Decision Schema Research Articles

Competence committees decision-making; an interplay of data, group orientation, and intangible impressions

BackgroundThe implementation of competency-based medical education and utilization of competence committees (CC) represents a paradigm shift in residency education. This qualitative study aimed to explore the methods used by two operational CC and their members to make decisions about progression and competence of their residents.MethodsAn instrumental case study methodology was used to study the CC of two postgraduate training programs. Transcripts from observed CC meetings, member interviews, and guiding documents were analyzed using a constructivist grounded theory approach to reveal themes explaining the decision-making process.ResultsOur study found that the CC followed a process that began within a social decision schema model and evolved to a discussion that invoked social influence theory, shared mental models, and social judgment scheme to clarify the points of contention. We identified that the CC decision-making was at risk of bias, primarily influenced by the group composition, the group orientation and individual members’ mindset, as well as their personal experiences with the trainees.ConclusionsIncreased awareness of the sources of bias in CC functioning and familiarity with the CC role in competency-based medical education would enable committees to provide valuable feedback to all trainees regardless of their trajectory.

Technical solution «third decision schema» of increasing the efficiency of search and synchronization of difficult broadband noise like signals

Technical solution «third decision schema» of increasing the efficiency of search and synchronization of difficult broadband noise like signals

Algorithm for implementation of the «third decision scheme» of increasing the efficiency of search and synchronization of difficult broadband noise like signals

The construction of telecommunication networks with a guaranteed level of quality of service involves assessing and ensuring the security of both the networks themselves and information flows from unauthorized access and various kinds of interference, in particular at the 1st (physical) level of the network. In this regard, research in the field of creating recurrent code sequences with improved systemic, correlation, secretive, imitation-resistant properties is constantly relevant. In particular, research in the development and application of derivative nonlinear recurrent sequences, as a central element in the developed theory of the «third decision scheme». Goal of the work is to develop an algorithm for increasing the efficiency of search and synchronization of broadband signals in the form of double derivatives of nonlinear recurrent sequences, which directly uses the features of their code structure, the properties of determinism of their auto- and cross-correlation functions. The results of the research and development of the efficiency of the algorithm for accelerated search and synchronization of broadband complex signals in the form of phase-shift keyed derivatives of nonlinear recurrent sequences, which implements the principles of the «third decision schema» The developed algorithm, based on the use of double derivatives of nonlinear recurrent sequences as wideband signals, can be applied in the construction of promising packet radio networks.

Method for implementation of the «third decision schema» of increasing the efficiency of search and synchronization of difficult broadband noise like signals

Method for implementation of the «third decision schema» of increasing the efficiency of search and synchronization of difficult broadband noise like signals

Decision model change patterns for dynamic system evolution

In the modern digital era, information systems must operate in increasingly interconnected and dynamic environments, which force them to be changeable yet consistent. Such modern information systems are usually decision- and knowledge-intensive. A recently introduced standard, the decision model and notation (DMN), has been adopted in both industry and academia as a suitable method for modelling decisions and decision rules. Noteworthy is that, despite the dynamic nature of modern knowledge-intensive systems, DMN was only studied and implemented in a static fashion, as decision schema change patterns have not received any attention so far. This paper identifies and analyses the change patterns that can occur in a DMN decision model. A change in the decision model can require the triggering of other changes in order to safeguard consistency. As such, this paper will also investigate for each change pattern which further changes should be performed to ensure model consistency. The patterns presented in this paper will not only facilitate the understanding of decision change management and within-model consistency, but can also be capitalised on for developing and implementing flexible decision management systems. To illustrate this, we present a modelling environment prototype that provides modelling support when applying the proposed change patterns.

Harmonized global maps of above and belowground biomass carbon density in the year 2010

Remotely sensed biomass carbon density maps are widely used for myriad scientific and policy applications, but all remain limited in scope. They often only represent a single vegetation type and rarely account for carbon stocks in belowground biomass. To date, no global product integrates these disparate estimates into an all-encompassing map at a scale appropriate for many modelling or decision-making applications. We developed an approach for harmonizing vegetation-specific maps of both above and belowground biomass into a single, comprehensive representation of each. We overlaid input maps and allocated their estimates in proportion to the relative spatial extent of each vegetation type using ancillary maps of percent tree cover and landcover, and a rule-based decision schema. The resulting maps consistently and seamlessly report biomass carbon density estimates across a wide range of vegetation types in 2010 with quantified uncertainty. They do so for the globe at an unprecedented 300-meter spatial resolution and can be used to more holistically account for diverse vegetation carbon stocks in global analyses and greenhouse gas inventories.

A framework for assessment of predictive capability maturity and its application in nuclear thermal hydraulics

This work presents a formalized and computerized framework for the assessment of decision regarding the adequacy of a simulation tool for a nuclear reactor application. The decision regarding a code’s adequacy for an application is dependent on the assessment of different attributes that govern verification, validation, and uncertainty quantification of the code. In this work, the focus is on code validation. Therefore, the framework is developed and illustrated from the perspective of decision regarding the validation assessment of a code. Code validation assessment is performed based on the validation test results, data applicability, and process quality assurance factors. The process quality assurance factors warrant the trustworthiness of the evidence and help in checking people and process compliance with respect to the standard requirements.The proposed framework is developed using an argument modeling technique called Goal Structuring Notation (GSN). Goal structuring notation facilitates structural knowledge representation, information abstraction, evidence incorporation, and provides a skeletal structure for quantitative maturity assessment. The decision schema for the development of the decision model is based on the Predictive Capability Maturity Model (PCMM) and Analytic Hierarchy Process (AHP) and formalized using Goal structuring notation. Each decision attribute is formulated as a claim, where the degree of validity of the claim (attribute’s assessment) is expressed using different maturity levels. The GSN representation of the decision model is transformed into a confidence network to provide evidence-based quantitative maturity assessment using the Bayesian network. A metric based on the expected utility of maturity levels, called expected distance metric, is proposed to measure the distance between target maturity and achieved maturity on a scale of zero to one. Expected distance metric helps in comparing the assessment of different attributes and identification of major areas of concern in terms of modeling capability, data needs, and quality of assessment process. The practical application of the framework is demonstrated by a case study on validation assessment of a thermal-hydraulic code for a challenge problem called Departure from Nucleate Boiling (DNB).

Intracerebral haemorrhage risk in microbleed-positive ischaemic stroke patients with atrial fibrillation: Preliminary meta-analysis of cohorts and anticoagulation decision schema

IntroductionWhether ischaemic stroke patients with atrial fibrillation (AF) and cerebral microbleeds (CMBs) on MRI can be safely anticoagulated is a hotly debated topic. We performed a systematic review and meta-analysis of published aggregate data, to investigate the risk of subsequent intracerebral haemorrhage (ICH) based on CMBs presence in this stroke population, generally considered for oral anticoagulation. We also suggest a decision-making schema for anticoagulation use in this setting. MethodsWe searched PubMed for relevant observational studies. Random effects models with DerSimonian-Laird weights were used to investigated the association between CMBs presence at baseline MRI and ICH or ischaemic stroke during follow-up. ResultsFour studies, with slightly heterogeneous design, including 990 ischaemic stroke patients were pooled in a meta-analysis (crude CMBs prevalence: 25%; 95%CI: 17%–33%). The median follow-up ranged between 17 and 37months. The future symptomatic ICH rate was 1.6% (16/990), while recurrent ischaemic stroke rate was 5.9% (58/990). Baseline CMB presence was associated with increased risk of symptomatic ICH during follow-up compared to patients without CMBs (OR: 4.16; 95%CI: 1.54–11.25; p=0.005). There was no association between CMBs presence and recurrent ischaemic stroke risk. ConclusionWe have shown that the presence of CMBs in cohorts of ischaemic stroke patients, most with AF on warfarin, is associated with a 4-fold increase in subsequent ICH (but not ischaemic stroke) risk (Class III evidence). These pooled estimates are useful for future trials design. We propose a simple data-driven anticoagulation schema which awaits validation and refinement as new prospective data are accumulated.

Tree-shaped Decision Schema for Multi-classification

This paper presents a novel M-class classification schema. SVCMR creates a tree-shaped decision frame which contains M/2 three-separation classifiers as decision nodes. In an informed order, a series of basic classifiers are trained on the reduced dataset, and this order ensures the less number of basic models to cover decisions on all classes. SVCMR is characterized with individual parameterization of Kernel scale and penalty coefficient. Experiments on real experiments demonstrate the fine performance of SVCMR.

IBMMS Decision Support Tool for Management of Bank Telemarketing Campaign

Although direct marketing is a good method for banks to utilize in the face of global competition and the financial crisis, it has been shown to exhibit poor performance. However, there are some drawbacks to direct campaigns, such as those related to improving the negative attributes that customers ascribe to banks. To overcome these problems, attractive long-term deposit campaigns should be organized and managed more effectively. The aim of this study is to develop an Intelligent Bank Market Management System (IBMMS) for bank managers who want to manage efficient marketing campaigns. IBMMS is the first system developed by combining the power of data mining with the capabilities of expert systems in this area. Moreover, IBMMS includes important features that enable it to be intelligent: a knowledge base, an inference engine and an advisor. Using this system, a manager can successfully direct marketing campaigns and follow the decision schemas of customers both as individuals and as a group; moreover, a manager can make decisions that lead to the desired response by customers.

Defining an Affective Algorithm for Purchasing Decisions in E-Commerce Environments

This paper presents an affective algorithm to support purchasing decisions in e-commerce environments. The literature associated with decision-making theory includes the affective dimension as a clear human decision factor. In the same sense, several models and proposals of consumer behavior consider both affective and social dimensions as very important factors that influence each human decision. However, the related work associated with electronic commerce proposes strongly the use of rational dimension as the main decision factor. Our approach proposes the incorporation of the affective dimension as a central component within an integrated decision schema. The proposed algorithm considers three different decision factors: an objective dimension, which represents the rational decision factors; an individual subjective dimension, which represents the affective decision factors; and a social subjective dimension, which represents the social decision factors. The study case explains how the proposal algorithm can be implemented in a real scenario.

Decision making models embedded into a web-based tool for assessing pest infestation risk

Current practices in agricultural management involve the application of rules and techniques to ensure high quality and environmentally friendly production. Based on their experience, agricultural technicians and farmers make critical decisions affecting crop growth while considering several interwoven agricultural, technological, environmental, legal and economic factors. In this context, decision support systems and the knowledge models that support them, enable the incorporation of valuable experience into software systems providing support to agricultural technicians to make rapid and effective decisions for efficient crop growth. Pest control is an important issue in agricultural management due to crop yield reductions caused by pests and it involves expert knowledge. This paper presents a formalisation of the pest control problem and the workflow followed by agricultural technicians and farmers in integrated pest management, the crop production strategy that combines different practices for growing healthy crops whilst minimising pesticide use. A generic decision schema for estimating infestation risk of a given pest on a given crop is defined and it acts as a metamodel for the maintenance and extension of the knowledge embedded in a pest management decision support system which is also presented. This software tool has been implemented by integrating a rule-based tool into web-based architecture. Evaluation from validity and usability perspectives concluded that both agricultural technicians and farmers considered it a useful tool in pest control, particularly for training new technicians and inexperienced farmers.

The Future is Now: How Joint Decision Making Curbs Hyperbolic Discounting but Blurs Social Responsibility in the Intergenerational Equity Public Policy Domain

When individuals judge alternative choices, presenting alternatives concurrently improves decision making outcomes. The joint decision making advantage has been proven in the Western world, yet generalizations for other cultures are missing. This paper explores the applicability of joint decision making for global public policy decisions in the intergenerational equity domain. Presenting the viewpoints of two generations with outcomes now or later concurrently worked towards intergenerationally equitable choices when surveying 223 Chinese individuals (Study 1) and 374 online recruited respondents (Study 2). Joint decision making is a powerful, previously untested means to overcome hyperbolic discounting biases in decisions on global common goods dilemmas. We also find policy bundling decreases social responsibility. The joint alternative presentation thus leads to future-orientation versus social responsibility trade-off predicaments in intergenerational decisions. Policy makers are advised to consider a multi-faceted decision schema and age-differentiated consortia may help implement intergenerational equity.

Input information complexity, perceived time pressure, and information processing in GSS-based work groups: An experimental investigation using a decision schema to alleviate information overload conditions

Collaboration technology enhances the ability of work groups to acquire and share large volumes of information within a short period. The processing of voluminous information is challenging and may lead to conditions of information overload. The issue of complexity of information processing in collaboration technology supported group work, and the mechanisms to overcome the information overload conditions have not received sufficient attention in the past. In this paper, we attempt to address this gap by building a theoretical model and validating it through a laboratory experiment. Based on prior research on information processing at individual level, we propose that information processing in groups that use group support systems (GSS) is shaped by input information complexity and time pressure. We examine information processing of GSS-supported groups to perform tasks involving cognitive conflict. We demonstrate that information processing has an inverted U-shaped relationship with input information complexity and a positive relationship with time pressure. The study also demonstrates that the inclusion of a decision schema that incorporates aggregate level information gleaned from the work of prior groups engaged in a similar decision situation alleviates the information overload, enabling groups to process larger and more complex information.

Decision tools for life support: A review and policy analysis

To identify, describe, and compare published documents intended to guide decisions about the administration, withholding, or withdrawal of life support in critical care. Review article. SETTING AND SOURCES: Publicly available, English-language guidelines or decision tools for life support, identified through systematic literature search. Forty-nine documents were included and coded for authorship, source, development methodology, format, and positions taken on 12 common life-support issues. Sources were independent academics (n=21, 43%), professional organizations (n=19, 44%), and provider organizations. Eighteen documents (37%) described no development method. Twenty-three (47%) were produced collectively (e.g., by committees or consensus conference), 7 (14%) mentioned a literature review, and 2 (4%) were based upon the author's professional experience. Tools differed in format and focus; we characterize three types as decision schemas (involving clinical practice algorithms; n=7, 14%), decision guides (reviewing legal or professional positions; n=29, 59%), and decision counsels (more discursive and focusing typically on ethical issues; n=13, 27%). Tools addressed 12 common life-support issues: advance directives (67%), resource considerations (51%), ICU discharge criteria (27%), ICU admission criteria (16%), whether withholding differs from withdrawing life support (59%), whether nutrition and hydration decisions are different from decisions about other types of life support (61%), euthanasia (49%), double effect (47%), brain death (35%), special considerations for patients in a persistent vegetative state (51%), potential organ donors (12%), and pregnant patients (10%). Positions on these key life-support issues varied. Published tools for guiding life-support decisions vary widely in their genesis, authorship, format, focus, and practicality. They also differ in their attention to, and positions on, key life-support dilemmas. Future research on decision tools should focus on how users interpret and apply the messages in these tools and their impacts on practice, quality of care, participant experiences, and outcomes.

MODELING DRINKING WATER QUALITY VIOLATIONS WITH BAYESIAN NETWORKS1

ABSTRACT: Compliance violations at community water systems are rare but represent significant human health risks. These risks are mediated by the decision schema of human operators at water treatment facilities. However, causal uncertainty among physical and human factors involved in water quality problems complicates assessment of their probability and severity. This study uses a probabilistic Bayesian network modeling approach to explore the causes of compliance violations in a sample of water treatment systems in Pennsylvania. The model presented here is one of several created by treatment system operators during an expert elicitation process. The expert model alone predicts violations poorly, suggesting that experts make inaccurate quantitative estimates. However, Bayesian networks are capable of combining the subjective expertise of treatment system operators with the objective compliance histories of the facilities they manage, and the expert model accurately predicts violations when trained with historical compliance data. Analysis of the trained network reveals those components of the treatment process, including environmental and system characteristics as well as operator decisions, that play the greatest role in determining the likelihood of major violation types. Among operator decisions, coagulant dosing and filter backwash frequency are the most important determinants of violation likelihood.

Diagnostic classification of cancer using DNA microarrays and artificial intelligence.

The application of artificial intelligence (AI) to microarray data has been receiving much attention in recent years because of the possibility of automated diagnosis in the near future. Studies have been published predicting tumor type, estrogen receptor status, and prognosis using a variety of AI algorithms. The performance of intelligent computing decisions based on gene expression signatures is in some cases comparable to or better than the current clinical decision schemas. The goal of these tools is not to make clinicians obsolete, but rather to give clinicians one more tool in their armamentarium to accurately diagnose and hence better treat cancer patients. Several such applications are summarized in this chapter, and some of the common pitfalls are noted.

Management ‘Intuition’: An Interpretative Account of Structure and Content of Decision Schemas Using Cognitive Maps

In this paper, the structure and content of executive perceptions are considered using cognitive mapping to isolate ‘intuitive’ elements within their individual decision schemas. An inductive approach is used to develop three propositions drawn from the literature. These are explored using the results of interviews with senior executives of two UK retail organizations. Three of the maps represent different levels of seniority and roles and are used to explore potential differences within the organization. Similarities and differences between organizations are examined with reference to an additional map of an individual in a second organization.[1] Propositions are interpreted and developed with reference to the maps and textual extracts from the interviews, to provide additional insight into the concept of intuition prior to larger‐scale studies. The study highlights the need to explore differences in schemas both within and between different industry sectors. It emphasizes three important aspects of intuition as a way in which individuals ‘cut through’ a decision situation to make an ‘unexplained’ relationship between input and cognition without really thinking in‐depth. First, they appear to trade‐off depth for breadth of information. Second, they use personal experiences, surrogate indicators, and typologies to rationalize their decisions. Finally, the study shows there are important overlaps and differences in the content of decision schemas that represent ground for agreement and disagreement and as a basis for negotiating group decisions. These insights are used to redevelop and extend the propositions by way of conclusion.

USING A COGNITIVE PROSTHESIS TO ASSIST FOODSERVICE MANAGERIAL DECISION MAKING

The artificial intelligence community has been notably unsuccessful in producing intelligent agents that think for themselves. However, there is an obvious need for increased information processing power in real life situations. An example of this can be witnessed in the training of a foodservice manager, who is expected to solve a wide variety of complex problems on a daily basis. This article explores the possibil­ ity of creating an intelligence aid, rather than an intelligence agent, to assist novice foodservice managers in making decisions that are congruent with a subject matter expert's decision schema.

A Structural Analysis of Value, Quality, and Price Perceptions of Business and Leisure Travelers

Customer value has become the focus of firm strategies in recent years. This study investigates the relationships between travelers’ perceptions of value, quality, and price and their influence on travelers’ ratings of similar hotels and revisit intentions in two segments, business and leisure travelers. The findings suggest that value plays a pivotal role in travelers’ decision schema, emphasizing the need to shift efforts from managing quality alone to managing customer value. Differences in the value perceptions of business and leisure travelers emphasize the need to develop segment-based strategies for managing price and quality.