scholarly journals Comparisons with a “color” component as a means of human assessment (based on the Tatar and Russian languages)

Tatarica ◽  
2021 ◽  
Vol 17 (2) ◽  
pp. 25-44
Author(s):  
Ramziya Bolgarova ◽  
◽  
Nurmukhametova Raushaniya ◽  
Keyword(s):  
Color Component ◽  
Human Assessment

The Load of Perceptual Indifference in Human Cognition of Load Heaviness in Manual Lifting Tasks

1998 ◽  
Vol 42 (12) ◽  
pp. 940-944
Author(s):  
Waldemar Karwowski
Keyword(s):  
Magnitude Estimation ◽  
Quantitative Model ◽  
Cognitive Engineering ◽  
Human Cognition ◽  
Ecological Approach ◽  
Research Approach ◽  
Heavy Load ◽  
Manual Lifting ◽  
New Research ◽  
Human Assessment

This main objective of this study was to introduce and investigate the concept of load of perceptual indifference (LPI) for assessment of load heaviness in manual lifting tasks. The loads of perceptual indifference were defined as those box weights which would result in the same values of subjective compatibility scores for a given pair of perceptual categories of load heaviness. At the point of indifference, the loads are perceived as to be acceptable, safe or not-too-heavy with an equal strength as the loads judged to be too-heavy for continuous lifting. The linguistic magnitude estimation (LME) method (Karwowski, 1990) was used for experimental and modeling purposes. This allowed to develop a quantitative model for the human assessment of four categories of lifted loads of interest. The results indicate that the lack of cognitive benchmark introduces inconsistency in subjects perception of load acceptability and safety compared to the concept of to-heavy load. In order to overcome this problem, a new research approach to manual lifting tasks is needed, based on the integration of cognitive engineering, active psychophysics and ecological approach.

scholarly journals AN EFFECTIVE COLOR FACE RECOGNITION BASED ON BEST COLOR FEATURE SELECTION ALGORITHM USING WEIGHTED FEATURES FUSION SYSTEM

2013 ◽  
Vol 8 (2) ◽  
pp. 787-795
Author(s):  
Sasi Kumar Balasundaram ◽  
J. Umadevi ◽  
B. Sankara Gomathi
Keyword(s):  
Feature Selection ◽  
Face Recognition ◽  
Feature Fusion ◽  
Recognition Performance ◽  
Feature Selection Method ◽  
Recognition Method ◽  
Color Feature ◽  
Color Component ◽  
Pose Variation ◽  
Color Face Recognition

This paper aims to achieve the best color face recognition performance. The newly introduced feature selection method takes advantage of novel learning which is used to find the optimal set of color-component features for the purpose of achieving the best face recognition result. The proposed color face recognition method consists of two parts namely color-component feature selection with boosting and color face recognition solution using selected color component features. This method is better than existing color face recognition methods with illumination, pose variation and low resolution face images. This system is based on the selection of the best color component features from various color models using the novel boosting learning framework. These selected color component features are then combined into a single concatenated color feature using weighted feature fusion. The effectiveness of color face recognition method has been successfully evaluated by the public face databases.

Problems in Human Assessment

1969 ◽  
Vol 6 (1) ◽  
pp. 104
Author(s):  
Max D. Engelhart ◽  
Douglas N. Jackson ◽  
Samuel Messick ◽  
William A. Mehrens ◽  
Robert L. Ebel
Keyword(s):  
Human Assessment

scholarly journals First-in-human evaluation of a hand-held automated venipuncture device for rapid venous blood draws

TECHNOLOGY ◽  
2019 ◽  
Vol 07 (03n04) ◽  
pp. 98-107 ◽  
Author(s):  
Josh M. Leipheimer ◽  
Max L. Balter ◽  
Alvin I. Chen ◽  
Enrique J. Pantin ◽  
Alexander E. Davidovich ◽  
...  
Keyword(s):  
Success Rate ◽  
Central Venous Access ◽  
Venous Blood ◽  
Venous Access ◽  
Arterial Line ◽  
Success Rates ◽  
Healthcare Facilities ◽  
Fluid Delivery ◽  
Human Assessment ◽  
Average Procedure Time

Obtaining venous access for blood sampling or intravenous (IV) fluid delivery is an essential first step in patient care. However, success rates rely heavily on clinician experience and patient physiology. Difficulties in obtaining venous access result in missed sticks and injury to patients, and typically require alternative access pathways and additional personnel that lengthen procedure times, thereby creating unnecessary costs to healthcare facilities. Here, we present the first-in-human assessment of an automated robotic venipuncture device designed to safely perform blood draws on peripheral forearm veins. The device combines ultrasound imaging and miniaturized robotics to identify suitable vessels for cannulation and robotically guide an attached needle toward the lumen center. The device demonstrated results comparable to or exceeding that of clinical standards, with a success rate of 87% on all participants ([Formula: see text]), a 97% success rate on nondifficult venous access participants ([Formula: see text]), and an average procedure time of [Formula: see text][Formula: see text]s ([Formula: see text]). In the future, this device can be extended to other areas of vascular access such as IV catheterization, central venous access, dialysis, and arterial line placement.

Sign in / Sign up

Export Citation Format

Share Document