scholarly journals A Robotic Cognitive Architecture for Slope and Dam Inspections

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4579 ◽  
Author(s):  
Milena F. Pinto ◽  
Leonardo M. Honorio ◽  
Aurélio Melo ◽  
Andre L. M. Marcato
Keyword(s):  
Decision Making ◽  
Cognitive Architecture ◽  
Electrical Power ◽  
Data Gathering ◽  
Path Following ◽  
Sensors And Actuators ◽  
Construction Enterprises ◽  
Performance Quality ◽  
Human Operators ◽  
High Level

Big construction enterprises, such as electrical power generation dams and mining slopes, demand continuous visual inspections. The sizes of these structures and the necessary level of detail in each mission requires a conflicting set of multi-objective goals, such as performance, quality, and safety. It is challenging for human operators, or simple autonomous path-following drones, to process all this information, and thus, it is common that a mission must be repeated several times until it succeeds. This paper deals with this problem by developing a new cognitive architecture based on a collaborative environment between the unmanned aerial vehicles (UAVs) and other agents focusing on optimizing the data gathering, information processing, and decision-making. The proposed architecture breaks the problem into independent units ranging from sensors and actuators up to high-level intelligence processes. It organizes the structures into data and information; each agent may request an individual behavior from the system. To deal with conflicting behaviors, a supervisory agent analyzes all requests and defines the final planning. This architecture enables real-time decision-making with intelligent social behavior among the agents. Thus, it is possible to process and make decisions about the best way to accomplish the mission. To present the methodology, slope inspection scenarios are shown.

scholarly journals ARCog: An Aerial Robotics Cognitive Architecture

Robotica ◽  
2020 ◽  
pp. 1-20 ◽  
Author(s):  
Milena F. Pinto ◽  
Leonardo M. Honório ◽  
Andre L. M. Marcato ◽  
Mario A. R. Dantas ◽  
Aurelio G. Melo ◽  
...  
Keyword(s):  
Decision Making ◽  
Cognitive Architecture ◽  
Aerial Robotics ◽  
Sensors And Actuators ◽  
Cognitive Approach ◽  
Vehicle Architecture ◽  
Level Data ◽  
Intelligent Behavior ◽  
Key Issues ◽  
High Level

SUMMARY Efficient algorithm integration is a key issue in aerial robotics. However, only a few integration solutions rely on a cognitive approach. Cognitive approaches break down complex problems into independent units that may deal with progressively lower-level data interfaces, all the way down to sensors and actuators. A cognitive architecture defines information flow among units to produce emergent intelligent behavior. Despite the improvements in autonomous decision-making, several key issues remain open. One of these issues is the selection, coordination, and decision-making related to the several specialized tasks required for fulfilling mission objectives. This work addresses decision-making for the cognitive unmanned-aerial-vehicle architecture coined as ARCog. The proposed architecture lays the groundwork for the development of a software platform aligned with the requirements of the state-of-the-art technology in the field. The system is designed to provide high-level decision-making. Experiments prove that ARCog works correctly in its target scenario.

Radiological safety and assessment of the performance of X-ray systems in veterinary facilities

2020 ◽  
Author(s):  
S. Economides ◽  
C.J. Hourdakis ◽  
C. Pafilis ◽  
G. Simantirakis ◽  
P. Tritakis ◽  
...  
Keyword(s):  
Decision Making ◽  
Radiation Protection ◽  
Atomic Energy Commission ◽  
Atomic Energy ◽  
Regulatory Control ◽  
Continuous Training ◽  
X Ray ◽  
The Public ◽  
Radiological Safety ◽  
High Level

This paper concerns an analysis regarding the performance of X-ray equipment as well as the radiological safety in veterinary facilities. Data were collected from 380 X-ray veterinary facilities countrywide during the on-site regulatory inspections carried out by the Greek Atomic Energy Commission. The analysis of the results shows that the majority of the veterinary radiographic systems perform within the acceptable limits; moreover, the design and shielding of X-ray rooms as well as the applied procedures ensure a high level of radiological safety for the practitioners, operators and the members of the public. An issue that requires specific attention in the optimization process for the proper implementation of veterinary radiology practices in terms of radiological safety is the continuous training of the personnel. The above findings and the regulatory experience gained were valuable decision-making elements regarding the type of the regulatory control of veterinary radiology practices in the new radiation protection framework.

Decision making power of college girls in relation to clothing

2018 ◽  
Vol 9 (01) ◽  
Author(s):  
Parul Gill ◽  
Poonam Malik ◽  
Pankaj Gill
Keyword(s):  
Decision Making ◽  
Satisfaction Level ◽  
College Going ◽  
Level Of Satisfaction ◽  
High Level ◽  
Garment Design ◽  
Structured Questionnaire

The present study was undertaken to explore the decision making patterns of college girls in relation to clothing and their satisfaction level with these decision making patterns. Thirty under graduate college girls from Panipat city were approached to record their responses regarding decision making in relation to clothing and satisfaction level through a well structured questionnaire. It was found that most of the girls (56.66%) themselves made the decisions about the type of garment (Indian, western or both) they wear and majority of girls (70%) were highly satisfied with this decision making. Parents performed the role of buyers for their college going daughters' garments in most of the cases (63.33%) and the 73.33% girls had high level of satisfaction with this. In most of the cases (60%) the decision about the garment design was made by the girls themselves and they were highly satisfied with it. Keywords: clothing, college, girls, decision making.

scholarly journals EXPRESS: Marketers Project Their Personal Preferences onto Consumers: Overcoming the Threat of Egocentric Decision Making

2021 ◽  
pp. 002224372199837
Author(s):  
Walter Herzog ◽  
Johannes D. Hattula ◽  
Darren W. Dahl
Keyword(s):  
Decision Making ◽  
Consumer Preferences ◽  
Research Question ◽  
Pilot Studies ◽  
Low Level ◽  
Marketing Managers ◽  
False Consensus Effect ◽  
False Consensus ◽  
High Level

This research explores how marketing managers can avoid the so-called false consensus effect—the egocentric tendency to project personal preferences onto consumers. Two pilot studies were conducted to provide evidence for the managerial importance of this research question and to explore how marketing managers attempt to avoid false consensus effects in practice. The results suggest that the debiasing tactic most frequently used by marketers is to suppress their personal preferences when predicting consumer preferences. Four subsequent studies show that, ironically, this debiasing tactic can backfire and increase managers’ susceptibility to the false consensus effect. Specifically, the results suggest that these backfire effects are most likely to occur for managers with a low level of preference certainty. In contrast, the results imply that preference suppression does not backfire but instead decreases false consensus effects for managers with a high level of preference certainty. Finally, the studies explore the mechanism behind these results and show how managers can ultimately avoid false consensus effects—regardless of their level of preference certainty and without risking backfire effects.

Exploring The Effect of Visual Information Degradation on Human Perception and Performance In A Human-Telerobot System

2020 ◽  
Vol 64 (1) ◽  
pp. 1302-1307
Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall
Keyword(s):  
Visual Information ◽  
Human Perception ◽  
Low Level ◽  
Hit Rate ◽  
Word Level ◽  
Level Of Automation ◽  
Significant Difference ◽  
Human Operators ◽  
And Performance ◽  
High Level

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.

scholarly journals Fuzzy Logic for Intelligent Control System Using Soft Computing Applications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2617
Author(s):  
Catalin Dumitrescu ◽  
Petrica Ciotirnae ◽  
Constantin Vizitiu
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Control Technique ◽  
Distributed Intelligence ◽  
High Level ◽  
The Impact ◽  
Fuzzy Subsets

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

Comparing Two Decision Support Modes Using the Cognitive Shadow Online Policy-Capturing System

2020 ◽  
Vol 64 (1) ◽  
pp. 1125-1129
Author(s):  
Katherine Labonté ◽  
Daniel Lafond ◽  
Aren Hunter ◽  
Heather F. Neyedli ◽  
Sébastien Tremblay
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Response Pattern ◽  
Policy Capturing ◽  
Model Accuracy ◽  
Prototype Tool ◽  
Human Operators ◽  
Support Decision Making ◽  
Threat Evaluation

The Cognitive Shadow is a prototype tool intended to support decision making by autonomously modeling human operators’ response pattern and providing online notifications to the operators about the decision they are expected to make in new situations. Since the system can be configured either in a reactive “shadowing” or a proactive “recommendation” mode, this study aimed to determine its most effective mode in terms of human and model accuracy, workload, and trust. Subjects participated in an aircraft threat evaluation simulation without decision support or while using either mode of the Cognitive Shadow. Whereas the recommendation mode had no advantage over the control condition, the shadowing mode led to higher human and model accuracy. These benefits were maintained even when the tool was unexpectedly removed. Neither mode influenced workload, and the initial lower trust rating in the shadowing mode faded quickly, making it the best overall configuration for the cognitive assistant.

Transfer Reinforcement Learning for Autonomous Driving

2021 ◽  
Vol 31 (3) ◽  
pp. 1-26
Author(s):  
Aravind Balakrishnan ◽  
Jaeyoung Lee ◽  
Ashish Gaurav ◽  
Krzysztof Czarnecki ◽  
Sean Sedwards
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Transfer Problem ◽  
Autonomous Driving ◽  
High Fidelity ◽  
Rule Based ◽  
High Level ◽  
Real Vehicle

Reinforcement learning (RL) is an attractive way to implement high-level decision-making policies for autonomous driving, but learning directly from a real vehicle or a high-fidelity simulator is variously infeasible. We therefore consider the problem of transfer reinforcement learning and study how a policy learned in a simple environment using WiseMove can be transferred to our high-fidelity simulator, W ise M ove . WiseMove is a framework to study safety and other aspects of RL for autonomous driving. W ise M ove accurately reproduces the dynamics and software stack of our real vehicle. We find that the accurately modelled perception errors in W ise M ove contribute the most to the transfer problem. These errors, when even naively modelled in WiseMove , provide an RL policy that performs better in W ise M ove than a hand-crafted rule-based policy. Applying domain randomization to the environment in WiseMove yields an even better policy. The final RL policy reduces the failures due to perception errors from 10% to 2.75%. We also observe that the RL policy has significantly less reliance on velocity compared to the rule-based policy, having learned that its measurement is unreliable.

scholarly journals Decision-making process for introduction of maternal vaccines in Kenya, 2017–2018

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Nancy A. Otieno ◽  
Fauzia A. Malik ◽  
Stacy W. Nganga ◽  
Winnie N. Wairimu ◽  
Dominic O. Ouma ◽  
...  
Keyword(s):  
Decision Making ◽  
Policy Development ◽  
Implementation Process ◽  
Policy Formulation ◽  
Advisory Group ◽  
Decision Making Process ◽  
Middle Income ◽  
Maternal Immunization ◽  
Negative Impacts ◽  
High Level

Abstract Background Maternal immunization is a key strategy for reducing morbidity and mortality associated with infectious diseases in mothers and their newborns. Recent developments in the science and safety of maternal vaccinations have made possible development of new maternal vaccines ready for introduction in low- and middle-income countries. Decisions at the policy level remain the entry point for maternal immunization programs. We describe the policy and decision-making process in Kenya for the introduction of new vaccines, with particular emphasis on maternal vaccines, and identify opportunities to improve vaccine policy formulation and implementation process. Methods We conducted 29 formal interviews with government officials and policy makers, including high-level officials at the Kenya National Immunization Technical Advisory Group, and Ministry of Health officials at national and county levels. All interviews were recorded and transcribed. We analyzed the qualitative data using NVivo 11.0 software. Results All key informants understood the vaccine policy formulation and implementation processes, although national officials appeared more informed compared to county officials. County officials reported feeling left out of policy development. The recent health system decentralization had both positive and negative impacts on the policy process; however, the negative impacts outweighed the positive impacts. Other factors outside vaccine policy environment such as rumours, sociocultural practices, and anti-vaccine campaigns influenced the policy development and implementation process. Conclusions Public policy development process is complex and multifaceted by its nature. As Kenya prepares for introduction of other maternal vaccines, it is important that the identified policy gaps and challenges are addressed.

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