scholarly journals The relationship between the subjective experience of real-world cognitive failures and objective target-detection performance in visual search

Cognition ◽  
2021 ◽  
Vol 217 ◽  
pp. 104914
Author(s):  
Katherine J. Thomson ◽  
Stephanie C. Goodhew
Keyword(s):  
Visual Search ◽  
Target Detection ◽  
Real World ◽  
Subjective Experience ◽  
Detection Performance ◽  
Cognitive Failures ◽  
The Relationship

A Fitting Solution

2018 ◽  
Author(s):  
Kaori Kashimura ◽  
Takafumi Kawasaki Jr. ◽  
Nozomi Ikeya ◽  
Dave Randall
Keyword(s):  
Organizational Change ◽  
Power Plant ◽  
Augmented Reality ◽  
Real World ◽  
Work Practices ◽  
Plant Construction ◽  
Tightly Coupled ◽  
Complex Scenario ◽  
The Relationship ◽  
The Way

This chapter provides an ethnography of a complex scenario involving the construction of a power plant and, in so doing, tries to show the importance of a practice-based approach to the problem of technical and organizational change. The chapter reports on fieldwork conducted in a highly complex and tightly coupled environment: power plant construction. The ethnography describes work practices on three different sites and describes and analyses their interlocking dependencies, showing the difficulties encountered at each location and the way in which the delays that result cascade through the different sites. It goes on to describe some technological solutions that are associated with augmented reality and that are being designed in response to the insights gained from the fieldwork. The chapter also reflects more generally on the relationship between fieldwork and design in real-world contexts.

scholarly journals Implementation of a Modified Faster R-CNN for Target Detection Technology of Coastal Defense Radar

2021 ◽  
Vol 13 (9) ◽  
pp. 1703
Author(s):  
He Yan ◽  
Chao Chen ◽  
Guodong Jin ◽  
Jindong Zhang ◽  
Xudong Wang ◽  
...  
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Real Data ◽  
Detection Performance ◽  
Detection Accuracy ◽  
Constant False Alarm Rate ◽  
Data Set ◽  
Detection Technology ◽  
Coastal Defense

The traditional method of constant false-alarm rate detection is based on the assumption of an echo statistical model. The target recognition accuracy rate and the high false-alarm rate under the background of sea clutter and other interferences are very low. Therefore, computer vision technology is widely discussed to improve the detection performance. However, the majority of studies have focused on the synthetic aperture radar because of its high resolution. For the defense radar, the detection performance is not satisfactory because of its low resolution. To this end, we herein propose a novel target detection method for the coastal defense radar based on faster region-based convolutional neural network (Faster R-CNN). The main processing steps are as follows: (1) the Faster R-CNN is selected as the sea-surface target detector because of its high target detection accuracy; (2) a modified Faster R-CNN based on the characteristics of sparsity and small target size in the data set is employed; and (3) soft non-maximum suppression is exploited to eliminate the possible overlapped detection boxes. Furthermore, detailed comparative experiments based on a real data set of coastal defense radar are performed. The mean average precision of the proposed method is improved by 10.86% compared with that of the original Faster R-CNN.

OP48 Nursing Requirements In Long-Term Care: A Health Technology Assessment

2019 ◽  
Vol 35 (S1) ◽  
pp. 11-12
Author(s):  
Paula Corabian ◽  
Charles Yan ◽  
Susan Armijo-Olivo ◽  
Bing Guo
Keyword(s):  
Nursing Care ◽  
Nursing Staff ◽  
Real World ◽  
Research Evidence ◽  
Long Term Care ◽  
Staff Time ◽  
Term Care ◽  
Policy Makers ◽  
The Relationship

IntroductionThe objectives of this study were to systematically review published research on the relationship between nursing staff coverage, care hours, and quality of care (QoC) in long-term care (LTC) facilities; and to conduct a real world evidence (RWE) analysis using Alberta real world data (RWD) to inform policy makers on whether any amendments could be made to current regulations.MethodsA systematic review (SR) of research evidence published between January 2000 and May 2018 on the relationship between nursing staff coverage, care hours, and QoC in LTC facilities was conducted. Panel data regressions using available RWD from Alberta, Canada, were performed to assess associations between nursing care hours and LTC outcomes. Outcomes of interest included quality indicators related to resident outcomes, hospital admissions, emergency room visits and family satisfaction. Nursing care hours considered in SR and RWE analysis included those provided by registered nurses (RNs) and licensed practical nurses (LPNs).ResultsThe SR found inconsistent and poor quality evidence relevant to the questions of interest, indicating a great uncertainty about the association between nursing staff time and type of coverage and QoC. Although some positive indications were suggested, major weaknesses of reviewed studies limited interpretation of SR results. RWE analysis found that impact of care hours on LTC outcomes was heterogeneous, dependent on outcome measurements. There was evidence that total staff, RN, and LPN hours had positive effects on some resident outcomes and magnitude of effect differed for different nursing staff.ConclusionsNo definitive conclusion could be drawn on whether changing nursing staff time or nursing staff coverage models would affect residents’ outcomes based on the research evidence gathered in the SR. RWE analysis helped to fill a gap in the available published literature and allowed policy makers to better understand the impact of revising current regulations based on actual outcomes.

scholarly journals Clutter Cancellation and Long Time Integration for GNSS-Based Passive Bistatic Radar

2021 ◽  
Vol 13 (4) ◽  
pp. 701 ◽  
Author(s):  
Binbin Wang ◽  
Hao Cha ◽  
Zibo Zhou ◽  
Bin Tian
Keyword(s):  
Fourier Transform ◽  
Target Detection ◽  
Time Integration ◽  
Detection Performance ◽  
Bistatic Radar ◽  
Detection Range ◽  
Robust Detection ◽  
Coherent Integration ◽  
Long Time ◽  
Long Time Integration

Clutter cancellation and long time integration are two vital steps for global navigation satellite system (GNSS)-based bistatic radar target detection. The former eliminates the influence of direct and multipath signals on the target detection performance, and the latter improves the radar detection range. In this paper, the extensive cancellation algorithm (ECA), which projects the surveillance channel signal in the subspace orthogonal to the clutter subspace, is first applied in GNSS-based bistatic radar. As a result, the clutter has been removed from the surveillance channel effectively. For long time integration, a modified version of the Fourier transform (FT), called long-time integration Fourier transform (LIFT), is proposed to obtain a high coherent processing gain. Relative acceleration (RA) is defined to describe the Doppler variation results from the motion of the target and long integration time. With the estimated RA, the Doppler frequency shift compensation is carried out in the LIFT. This method achieves a better and robust detection performance when comparing with the traditional coherent integration method. The simulation results demonstrate the effectiveness and advantages of the proposed processing method.

The Relationship Between Brain Fog and Medication Adherence for Individuals With Hypothyroidism

2021 ◽  
pp. 105477382110381
Author(s):  
Kelly Haskard-Zolnierek ◽  
Courtney Wilson ◽  
Julia Pruin ◽  
Rebecca Deason ◽  
Krista Howard
Keyword(s):  
Memory Impairment ◽  
Hormone Replacement ◽  
Long Term Memory ◽  
Adherence Level ◽  
Thyroid Hormone Replacement ◽  
Memory Impairments ◽  
Cognitive Failures ◽  
Short And Long Term ◽  
The Relationship

Individuals with hypothyroidism suffer from symptoms including impairments to cognition (i.e., “brain fog”). Medication can help reduce symptoms of hypothyroidism; however, brain fog may hinder adherence. The aim of this study was to determine if memory impairment and cognitive failures are related to treatment nonadherence in 441 individuals with hypothyroidism. Participants with a diagnosis of hypothyroidism and currently prescribed a thyroid hormone replacement medication were placed in two groups according to adherence level and compared on validated scales assessing impairments to memory and cognition. Results indicated a significant association between treatment nonadherence and self-reported brain fog, represented by greater cognitive and memory impairments. Nonadherent individuals indicated impairments with prospective, retrospective, and short- and long-term memory; and more cognitive failures, compared to adherent individuals. Findings suggest the importance of interventions to enhance adherence for individuals with brain fog, such as encouraging the use of reminders.

Visual search in the (un)real world

2010 ◽  
Author(s):  
Tobit Kollenberg ◽  
Alexander Neumann ◽  
Dorothe Schneider ◽  
Tessa-Karina Tews ◽  
Thomas Hermann ◽  
...  
Keyword(s):  
Visual Search ◽  
Real World

scholarly journals Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization

2021 ◽  
Vol 13 (4) ◽  
pp. 594
Author(s):  
Rui Wang ◽  
Yiming Zhang ◽  
Weiming Tian ◽  
Jiong Cai ◽  
Cheng Hu ◽  
...  
Keyword(s):  
Target Detection ◽  
Computational Cost ◽  
Detection Performance ◽  
Coherent Detection ◽  
Observation Data ◽  
Multimodal Optimization ◽  
Performance Simulation ◽  
Single Target ◽  
Parameter Search ◽  
Long Time

Entomological radars are important for scientific research of insect migration and early warning of migratory pests. However, insects are hard to detect because of their tiny size and highly maneuvering trajectory. Generalized Radon–Fourier transform (GRFT) has been proposed for effective weak maneuvering target detection by long-time coherent detection via jointly motion parameter search, but the heavy computational burden makes it impractical in real signal processing. Particle swarm optimization (PSO) has been used to achieve GRFT detection by fast heuristic parameter search, but it suffers from obvious detection probability loss and is only suitable for single target detection. In this paper, we convert the realization of GRFT into a multimodal optimization problem for insect multi-target detection. A novel niching method without radius parameter is proposed to detect unevenly distributed insect targets. Species reset and boundary constraint strategy are used to improve the detection performance. Simulation analyses of detection performance and computational cost are given to prove the effectiveness of the proposed method. Furthermore, real observation data acquired from a Ku-band entomological radar is used to test this method. The results show that it has better performance on detected target amount and track continuity in insect multi-target detection.

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