the local health service level. A framework for disinvestment in a local healthcare setting is proposed. Definitions for essential terms and key concepts underpinning the framework have been made explicit to address the lack of consistent terminology. Given the negative connotations of the word 'disinvestment' and the problems inherent in considering disinvestment in isolation, the basis for the proposed framework is 'resource allocation' to address the spectrum of decision-making from investment to disinvestment. The focus is positive: optimising healthcare, improving health outcomes, using resources effectively. The framework is based on three components: a program for decision-making, projects to implement decisions and evaluate outcomes, and research to understand and improve the program and project activities. The program consists of principles for decision-making and settings that provide opportunities to introduce systematic prompts and triggers to initiate disinvestment. The projects follow the steps in the disinvestment process. Potential methods and tools are presented, however the framework does not stipulate project design or conduct; allowing application of any theories, methods or tools at each step. Barriers are discussed and examples illustrating constituent elements are provided. The framework can be employed at network, institutional, departmental, ward or committee level. It is proposed as an organisation-wide application, embedded within existing systems and processes, which can be responsive to needs and priorities at the level of implementation. It can be used in policy, management or clinical contexts.
An Isometric Mapping Based Co-Location Decision Tree Algorithm
NASA Astrophysics Data System (ADS)
Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.
2018-05-01
Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.
Wang, Ting; Li, Weiying; Zheng, Xiaofeng; Lin, Zhifen; Kong, Deyang
2014-02-01
During the last past decades, there is an increasing number of studies about estrogenic activities of the environmental pollutants on amphibians and many determination methods have been proposed. However, these determination methods are time-consuming and expensive, and a rapid and simple method to screen and test the chemicals for estrogenic activities to amphibians is therefore imperative. Herein is proposed a new decision tree formulated not only with physicochemical parameters but also a biological parameter that was successfully used to screen estrogenic activities of the chemicals on amphibians. The biological parameter, CDOCKER interaction energy (Ebinding ) between chemicals and the target proteins was calculated based on the method of molecular docking, and it was used to revise the decision tree formulated by Hong only with physicochemical parameters for screening estrogenic activity of chemicals in rat. According to the correlation between Ebinding of rat and Xenopus laevis, a new decision tree for estrogenic activities in Xenopus laevis is finally proposed. Then it was validated by using the randomly 8 chemicals which can be frequently exposed to Xenopus laevis, and the agreement between the results from the new decision tree and the ones from experiments is generally satisfactory. Consequently, the new decision tree can be used to screen the estrogenic activities of the chemicals, and combinational use of the Ebinding and classical physicochemical parameters can greatly improves Hong's decision tree. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Management of contaminated marine marketable resources after oil and HNS spills in Europe.
Cunha, Isabel; Neuparth, Teresa; Moreira, Susana; Santos, Miguel M; Reis-Henriques, Maria Armanda
2014-03-15
Different risk evaluation approaches have been used to face oil and hazardous and noxious substances (HNS) spills all over the world. To minimize health risks and mitigate economic losses due to a long term ban on the sale of sea products after a spill, it is essential to preemptively set risk evaluation criteria and standard methodologies based on previous experience and appropriate scientifically sound criteria. Standard methodologies are analyzed and proposed in order to improve the definition of criteria for reintegrating previously contaminated marine marketable resources into the commercialization chain in Europe. The criteria used in former spills for the closing of and lifting of bans on fisheries and harvesting are analyzed. European legislation was identified regarding food sampling, food chemical analysis and maximum levels of contaminants allowed in seafood, which ought to be incorporated in the standard methodologies for the evaluation of the decision criteria defined for oil and HNS spills in Europe. A decision flowchart is proposed that opens the current decision criteria to new material that may be incorporated in the decision process. Decision criteria are discussed and compared among countries and incidents. An a priori definition of risk criteria and an elaboration of action plans are proposed to speed up actions that will lead to prompt final decisions. These decisions, based on the best available scientific data and conducing to lift or ban economic activity, will tend to be better understood and respected by citizens. Copyright © 2014 Elsevier Ltd. All rights reserved.
Decision feedback equalizer for holographic data storage.
Kim, Kyuhwan; Kim, Seung Hun; Koo, Gyogwon; Seo, Min Seok; Kim, Sang Woo
2018-05-20
Holographic data storage (HDS) has attracted much attention as a next-generation storage medium. Because HDS suffers from two-dimensional (2D) inter-symbol interference (ISI), the partial-response maximum-likelihood (PRML) method has been studied to reduce 2D ISI. However, the PRML method has various drawbacks. To solve the problems, we propose a modified decision feedback equalizer (DFE) for HDS. To prevent the error propagation problem, which is a typical problem in DFEs, we also propose a reliability factor for HDS. Various simulations were executed to analyze the performance of the proposed methods. The proposed methods showed fast processing speed after training, superior bit error rate performance, and consistency.
A Chaotic Ordered Hierarchies Consistency Analysis Performance Evaluation Model
NASA Astrophysics Data System (ADS)
Yeh, Wei-Chang
2013-02-01
The Hierarchies Consistency Analysis (HCA) is proposed by Guh in-cooperated along with some case study on a Resort to reinforce the weakness of Analytical Hierarchy Process (AHP). Although the results obtained enabled aid for the Decision Maker to make more reasonable and rational verdicts, the HCA itself is flawed. In this paper, our objective is to indicate the problems of HCA, and then propose a revised method called chaotic ordered HCA (COH in short) which can avoid problems. Since the COH is based upon Guh's method, the Decision Maker establishes decisions in a way similar to that of the original method.
Simulation of California's Major Reservoirs Outflow Using Data Mining Technique
NASA Astrophysics Data System (ADS)
Yang, T.; Gao, X.; Sorooshian, S.
2014-12-01
The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.
Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making
NASA Astrophysics Data System (ADS)
Mohd, Wan Rosanisah Wan; Abdullah, Lazim
2017-11-01
A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weight of the evaluation criteria. Using the linguistic variables, pairwise comparison for evaluation criteria are made to the weights of criteria using Pythagorean fuzzy numbers (PFNs). The proposed method is implemented in the evaluation problem in order to demonstrate its applicability. This study shows that the proposed method provides us with a useful way and a new direction in solving MCDM problems with Pythagorean fuzzy context.
A Planning and Decision-Making Framework for Ecological Restoration.
ERIC Educational Resources Information Center
Wyant, James G.; And Others
1995-01-01
Provides a definition for restoration ecology that is suitable for extensive terrestrial applications and presents a decision framework to help organize different phases of the decision process. Encourages a wider spectrum of participants and decisions than have been traditionally employed for restoration planning. (AIM)
Tong, Xiayu; Wang, Zhou-Jing
2016-09-19
This article develops a group decision framework with intuitionistic preference relations. An approach is first devised to rectify an inconsistent intuitionistic preference relation to derive an additive consistent one. A new aggregation operator, the so-called induced intuitionistic ordered weighted averaging (IIOWA) operator, is proposed to aggregate individual intuitionistic fuzzy judgments. By using the mean absolute deviation between the original and rectified intuitionistic preference relations as an order inducing variable, the rectified consistent intuitionistic preference relations are aggregated into a collective preference relation. This treatment is presumably able to assign different weights to different decision-makers' judgments based on the quality of their inputs (in terms of consistency of their original judgments). A solution procedure is then developed for tackling group decision problems with intuitionistic preference relations. A low carbon supplier selection case study is developed to illustrate how to apply the proposed decision model in practice.
Tong, Xiayu; Wang, Zhou-Jing
2016-01-01
This article develops a group decision framework with intuitionistic preference relations. An approach is first devised to rectify an inconsistent intuitionistic preference relation to derive an additive consistent one. A new aggregation operator, the so-called induced intuitionistic ordered weighted averaging (IIOWA) operator, is proposed to aggregate individual intuitionistic fuzzy judgments. By using the mean absolute deviation between the original and rectified intuitionistic preference relations as an order inducing variable, the rectified consistent intuitionistic preference relations are aggregated into a collective preference relation. This treatment is presumably able to assign different weights to different decision-makers’ judgments based on the quality of their inputs (in terms of consistency of their original judgments). A solution procedure is then developed for tackling group decision problems with intuitionistic preference relations. A low carbon supplier selection case study is developed to illustrate how to apply the proposed decision model in practice. PMID:27657097
Sendi, Pedram; Al, Maiwenn J; Gafni, Amiram; Birch, Stephen
2004-05-01
Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.
Other People’s Money: The Role of Reciprocity and Social Uncertainty in Decisions for Others
2017-01-01
Many important decisions are taken not by the person who will ultimately gain or lose from the outcome, but on their behalf, by somebody else. We examined economic decision-making about risk and time in situations in which deciders chose for others who also chose for them. We propose that this unique setting, which has not been studied before, elicits perception of reciprocity that prompts a unique bias in preferences. We found that decision-makers are less patient (more discounting), and more risk averse for losses than gains, with other peoples’ money, especially when their choices for others are more uncertain. Those results were derived by exploiting a computational modeling framework that has been shown to account for the underlying psychological and neural decision processes. We propose a novel theoretical mechanism—precautionary preferences under social uncertainty, which explains the findings. Implications for future research and alternative models are also discussed. PMID:29456782
A Cross-Layer User Centric Vertical Handover Decision Approach Based on MIH Local Triggers
NASA Astrophysics Data System (ADS)
Rehan, Maaz; Yousaf, Muhammad; Qayyum, Amir; Malik, Shahzad
Vertical handover decision algorithm that is based on user preferences and coupled with Media Independent Handover (MIH) local triggers have not been explored much in the literature. We have developed a comprehensive cross-layer solution, called Vertical Handover Decision (VHOD) approach, which consists of three parts viz. mechanism for collecting and storing user preferences, Vertical Handover Decision (VHOD) algorithm and the MIH Function (MIHF). MIHF triggers the VHOD algorithm which operates on user preferences to issue handover commands to mobility management protocol. VHOD algorithm is an MIH User and therefore needs to subscribe events and configure thresholds for receiving triggers from MIHF. In this regard, we have performed experiments in WLAN to suggest thresholds for Link Going Down trigger. We have also critically evaluated the handover decision process, proposed Just-in-time interface activation technique, compared our proposed approach with prominent user centric approaches and analyzed our approach from different aspects.
Incorporating uncertainty in watershed management decision-making: A mercury TMDL case study
Labiosa, W.; Leckie, J.; Shachter, R.; Freyberg, D.; Rytuba, J.; ,
2005-01-01
Water quality impairment due to high mercury fish tissue concentrations and high mercury aqueous concentrations is a widespread problem in several sub-watersheds that are major sources of mercury to the San Francisco Bay. Several mercury Total Maximum Daily Load regulations are currently being developed to address this problem. Decisions about control strategies are being made despite very large uncertainties about current mercury loading behavior, relationships between total mercury loading and methyl mercury formation, and relationships between potential controls and mercury fish tissue levels. To deal with the issues of very large uncertainties, data limitations, knowledge gaps, and very limited State agency resources, this work proposes a decision analytical alternative for mercury TMDL decision support. The proposed probabilistic decision model is Bayesian in nature and is fully compatible with a "learning while doing" adaptive management approach. Strategy evaluation, sensitivity analysis, and information collection prioritization are examples of analyses that can be performed using this approach.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-06
... DEPARTMENT OF DEFENSE Department of the Air Force Record of Decision for the White Elk Military... Availability (NOA) of a Record of Decision (ROD). SUMMARY: On November 4, 2011, the United States Air Force... states the Air Force decision to select the Proposed Action to establish the White Elk MOA airspace...
Putting It All Together: A Unified Account of Word Recognition and Reaction-Time Distributions
ERIC Educational Resources Information Center
Norris, Dennis
2009-01-01
R. Ratcliff, P. Gomez, and G. McKoon (2004) suggested much of what goes on in lexical decision is attributable to decision processes and may not be particularly informative about word recognition. They proposed that lexical decision should be characterized by a decision process, taking the form of a drift-diffusion model (R. Ratcliff, 1978), that…
Rajavel, Rajkumar; Thangarathinam, Mala
2015-01-01
Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework. PMID:26543899
Rajavel, Rajkumar; Thangarathinam, Mala
2015-01-01
Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework.
Decision-making capacity should not be decisive in emergencies.
Hubbeling, Dieneke
2014-05-01
Examples of patients with anorexia nervosa, depression or borderline personality disorder who have decision-making capacity as currently operationalized, but refuse treatment, are discussed. It appears counterintuitive to respect their treatment refusal because their wish seems to be fuelled by their illness and the consequences of their refusal of treatment are severe. Some proposed solutions have focused on broadening the criteria for decision-making capacity, either in general or for specific patient groups, but these adjustments might discriminate against particular groups of patients and render the process less transparent. Other solutions focus on preferences expressed when patients are not ill, but this information is often not available. The reason for such difficulties with assessing decision-making capacity is that the underlying psychological processes of normal decision-making are not well known and one cannot differentiate between unwise decisions caused by an illness or other factors. The proposed alternative, set out in this paper, is to allow compulsory treatment of patients with decision-making capacity in cases of an emergency, if the refusal is potentially life threatening, but only for a time-limited period. The argument is also made for investigating hindsight agreement, in particular after compulsory measures.
Quantum-Like Bayesian Networks for Modeling Decision Making
Moreira, Catarina; Wichert, Andreas
2016-01-01
In this work, we explore an alternative quantum structure to perform quantum probabilistic inferences to accommodate the paradoxical findings of the Sure Thing Principle. We propose a Quantum-Like Bayesian Network, which consists in replacing classical probabilities by quantum probability amplitudes. However, since this approach suffers from the problem of exponential growth of quantum parameters, we also propose a similarity heuristic that automatically fits quantum parameters through vector similarities. This makes the proposed model general and predictive in contrast to the current state of the art models, which cannot be generalized for more complex decision scenarios and that only provide an explanatory nature for the observed paradoxes. In the end, the model that we propose consists in a nonparametric method for estimating inference effects from a statistical point of view. It is a statistical model that is simpler than the previous quantum dynamic and quantum-like models proposed in the literature. We tested the proposed network with several empirical data from the literature, mainly from the Prisoner's Dilemma game and the Two Stage Gambling game. The results obtained show that the proposed quantum Bayesian Network is a general method that can accommodate violations of the laws of classical probability theory and make accurate predictions regarding human decision-making in these scenarios. PMID:26858669
Automatic rule generation for high-level vision
NASA Technical Reports Server (NTRS)
Rhee, Frank Chung-Hoon; Krishnapuram, Raghu
1992-01-01
A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.
36 CFR 251.83 - Decisions not appealable.
Code of Federal Regulations, 2011 CFR
2011-07-01
...); and 4 CFR part 21 (Bid Protests). (f) Decisions pursuant to Office of Management and Budget Circular A... proposed action. (l) Decisions related to National Forest land and resource management plans and projects... such as wildfires, severe wind, earthquakes, and flooding when the Regional Forester or, in situations...
36 CFR 251.83 - Decisions not appealable.
Code of Federal Regulations, 2012 CFR
2012-07-01
...); and 4 CFR part 21 (Bid Protests). (f) Decisions pursuant to Office of Management and Budget Circular A... proposed action. (l) Decisions related to National Forest land and resource management plans and projects... such as wildfires, severe wind, earthquakes, and flooding when the Regional Forester or, in situations...
36 CFR 251.83 - Decisions not appealable.
Code of Federal Regulations, 2010 CFR
2010-07-01
...); and 4 CFR part 21 (Bid Protests). (f) Decisions pursuant to Office of Management and Budget Circular A... proposed action. (l) Decisions related to National Forest land and resource management plans and projects... such as wildfires, severe wind, earthquakes, and flooding when the Regional Forester or, in situations...
On the Composition of Risk Preference and Belief
ERIC Educational Resources Information Center
Wakkar, Peter P.
2004-01-01
Prospect theory assumes nonadditive decision weights for preferences over risky gambles. Such decision weights generalize additive probabilities. This article proposes a decomposition of decision weights into a component reflecting risk attitude and a new component depending on belief. The decomposition is based on an observable preference…
44 CFR 10.12 - Pre-implementation actions.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Pre-implementation actions. (a) Decision-making. The Regional Administrator shall ensure that... integrated into the decision-making process. Because of the diversity of FEMA, it is not feasible to describe in this part the decision-making process for each of the various FEMA programs. Proposals and actions...
77 FR 6092 - Proposed Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-07
... systems which provide a way to compare surveillance and detection equipment and make informed purchasing decisions. Due to rapid changes and inventions in technology, the market survey must be updated to ensure... will be analyzed by a team of subject matter experts in detection and decision analysis. Decision...
NASA Astrophysics Data System (ADS)
Belkadi, Farouk; Messaadia, Mourad; Bernard, Alain; Baudry, David
2017-08-01
Due to the increased competitiveness and the diversity of requirements in today's markets, manufacturing companies need to join their competencies and resources to propose innovative solutions for each specific market, with the possibility to transpose these solutions to another market, by means of slight adaptations. Thus, manufacturing firms must constantly conduct new collaborations with known partners in most cases, but also with new partners. The critical question for managers in this latter case is how to define the best collaborative strategy according to the goals of the project and the specificity of the target market. This paper tackles the problem by proposing a conceptual framework for supporting the management of collaborative situations in the case of Original equipment manufacturers (OEMs). Based on the concept of trust level, the framework proposes a classification of different collaboration modes to be adopted in various contexts of inter-enterprise relationships, in manufacturing sector. The aim is to support the flexible navigation between different collaborative situations by taking into account all decision-making levels from the strategy to the implementation of the information technologies (IT) systems at the operational level.
A Hybrid Cellular Genetic Algorithm for Multi-objective Crew Scheduling Problem
NASA Astrophysics Data System (ADS)
Jolai, Fariborz; Assadipour, Ghazal
Crew scheduling is one of the important problems of the airline industry. This problem aims to cover a number of flights by crew members, such that all the flights are covered. In a robust scheduling the assignment should be so that the total cost, delays, and unbalanced utilization are minimized. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimization method. The proposed algorithm provides the decision maker with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Evaluating the performance of the proposed algorithm, three metrics are suggested, and the diversity and the convergence of the achieved Pareto front are appraised. Finally a comparison is made between CellDE and PAES, another meta-heuristic algorithm. The results show the superiority of CellDE.
NASA Astrophysics Data System (ADS)
Cui, Lingli; Gong, Xiangyang; Zhang, Jianyu; Wang, Huaqing
2016-12-01
The quantitative diagnosis of rolling bearing fault severity is particularly crucial to realize a proper maintenance decision. Aiming at the fault feature of rolling bearing, a novel double-dictionary matching pursuit (DDMP) for fault extent evaluation of rolling bearing based on the Lempel-Ziv complexity (LZC) index is proposed in this paper. In order to match the features of rolling bearing fault, the impulse time-frequency dictionary and modulation dictionary are constructed to form the double-dictionary by using the method of parameterized function model. Then a novel matching pursuit method is proposed based on the new double-dictionary. For rolling bearing vibration signals with different fault sizes, the signals are decomposed and reconstructed by the DDMP. After the noise reduced and signals reconstructed, the LZC index is introduced to realize the fault extent evaluation. The applications of this method to the fault experimental signals of bearing outer race and inner race with different degree of injury have shown that the proposed method can effectively realize the fault extent evaluation.
Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals
Zhao, Ming; Lin, Jing; Miao, Yonghao; Xu, Xiaoqiang
2016-01-01
Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how this information could be properly integrated to achieve a more reliable maintenance decision. Aiming at this problem, a framework of R/C signals analysis is presented for the health assessment of gearbox. In the proposed methodology, we first investigate the data preprocessing and feature selection issues for R/C signals. Based on that, a sparsity-guided feature enhancement scheme is then proposed to extract the weak phase jitter associated with gear defect. In order for an effective feature mining and integration under R/C, a generalized phase demodulation technique is further established to reveal the evolution of modulation feature with operating speed and rotation angle. The experimental results indicate that the proposed methodology could not only detect the presence of gear damage, but also offer a novel insight into the dynamic behavior of gearbox. PMID:27827831
Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals.
Zhao, Ming; Lin, Jing; Miao, Yonghao; Xu, Xiaoqiang
2016-11-02
Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how this information could be properly integrated to achieve a more reliable maintenance decision. Aiming at this problem, a framework of R/C signals analysis is presented for the health assessment of gearbox. In the proposed methodology, we first investigate the data preprocessing and feature selection issues for R/C signals. Based on that, a sparsity-guided feature enhancement scheme is then proposed to extract the weak phase jitter associated with gear defect. In order for an effective feature mining and integration under R/C, a generalized phase demodulation technique is further established to reveal the evolution of modulation feature with operating speed and rotation angle. The experimental results indicate that the proposed methodology could not only detect the presence of gear damage, but also offer a novel insight into the dynamic behavior of gearbox.
Real-time energy-saving metro train rescheduling with primary delay identification
Li, Keping; Schonfeld, Paul
2018-01-01
This paper aims to reschedule online metro trains in delay scenarios. A graph representation and a mixed integer programming model are proposed to formulate the optimization problem. The solution approach is a two-stage optimization method. In the first stage, based on a proposed train state graph and system analysis, the primary and flow-on delays are specifically analyzed and identified with a critical path algorithm. For the second stage a hybrid genetic algorithm is designed to optimize the schedule, with the delay identification results as input. Then, based on the infrastructure data of Beijing Subway Line 4 of China, case studies are presented to demonstrate the effectiveness and efficiency of the solution approach. The results show that the algorithm can quickly and accurately identify primary delays among different types of delays. The economic cost of energy consumption and total delay is considerably reduced (by more than 10% in each case). The computation time of the Hybrid-GA is low enough for rescheduling online. Sensitivity analyses further demonstrate that the proposed approach can be used as a decision-making support tool for operators. PMID:29474471
NASA Astrophysics Data System (ADS)
Ueda, Keiichi; Kurahashi, Setsuya
2018-02-01
The continuous development of the service economy and an aging society with fewer children is expected to lead to a shortage of workers in the near future. In addition, the growth of the service economy would require service providers to meet various service requirements. In this regard, self-service technology (SST) is a promising alternative to securing labor in both developed and emerging countries. SST is expected to coordinate the controllable productive properties in order to optimize resources and minimize consumer stress. As services are characterized by simultaneity and inseparability, a smoother operation in cooperation with the consumer is required to provide a certain level of service. This study focuses on passenger handling in an airport departure lobby with the objective of optimizing multiple service resources comprising interpersonal service staff and self-service kiosks. Our aim is to elucidate the passenger decision- making mechanism of choosing either interpersonal service or self-service as the check-in option, and to apply it to analyze several scenarios to determine the best practice. The experimental space is studied and an agent-based model is proposed to analyze the operational efficiency via a simulation. We expand on a previous SST adoption model, which is enhanced by introducing the concept of individual traits. We focus on the decision-making of individuals who are neutral toward the service option, by tracking the actual activity of passengers and mapping their behavior into the model. A new method of validation that follows a different approach is proposed to ensure that this model approximates real-world situations. A scenario analysis is then carried out with the aim of exploring the best operational practice to minimize the stress experienced by the air travelers and to meet the business needs of the airline managers at the airport. We collected actual data from the Departure Control System of an airline to map the real-world data to the proposed model. Passenger behavior was extracted by front-line service experts and clarified through consecutive on-site observations.
NASA Technical Reports Server (NTRS)
DeMott, Diana; Fuqua, Bryan; Wilson, Paul
2013-01-01
Once a project obtains approval, decision makers have to consider a variety of alternative paths for completing the project and meeting the project objectives. How decisions are made involves a variety of elements including: cost, experience, current technology, ideologies, politics, future needs and desires, capabilities, manpower, timing, available information, and for many ventures management needs to assess the elements of risk versus reward. The use of high level Probabilistic Risk Assessment (PRA) Models during conceptual design phases provides management with additional information during the decision making process regarding the risk potential for proposed operations and design prototypes. The methodology can be used as a tool to: 1) allow trade studies to compare alternatives based on risk, 2) determine which elements (equipment, process or operational parameters) drives the risk, and 3) provide information to mitigate or eliminate risks early in the conceptual design to lower costs. Creating system models using conceptual design proposals and generic key systems based on what is known today can provide an understanding of the magnitudes of proposed systems and operational risks and facilitates trade study comparisons early in the decision making process. Identifying the "best" way to achieve the desired results is difficult, and generally occurs based on limited information. PRA provides a tool for decision makers to explore how some decisions will affect risk before the project is committed to that path, which can ultimately save time and money.
Gouin, Marie-Michelle; Coutu, Marie-France; Durand, Marie-José
2017-11-12
Collective decision-making by stakeholders appears important to return-to-work success, yet few studies have explored the processes involved. This study aims to explore the influence of decision-making on return-to-work for workers with musculoskeletal or common mental disorders. This study is a secondary analysis using data from three earlier multiple-case studies that documented decision-making during similar and comparable work rehabilitation programs. Individual interviews were conducted at the end of the program with stakeholders, namely, the disabled workers and representatives of health care professionals, employers, unions and insurers. Verbatims were analysed inductively. The 28 decision-making processes (cases) led to 115 different decisions-making instances and included the following components: subjects of the decisions, stakeholders' concerns and powers, and types of decision-making. No differences were found in decision-making processes relative to the workers' diagnoses or return-to-work status. However, overall analysis of decision-making revealed that stakeholder agreement on a return-to-work goal and acceptance of an intervention plan in which the task demands aligned with the worker's capacities were essential for return-to-work success. These results support the possibility of return-to-work success despite conflictual decision-making processes. In addition to facilitating consensual decisions, future studies should be aimed at facilitating negotiated decisions. Implications for rehabilitation Facilitating decision-making, with the aim of obtaining agreement from all stakeholders on a return-to-work goal and their acceptance of an intervention plan that respects the worker's capacities, is important for return-to-work success. Rehabilitation professionals should constantly be on the lookout for potential conflicts, which may either complicate the reach of an agreement between the stakeholders or constrain return-to-work possibilities. Rehabilitation professionals should also be constantly watching for workers' and employers' return-to-work concerns, as they may change during work rehabilitation, potentially challenging a reached agreement.
Intelligent Local Avoided Collision (iLAC) MAC Protocol for Very High Speed Wireless Network
NASA Astrophysics Data System (ADS)
Hieu, Dinh Chi; Masuda, Akeo; Rabarijaona, Verotiana Hanitriniala; Shimamoto, Shigeru
Future wireless communication systems aim at very high data rates. As the medium access control (MAC) protocol plays the central role in determining the overall performance of the wireless system, designing a suitable MAC protocol is critical to fully exploit the benefit of high speed transmission that the physical layer (PHY) offers. In the latest 802.11n standard [2], the problem of long overhead has been addressed adequately but the issue of excessive colliding transmissions, especially in congested situation, remains untouched. The procedure of setting the backoff value is the heart of the 802.11 distributed coordination function (DCF) to avoid collision in which each station makes its own decision on how to avoid collision in the next transmission. However, collision avoidance is a problem that can not be solved by a single station. In this paper, we introduce a new MAC protocol called Intelligent Local Avoided Collision (iLAC) that redefines individual rationality in choosing the backoff counter value to avoid a colliding transmission. The distinguishing feature of iLAC is that it fundamentally changes this decision making process from collision avoidance to collaborative collision prevention. As a result, stations can avoid colliding transmissions with much greater precision. Analytical solution confirms the validity of this proposal and simulation results show that the proposed algorithm outperforms the conventional algorithms by a large margin.
Gong, Xinyu; Xia, Ling-Xiang; Sun, Yanlin; Guo, Lei; Carpenter, Vanessa C; Fang, Yuan; Chen, Yunli
2017-01-01
Interpersonal responsibility is an indigenous Chinese personality construct, which is regarded to have positive social functions. Two studies were designed to explore the relationship among interpersonal responsibility, proposal allocation ratio, and responders' hostile decisions in an ultimatum game. Study 1 was a scenario study using a hypothetical ultimatum game with a valid sample of 551 high school students. Study 2 was an experimental study which recruited 54 undergraduate students to play the incentivized ultimatum game online. The results of the two studies showed a significantly negative correlation between interpersonal responsibility and responders' rejection responses only when the proposal allocation ratio was 3:7. In addition, in Study 2, interpersonal responsibility had negative effects on responders' rejection responses under the offer of 3:7, even after controlling for the Big Five personality traits. Taken together, proposal allocation ratio might moderate the effects of interpersonal responsibility on hostile decision-making in the ultimatum game. The social function of interpersonal responsibility might be beyond the Big Five.
Evolution of Fairness in the Not Quite Ultimatum Game
NASA Astrophysics Data System (ADS)
Ichinose, Genki; Sayama, Hiroki
2014-05-01
The Ultimatum Game (UG) is an economic game where two players (proposer and responder) decide how to split a certain amount of money. While traditional economic theories based on rational decision making predict that the proposer should make a minimal offer and the responder should accept it, human subjects tend to behave more fairly in UG. Previous studies suggested that extra information such as reputation, empathy, or spatial structure is needed for fairness to evolve in UG. Here we show that fairness can evolve without additional information if players make decisions probabilistically and may continue interactions when the offer is rejected, which we call the Not Quite Ultimatum Game (NQUG). Evolutionary simulations of NQUG showed that the probabilistic decision making contributes to the increase of proposers' offer amounts to avoid rejection, while the repetition of the game works to responders' advantage because they can wait until a good offer comes. These simple extensions greatly promote evolution of fairness in both proposers' offers and responders' acceptance thresholds.
Knox, Lucy; Douglas, Jacinta M; Bigby, Christine
2017-11-01
Although adults who sustain a severe traumatic brain injury (TBI) require support to make decisions in their lives, little is known about their experience of this process. The aim of this study was to explore how participation in decision making contributes to self-conceptualization in adults with severe TBI. We used constructivist grounded theory methods. Data included 20 in-depth interviews with adults with severe TBI. Through a process of constant comparison, analysis involved open and focused coding until clear categories emerged and data saturation was achieved. Self-conceptualization emerged as a complex and multifaceted process, as individuals with TBI aimed to reestablish a sense of autonomy. We describe a recursive relationship in which decision-making participation assists the dynamic construction of self, and self-concept contributes to the experience of making decisions. The role of an individual's social support network in acting as a bridge between participation and self-conceptualization is presented. Findings emphasize that contributing to decisions about one's own goals across a range of life areas can reinforce a positive self-concept. It is vital that supporters understand that participation in decision making provides a pathway to conceptualizing self and aim to maximize the person's participation in the decision-making process. Implications for Rehabilitation Previous research has identified that the experience of sustaining TBI has a significant impact on a person's conceptualization of self. This study identified that decision-making experiences play an important role in the ongoing process of self-conceptualization after injury. Decision-making experiences can reinforce a person's self-concept or lead them to revise (positively or negatively) their sense of self. By maximizing the person's decision-making participation, those around them can support them to develop positive self-attributes and contribute to shaping their future goals.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Hu-Chen; Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo 152-8552; Wu, Jing
Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires considerationmore » of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way.« less
Sex and the money--How gender stereotypes modulate economic decision-making: An ERP study.
Fabre, Eve F; Causse, Mickael; Pesciarelli, Francesca; Cacciari, Cristina
2015-08-01
In the present event-related potential study, we investigated whether and how participants playing the ultimatum game as responders modulate their decisions according to the proposers' stereotypical identity. The proposers' identity was manipulated using occupational role nouns stereotypically marked with gender (e.g., Teacher; Engineer), paired with either feminine or masculine proper names (e.g., Anna; David). Greater FRN amplitudes reflected the early processing of the conflict between the strategic rule (i.e., earning as much money as possible) and ready-to-go responses (i.e., refusing unequal offers and discriminating proposers according to their stereotype). Responders were found to rely on a dual-process system (i.e., automatic and heuristic-based system 1 vs. cognitively costly and deliberative system 2), the P300 amplitude reflecting the switch from a decision making system to another. Greater P300 amplitudes were found in response to both fair and unfair offers and male-stereotyped proposers' offers reflecting an automatic decision making based on heuristics, while lower P300 amplitudes were found in response to 3€ offers and the female-stereotyped proposers' offers reflecting a more deliberative reasoning. Overall, the results indicate that participants were more motivated to engage in a costly deliberative reasoning associated with an increase in acceptation rate when playing with female-stereotyped proposers, who may have induced more positive and emphatic feelings in the participants than did male-stereotyped proposers. Then, we assume that people with an occupation stereotypically marked with female gender and engaged in an economic negotiation may benefit from their occupation at least in the case their counterparts lose their money if the negotiation fails. Copyright © 2015 Elsevier Ltd. All rights reserved.
Locally adaptive decision in detection of clustered microcalcifications in mammograms.
Sainz de Cea, María V; Nishikawa, Robert M; Yang, Yongyi
2018-02-15
In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value <10 -4 ). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.
Locally adaptive decision in detection of clustered microcalcifications in mammograms
NASA Astrophysics Data System (ADS)
Sainz de Cea, María V.; Nishikawa, Robert M.; Yang, Yongyi
2018-02-01
In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value <10-4). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.
Kimmel, Allison L; Wang, Jichuan; Scott, Rachel K; Briggs, Linda; Lyon, Maureen E
2015-07-01
Although the human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) has become a chronic illness, disease-specific advance care planning has not yet been evaluated for the palliative care needs of adults with HIV/AIDS. This prospective, longitudinal, randomized, two-arm controlled clinical trial aims to test the efficacy of FAmily CEntered advance care planning among adults living with AIDS and/or HIV with co-morbidities on congruence in treatment preferences, healthcare utilization, and quality of life. The FAmily CEntered intervention arm is two face-to-face sessions with a trained, certified facilitator: Session 1) Disease-Specific Advance Care Planning Respecting Choices Interview; Session 2) Completion of advance directive. The Healthy Living Control arm is: Session 1) Developmental/Relationship History; Session 2) Nutrition. Follow-up data will be collected at 3, 6, 12, and 18 months post-intervention. A total of 288 patient/surrogate dyads will be enrolled from five hospital-based, out-patient clinics in Washington, District of Columbia. Participants will be HIV positive and ≥ 21 years of age; surrogates will be ≥ 18 years of age. Exclusion criteria are homicidality, suicidality, psychosis, and impaired cognitive functioning. We hypothesize that this intervention will enhance patient-centered communication with a surrogate decision-maker about end of life treatment preferences over time, enhance patient quality of life and decrease health care utilization. We further hypothesize that this intervention will decrease health disparities for Blacks in completion of advance directives. If proposed aims are achieved, the benefits of palliative care, particularly increased treatment preferences about end-of-life care and enhanced quality of life, will be extended to people living with AIDS. Copyright © 2015 Elsevier Inc. All rights reserved.
Disentangling Decision Models: From Independence to Competition
ERIC Educational Resources Information Center
Teodorescu, Andrei R.; Usher, Marius
2013-01-01
A multitude of models have been proposed to account for the neural mechanism of value integration and decision making in speeded decision tasks. While most of these models account for existing data, they largely disagree on a fundamental characteristic of the choice mechanism: independent versus different types of competitive processing. Five…
Philosophy versus Student Need? A Reply to Smith and Hilton.
ERIC Educational Resources Information Center
Rainforth, Beverly
1994-01-01
This response to Smith and Hilton (1994) suggests that those authors reject philosophical bases for decision making regarding program design for students with mental retardation while actually proposing their own philosophical base for such decision making. The importance of philosophy in guiding decisions and practice over the last several…
ERIC Educational Resources Information Center
Huang, Jie-Tsuen
2015-01-01
Past empirical evidence has demonstrated that personality traits predict career decision self-efficacy. This study extends previous research by proposing and testing a model that examines the mediating roles of perceived internal and external employability on the relationship between personality hardiness and career decision self-efficacy. Using…
School-Based Decision Making: A Principal-Agent Perspective.
ERIC Educational Resources Information Center
Ferris, James M.
1992-01-01
A principal-agent framework is used to examine potential gains in educational performance and potential threats to public accountability that school-based decision-making proposals pose. Analysis underscores the need to tailor the design of decentralized decision making to the sources of poor educational performance and threats to school…
Hyltoft Petersen, Per; Klee, George G
2014-03-20
Diagnostic decisions based on decision limits according to medical guidelines are different from the majority of clinical decisions due to the strict dichotomization of patients into diseased and non-diseased. Consequently, the influence of analytical performance is more critical than for other diagnostic decisions where much other information is included. The aim of this opinion paper is to investigate consequences of analytical quality and other circumstances for the outcome of "Guideline-Driven Medical Decision Limits". Effects of analytical bias and imprecision should be investigated separately and analytical quality specifications should be estimated accordingly. Use of sharp decision limits doesn't consider biological variation and effects of this variation are closely connected with the effects of analytical performance. Such relationships are investigated for the guidelines for HbA1c in diagnosis of diabetes and in risk of coronary heart disease based on serum cholesterol. The effects of a second sampling in diagnosis give dramatic reduction in the effects of analytical quality showing minimal influence of imprecision up to 3 to 5% for two independent samplings, whereas the reduction in bias is more moderate and a 2% increase in concentration doubles the percentage of false positive diagnoses, both for HbA1c and cholesterol. An alternative approach comes from the current application of guidelines for follow-up laboratory tests according to clinical procedure orders, e.g. frequency of parathyroid hormone requests as a function of serum calcium concentrations. Here, the specifications for bias can be evaluated from the functional increase in requests for increasing serum calcium concentrations. In consequence of the difficulties with biological variation and the practical utilization of concentration dependence of frequency of follow-up laboratory tests already in use, a kind of probability function for diagnosis as function of the key-analyte is proposed. Copyright © 2013 Elsevier B.V. All rights reserved.
Hyltoft Petersen, Per; Klee, George G
2014-05-15
Diagnostic decisions based on decision limits according to medical guidelines are different from the majority of clinical decisions due to the strict dichotomization of patients into diseased and non-diseased. Consequently, the influence of analytical performance is more critical than for other diagnostic decisions where much other information is included. The aim of this opinion paper is to investigate consequences of analytical quality and other circumstances for the outcome of "Guideline-Driven Medical Decision Limits". Effects of analytical bias and imprecision should be investigated separately and analytical quality specifications should be estimated accordingly. Use of sharp decision limits doesn't consider biological variation and effects of this variation are closely connected with the effects of analytical performance. Such relationships are investigated for the guidelines for HbA1c in diagnosis of diabetes and in risk of coronary heart disease based on serum cholesterol. The effects of a second sampling in diagnosis give dramatic reduction in the effects of analytical quality showing minimal influence of imprecision up to 3 to 5% for two independent samplings, whereas the reduction in bias is more moderate and a 2% increase in concentration doubles the percentage of false positive diagnoses, both for HbA1c and cholesterol. An alternative approach comes from the current application of guidelines for follow-up laboratory tests according to clinical procedure orders, e.g. frequency of parathyroid hormone requests as a function of serum calcium concentrations. Here, the specifications for bias can be evaluated from the functional increase in requests for increasing serum calcium concentrations. In consequence of the difficulties with biological variation and the practical utilization of concentration dependence of frequency of follow-up laboratory tests already in use, a kind of probability function for diagnosis as function of the key-analyte is proposed. Copyright © 2014. Published by Elsevier B.V.
A contemporary approach to validity arguments: a practical guide to Kane's framework.
Cook, David A; Brydges, Ryan; Ginsburg, Shiphra; Hatala, Rose
2015-06-01
Assessment is central to medical education and the validation of assessments is vital to their use. Earlier validity frameworks suffer from a multiplicity of types of validity or failure to prioritise among sources of validity evidence. Kane's framework addresses both concerns by emphasising key inferences as the assessment progresses from a single observation to a final decision. Evidence evaluating these inferences is planned and presented as a validity argument. We aim to offer a practical introduction to the key concepts of Kane's framework that educators will find accessible and applicable to a wide range of assessment tools and activities. All assessments are ultimately intended to facilitate a defensible decision about the person being assessed. Validation is the process of collecting and interpreting evidence to support that decision. Rigorous validation involves articulating the claims and assumptions associated with the proposed decision (the interpretation/use argument), empirically testing these assumptions, and organising evidence into a coherent validity argument. Kane identifies four inferences in the validity argument: Scoring (translating an observation into one or more scores); Generalisation (using the score[s] as a reflection of performance in a test setting); Extrapolation (using the score[s] as a reflection of real-world performance), and Implications (applying the score[s] to inform a decision or action). Evidence should be collected to support each of these inferences and should focus on the most questionable assumptions in the chain of inference. Key assumptions (and needed evidence) vary depending on the assessment's intended use or associated decision. Kane's framework applies to quantitative and qualitative assessments, and to individual tests and programmes of assessment. Validation focuses on evaluating the key claims, assumptions and inferences that link assessment scores with their intended interpretations and uses. The Implications and associated decisions are the most important inferences in the validity argument. © 2015 John Wiley & Sons Ltd.
Mental competence and surrogate decision-making towards the end of life.
Strätling, M; Scharf, V E; Schmucker, P
2004-01-01
German legislation demands that decisions about the treatment of mentally incompetent patients require an 'informed consent'. If this was not given by the patient him-/herself before he/she became incompetent, it has to be sought by the physician from a guardian, who has to be formally legitimized before. Additionally this surrogate has to seek the permission of a Court of Guardianship (Vormundschaftsgericht), if he/she intends to consent to interventions, which pose significant risks to the health or the life of the person under his/her care. This includes 'end-of-life decisions'. Deviations from this procedure are only allowed in acute emergencies or cases of 'medical futility'. On the basis of epidemiological and demographical data it can be shown that the vast majority of surrogate decisions on incompetent patients in Germany is not covered by legally valid consent. Moreover, the data suggests that if consent were to be requested according to the legal regulations, both the legal and medical system could realistically never cope with the practical consequences of this. Additionally, empiric research has revealed serious deficits concerning medical 'end of life-decisions' and practical performance in palliative care. As a consequence a multidisciplinary discussion has developed in Germany about the reform of present legislation with respect to key-issues like the assessment of mental competence, the options for exercising patient self-determination via advance directives and durable powers of attorney, the improvement of palliative care facilities, the clarification of formal procedures for surrogate decision-making in health care and towards the end of life and the possibilities and their limitations of controlling these decision-making processes 'externally' (e.g., by Guardianship Courts or committees). The authors discuss those proposals, which clearly dominate the present debate: They all aim to comply with the scientific basis of German law, jurisdiction and the European traditions of philosophy of health care and bioethics.
75 FR 3233 - Sulfometuron Methyl Amendment to Reregistration Eligibility Decision
Federal Register 2010, 2011, 2012, 2013, 2014
2010-01-20
... specified in the 2008 Reregistration Eligibility Decision (RED) for the herbicide sulfometuron methyl. EPA... making process for this herbicide. Stakeholder comments, mitigation proposals, and other information...
Code of Federal Regulations, 2010 CFR
2010-07-01
..., allowing public review and comment on the proposal and providing a basis for informed decision-making. (b) The NEPA process should support sound, informed, and timely (early) decision-making; not produce...
Vlachopoulou, M; Coughlin, D; Forrow, D; Kirk, S; Logan, P; Voulvoulis, N
2014-02-01
The Ecosystem Approach provides a framework for looking at whole ecosystems in decision making to ensure that society can maintain a healthy and resilient natural environment now and for future generations. Although not explicitly mentioned in the Water Framework Directive, the Ecosystem Approach appears to be a promising concept to help its implementation, on the basis that there is a connection between the aims and objectives of the Directive (including good ecological status) and the provision of ecosystem services. In this paper, methodological linkages between the Ecosystem Approach and the Water Framework Directive have been reviewed and a framework is proposed that links its implementation to the Ecosystem Approach taking into consideration all ecosystem services and water management objectives. Individual River Basin Management Plan objectives are qualitatively assessed as to how strong their link is with individual ecosystem services. The benefits of using this approach to provide a preliminary assessment of how it could support future implementation of the Directive have been identified and discussed. Findings also demonstrate its potential to encourage more systematic and systemic thinking as it can provide a consistent framework for identifying shared aims and evaluating alternative water management scenarios and options in decision making. Allowing for a broad consideration of the benefits, costs and tradeoffs that occur in each case, this approach can further improve the economic case for certain measures, and can also help restore the shift in focus from strict legislative compliance towards a more holistic implementation that can deliver the wider aims and intentions of the Directive. © 2013.
Consumer's Online Shopping Influence Factors and Decision-Making Model
NASA Astrophysics Data System (ADS)
Yan, Xiangbin; Dai, Shiliang
Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.
NASA Astrophysics Data System (ADS)
Lei, Ted Chih-Wei; Tseng, Fan-Shuo
2017-07-01
This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.
What Learning Environments Help Improve Decision-Making?
ERIC Educational Resources Information Center
O'Connor, Donna; Larkin, Paul; Williams, A. Mark
2017-01-01
Background: Decision-making is a key component of performance in sport. However, there has been minimal investigation of how coaches may adapt practice sessions to specifically develop decision-making. Purpose: The aim in this exploratory study was to investigate the pedagogical approaches coaches use to develop decision-making in soccer. Method:…
Sorgner, Helene
2016-06-01
This paper compares Feyerabend's arguments in Science in a Free Society to the controversial theory of expertise proposed by Harry Collins and Robert Evans as a Third Wave of Science Studies. Is the legitimacy of democratic decisions threatened by the unquestioned authority of scientific advice? Or does, on the contrary, science need protection from too much democratic participation in technical decisions? Where Feyerabend's political relativism envisions democratic society as inherently pluralist and demands equal contribution of all traditions and worldviews to public decision-making, Collins and Evans hold a conception of elective modernism, defending the reality and value of technical expertise and arguing that science deserves a privileged status in modern democracies, because scientific values are also democratic values. I will argue that Feyerabend's political relativism provides a valuable framework for the evaluation of Collins' and Evans' theory of expertise. By constructing a dialog between Feyerabend and this more recent approach in Science and Technology Studies, the aim of this article is not only to show where the two positions differ and in what way they might be reconciled, but also how Feyerabend's philosophy provides substantial input to contemporary debate. Copyright © 2015 Elsevier Ltd. All rights reserved.
Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel
2008-01-01
With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.
The evaluation and enhancement of quality, environmental protection and seaport safety by using FAHP
NASA Astrophysics Data System (ADS)
Tadic, Danijela; Aleksic, Aleksandar; Popovic, Pavle; Arsovski, Slavko; Castelli, Ana; Joksimovic, Danijela; Stefanovic, Miladin
2017-02-01
The evaluation and enhancement of business processes in any organization in an uncertain environment presents one of the main requirements of ISO 9000:2008 and has a key effect on competitive advantage and long-term sustainability. The aim of this paper can be defined as the identification and discussion of some of the most important business processes of seaports and the performances of business processes and their key performance indicators (KPIs). The complexity and importance of the treated problem call for analytic methods rather than intuitive decisions. The existing decision variables of the considered problem are described by linguistic expressions which are modelled by triangular fuzzy numbers (TFNs). In this paper, the modified fuzzy extended analytic hierarchy process (FAHP) is proposed. The assessment of the relative importance of each pair of performances and their key performance indicators are stated as a fuzzy group decision-making problem. By using the modified fuzzy extended analytic hierarchy process, the fuzzy rank of business processes of a seaport is obtained. The model is tested through an illustrative example with real-life data, where the obtained data suggest measures which should enhance business strategy and improve key performance indicators. The future improvement is based on benchmark and knowledge sharing.
Comprehensible knowledge model creation for cancer treatment decision making.
Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar
2017-03-01
A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.
Using the weighted area under the net benefit curve for decision curve analysis.
Talluri, Rajesh; Shete, Sanjay
2016-07-18
Risk prediction models have been proposed for various diseases and are being improved as new predictors are identified. A major challenge is to determine whether the newly discovered predictors improve risk prediction. Decision curve analysis has been proposed as an alternative to the area under the curve and net reclassification index to evaluate the performance of prediction models in clinical scenarios. The decision curve computed using the net benefit can evaluate the predictive performance of risk models at a given or range of threshold probabilities. However, when the decision curves for 2 competing models cross in the range of interest, it is difficult to identify the best model as there is no readily available summary measure for evaluating the predictive performance. The key deterrent for using simple measures such as the area under the net benefit curve is the assumption that the threshold probabilities are uniformly distributed among patients. We propose a novel measure for performing decision curve analysis. The approach estimates the distribution of threshold probabilities without the need of additional data. Using the estimated distribution of threshold probabilities, the weighted area under the net benefit curve serves as the summary measure to compare risk prediction models in a range of interest. We compared 3 different approaches, the standard method, the area under the net benefit curve, and the weighted area under the net benefit curve. Type 1 error and power comparisons demonstrate that the weighted area under the net benefit curve has higher power compared to the other methods. Several simulation studies are presented to demonstrate the improvement in model comparison using the weighted area under the net benefit curve compared to the standard method. The proposed measure improves decision curve analysis by using the weighted area under the curve and thereby improves the power of the decision curve analysis to compare risk prediction models in a clinical scenario.
A Data mining Technique for Analyzing and Predicting the success of Movie
NASA Astrophysics Data System (ADS)
Meenakshi, K.; Maragatham, G.; Agarwal, Neha; Ghosh, Ishitha
2018-04-01
In real world prediction models and mechanisms can be used to predict the success of a movie. The proposed work aims to develop a system based upon data mining techniques that may help in predicting the success of a movie in advance thereby reducing certain level of uncertainty. An attempt is made to predict the past as well as the future of movie for the purpose of business certainty or simply a theoretical condition in which decision making [the success of the movie] is without risk, because the decision maker [movie makers and stake holders] has all the information about the exact outcome of the decision, before he or she makes the decision [release of the movie]. With over two million spectators a day and films exported to over 100 countries, the impact of Bollywood film industry is formidable We gather a series of interesting facts and relationships using a variety of data mining techniques. In particular, we concentrate on attributes relevant to the success prediction of movies, such as whether any particular actors or actresses are likely to help a movie to succeed. The paper additionally reports on the techniques used, giving their implementation and utility. Additionally, we found some attention-grabbing facts, such as the budget of a movie isn't any indication of how well-rated it'll be, there's a downward trend within the quality of films over time, and also the director and actors/actresses involved in the movie.