Decision criterion is determined by interaction's strength from inside or outside the perceptive field

2010 ◽  
Vol 9 (8) ◽  
pp. 1033-1033
Author(s):  
M. Lev ◽  
U. Polat
Keyword(s):  
Decision Criterion ◽  
Perceptive Field

scholarly journals The Effect of Informing Participants of the Response Bias of an Automated Target Recognition System on Trust and Reliance Behavior

2021 ◽  
pp. 001872082110217
Author(s):  
Shala Knocton ◽  
Aren Hunter ◽  
Warren Connors ◽  
Lori Dithurbide ◽  
Heather F. Neyedli
Keyword(s):  
Response Bias ◽  
Target Recognition ◽  
Rate Sensitivity ◽  
High Sensitivity ◽  
Recognition System ◽  
Decision Criterion ◽  
Detection Task ◽  
Mine Detection ◽  
Rate Condition ◽  
Consistent Response

Objective To determine how changing and informing a user of the false alarm (FA) rate of an automated target recognition (ATR) system affects the user’s trust in and reliance on the system and their performance during an underwater mine detection task. Background ATR systems are designed to operate using a high sensitivity and a liberal decision criterion to reduce the risk of the ATR system missing a target. A high number of FAs in general may lead to a decrease in operator trust and reliance. Methods Participants viewed sonar images and were asked to identify mines in the images. They performed the task without ATR and with ATR at a lower and higher FA rate. The participants were split into two groups—one informed and one uninformed of the changed FA rate. Trust and/or confidence in detecting mines was measured after each block. Results When not informed of the FA rate, the FA rate had a significant effect on the participants’ response bias. Participants had greater trust in the system and a more consistent response bias when informed of the FA rate. Sensitivity and confidence were not influenced by disclosure of the FA rate but were significantly worse for the high FA rate condition compared with performance without the ATR. Conclusion and application Informing a user of the FA rate of automation may positively influence the level of trust in and reliance on the aid.

scholarly journals A Satisficing Framework for Environmental Policy Under Model Uncertainty

2021 ◽  
Author(s):  
Stergios Athanasoglou ◽  
Valentina Bosetti ◽  
Laurent Drouet
Keyword(s):  
Environmental Policy ◽  
Model Uncertainty ◽  
Probability Distributions ◽  
Success Probability ◽  
Economic Assessment ◽  
Decision Criterion ◽  
Probability Criterion ◽  
Change Context ◽  
Future Consumption ◽  
Point Of Departure

AbstractWe propose a novel framework for the economic assessment of environmental policy. Our main point of departure from existing work is the adoption of a satisficing, as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different policies meet a set of goals at a specific future date instead of their performance vis-a-vis some intertemporal objective function. Consistent to the nature of environmental policymaking, our model takes explicit account of model uncertainty. To this end, the decision criterion we propose is an analog of the well-known success-probability criterion adapted to settings characterized by model uncertainty. We apply our criterion to the climate-change context and the probability distributions constructed by Drouet et al. (2015) linking carbon budgets to future consumption. Insights from computational geometry facilitate computations considerably and allow for the efficient application of the model in high-dimensional settings.

scholarly journals Estimating Recycling Return of Integrated Circuits Using Computer Vision on Printed Circuit Boards

2021 ◽  
Vol 11 (6) ◽  
pp. 2808
Author(s):  
Leandro H. de S. Silva ◽  
Agostinho A. F. Júnior ◽  
George O. A. Azevedo ◽  
Sergio C. Oliveira ◽  
Bruno J. T. Fernandes
Keyword(s):  
Integrated Circuits ◽  
Printed Circuit Boards ◽  
Printed Circuit Board ◽  
Electronic Waste ◽  
Decision Criterion ◽  
Economic Feasibility ◽  
Electronic Equipment ◽  
Circuit Board ◽  
Mechanical Recycling ◽  
Printed Circuit

The technological growth of the last decades has brought many improvements in daily life, but also concerns on how to deal with electronic waste. Electrical and electronic equipment waste is the fastest-growing rate in the industrialized world. One of the elements of electronic equipment is the printed circuit board (PCB) and almost every electronic equipment has a PCB inside it. While waste PCB (WPCB) recycling may result in the recovery of potentially precious materials and the reuse of some components, it is a challenging task because its composition diversity requires a cautious pre-processing stage to achieve optimal recycling outcomes. Our research focused on proposing a method to evaluate the economic feasibility of recycling integrated circuits (ICs) from WPCB. The proposed method can help decide whether to dismantle a separate WPCB before the physical or mechanical recycling process and consists of estimating the IC area from a WPCB, calculating the IC’s weight using surface density, and estimating how much metal can be recovered by recycling those ICs. To estimate the IC area in a WPCB, we used a state-of-the-art object detection deep learning model (YOLO) and the PCB DSLR image dataset to detect the WPCB’s ICs. Regarding IC detection, the best result was obtained with the partitioned analysis of each image through a sliding window, thus creating new images of smaller dimensions, reaching 86.77% mAP. As a final result, we estimate that the Deep PCB Dataset has a total of 1079.18 g of ICs, from which it would be possible to recover at least 909.94 g of metals and silicon elements from all WPCBs’ ICs. Since there is a high variability in the compositions of WPCBs, it is possible to calculate the gross income for each WPCB and use it as a decision criterion for the type of pre-processing.

scholarly journals DataStorm: Coupled, Continuous Simulations for Complex Urban Environments

2021 ◽  
Vol 2 (3) ◽  
pp. 1-37
Author(s):  
Hans Walter Behrens ◽  
K. Selçuk Candan ◽  
Xilun Chen ◽  
Yash Garg ◽  
Mao-Lin Li ◽  
...  
Keyword(s):  
Parameter Space ◽  
Simulation Analysis ◽  
Urban System ◽  
Decision Criterion ◽  
Urban Environments ◽  
Parallel Execution ◽  
Effective Density ◽  
Urban Systems ◽  
Space Partitioning ◽  
Imperfect Knowledge

Urban systems are characterized by complexity and dynamicity. Data-driven simulations represent a promising approach in understanding and predicting complex dynamic processes in the presence of shifting demands of urban systems. Yet, today’s silo-based, de-coupled simulation engines fail to provide an end-to-end view of the complex urban system, preventing informed decision-making. In this article, we present DataStorm to support integration of existing simulation, analysis and visualization components into integrated workflows. DataStorm provides a flow engine, DataStorm-FE , for coordinating data and decision flows among multiple actors (each representing a model, analytic operation, or a decision criterion) and enables ensemble planning and optimization across cloud resources. DataStorm provides native support for simulation ensemble creation through parameter space sampling to decide which simulations to run, as well as distributed instantiation and parallel execution of simulation instances on cluster resources. Recognizing that simulation ensembles are inherently sparse relative to the potential parameter space, we also present a density-boosting partition-stitch sampling scheme to increase the effective density of the simulation ensemble through a sub-space partitioning scheme, complemented with an efficient stitching mechanism that leverages partial and imperfect knowledge from partial dynamical systems to effectively obtain a global view of the complex urban process being simulated.

scholarly journals The added value of system robustness analysis for flood risk management illustrated by a case on the IJssel River

2015 ◽  
Vol 15 (2) ◽  
pp. 213-223 ◽  
Author(s):  
M. J. P. Mens ◽  
F. Klijn
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Robustness Analysis ◽  
Decision Criterion ◽  
Flood Damage ◽  
Flood Risk Management ◽  
Added Value ◽  
Common Basis ◽  
System Robustness ◽  
System Configurations

Abstract. Decision makers in fluvial flood risk management increasingly acknowledge that they have to prepare for extreme events. Flood risk is the most common basis on which to compare flood risk-reducing strategies. To take uncertainties into account the criteria of robustness and flexibility are advocated as well. This paper discusses the added value of robustness as an additional decision criterion compared to single-value flood risk only. We do so by quantifying flood risk and system robustness for alternative system configurations of the IJssel River valley in the Netherlands. We found that robustness analysis has added value in three respects: (1) it does not require assumptions on current and future flood probabilities, since flood consequences are shown as a function of discharge; (2) it shows the sensitivity of the system to varying discharges; and (3) it supports a discussion on the acceptability of flood damage. We conclude that robustness analysis is a valuable addition to flood risk analysis in support of long-term decision-making on flood risk management.

scholarly journals FUZZY MULTI-CRITERIA DECISION MAKING MODEL FOR SUBCONTRACTOR SELECTION IN INTERNATIONAL CONSTRUCTION PROJECTS

2015 ◽  
Vol 22 (2) ◽  
pp. 210-234 ◽  
Author(s):  
Serdar ULUBEYLI ◽  
Aynur KAZAZ
Keyword(s):  
Construction Projects ◽  
Decision Criterion ◽  
Practical Application ◽  
Human Judgment ◽  
Qualitative And Quantitative ◽  
International Construction ◽  
Weak Points ◽  
Initial Idea ◽  
Decision Making Model ◽  
Selection Of

A general contractor’s ability to select proper subcontractors in foreign projects is a key competitive advantage. Toward this aim, a subcontractor selection model (CoSMo) was developed in this study. As a computational approach, the fuzzy sets method was employed because it can model human judgment by means of linguistic values, combining qualitative and quantitative decision criteria into an aggregate measure. Although the algorithm may be complex for easy acceptance by industrial practitioners, this disadvantage was minimized through a computer-supported system. In order to gain a better understanding of the current practice of CoSMo, a real world construction project was conducted. As a result, it was observed that CoSMo has high practical application and can be used as an advisory system by satisfying principal contractor’s requirements to reduce the risk involved in the selection of a subcontractor. Moreover, it gives an initial idea of how subcontractors perform on each decision criterion and allows the main contractor to understand the picture on the strong and weak points of each bidder and thereby to take conscious decisions.

scholarly journals Let’s Talk about TEX—Understanding Consumer Preferences for Smart Interactive Textile Products Using a Conjoint Analysis Approach

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3152 ◽  
Author(s):  
Julia Offermann-van Heek ◽  
Philipp Brauner ◽  
Martina Ziefle
Keyword(s):  
Consumer Behavior ◽  
Conjoint Analysis ◽  
Consumer Preferences ◽  
Technological Development ◽  
Product Evaluation ◽  
Decision Criterion ◽  
Online Questionnaire ◽  
Close Link ◽  
Input Modality ◽  
Textile Products

Interactive textiles are reaching maturity. First technology augmented textiles in form of clothes and furnitures are becoming commercially available. In contrast to the close link between technological development and innovations, future users’ acceptance and usage of such interactive textiles has not been integrated sufficiently, yet. The current study investigates future users’ consumer behavior and acceptance of interactive textiles using a scenario-based conjoint analysis study, which was presented in an online questionnaire ( n = 324 ). Two prototypical interactive textiles were focused on: a smart jacket and a smart armchair. To assess the textile products, the participants had to choose the preferred product alternative consisting each of the acceptance-relevant factors “connectivity”, “input modality”, “feature range”, “usability”, and “ease of cleaning”and their respective levels. The results revealed that the “ease of cleaning” is the most important decision criterion for both textile devices (even more important for the smart jacket), followed by “feature range”, “connectivity”, and “usability”. In contrast, the “input modality” is perceived as least important. The study also identified user profiles based on the projected consumer behavior (“adopters”, “rejecters”, and “undecided”) for both products. Besides the differences in product evaluation and projected consumer behavior, the user groups are significantly influenced by the individual affinity to textiles (both products) and gender (smart jacket). The findings are used to derive design and communication guidelines referring to interactive textiles in order to incorporate users’ needs, wishes, and requirements into future products.

Sign in / Sign up

Export Citation Format

Share Document