Human Factor Study in Gesture Based CAD Environment

2015 ◽  
Author(s):  
Shrey Pareek ◽  
Vaibhav Sharma ◽  
Ehsan T. Esfahani
Keyword(s):  
Input Data ◽  
Human Factor ◽  
User Study ◽  
Computational Cost ◽  
High Extent ◽  
Qualitative And Quantitative ◽  
3D Space ◽  
Factor Study

This study proposes a gesture based CAD interface that uses pose, position, velocity and direction of fingers as input data in order to draw, extrude, scale, translate and rotate an object in the 3D space. The system allows the user to generate basic geometrical primitives and advanced geometries (geometries that cannot be realized using the CSG primitives) and to perform basic CAD operations described above. As opposed to traditional systems wherein path based gestures are used to carry out operations, the proposed system uses switches that operate on simple binary principles thus reducing the computational cost of the system by eliminating the use of a classifier scheme to a high extent. A user study involving 10 subjects is also presented in order to determine the qualitative and quantitative efficacy of the proposed system.

17.3-in Mini-LEDs halo effect and human factor study for high-end notebook application

2019 ◽  
pp. 1490
Author(s):  
Hao-Hao Wu ◽  
Jenn-Jia Su ◽  
Chun-Sheng Li ◽  
Han-Ping Kuo ◽  
Yu-Hsiu Chang ◽  
...  
Keyword(s):  
Human Factor ◽  
Halo Effect ◽  
Factor Study

scholarly journals Comparative evaluation of WIMP and immersive natural finger interaction: a user study on CAD assembly modeling

2021 ◽  
Author(s):  
Marius Fechter ◽  
Benjamin Schleich ◽  
Sandro Wartzack
Keyword(s):  
User Interfaces ◽  
User Study ◽  
Spatial Location ◽  
Ease Of Use ◽  
Natural Interaction ◽  
Assembly Modeling ◽  
3D Space ◽  
Computer Mouse ◽  
Study Results ◽  
Assembly Procedure

AbstractVirtual and augmented reality allows the utilization of natural user interfaces, such as realistic finger interaction, even for purposes that were previously dominated by the WIMP paradigm. This new form of interaction is particularly suitable for applications involving manipulation tasks in 3D space, such as CAD assembly modeling. The objective of this paper is to evaluate the suitability of natural interaction for CAD assembly modeling in virtual reality. An advantage of the natural interaction compared to the conventional operation by computer mouse would indicate development potential for user interfaces of current CAD applications. Our approach bases on two main elements. Firstly, a novel natural user interface for realistic finger interaction enables the user to interact with virtual objects similar to physical ones. Secondly, an algorithm automatically detects constraints between CAD components based solely on their geometry and spatial location. In order to prove the usability of the natural CAD assembly modeling approach in comparison with the assembly procedure in current WIMP operated CAD software, we present a comparative user study. Results show that the VR method including natural finger interaction significantly outperforms the desktop-based CAD application in terms of efficiency and ease of use.

Preparation of Sub-Criteria for Mathematical Modeling of Multi-Criteria Decision Making

2014 ◽  
Vol 1020 ◽  
pp. 765-768
Author(s):  
Eva Berankova ◽  
František Kuda ◽  
Stanislav Endel
Keyword(s):  
Decision Making ◽  
Public Service ◽  
Input Data ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Individual Selection ◽  
Qualitative And Quantitative ◽  
Data Analyses ◽  
Quantitative Characters ◽  
The Subject

The subject of this paper is to evaluate criteria in the decision-making process for choosing new usable office facilities in light of a big company or public service seeking for new usable office facilities. The criteria defining the requirements for individual selection variants enter into this decision-making process. These criteria have qualitative and quantitative characters. In order to model the criteria, it is desirable that their values are standardized. The method of standardization of these criteria is given in this paper. In this paper, attention is paid to the decision-making process in the course of choosing new usable facilities in administration objects. This decision-making process is based on input data analyses and on conclusions for a certain selection variant resulting from them.

Human factor study on the crosstalk of multiview autostereoscopic displays

2010 ◽  
Author(s):  
Jinn-Cherng Yang ◽  
Kuo-Chung Huang ◽  
Chou-Lin Wu ◽  
Kuen Lee ◽  
Sheue-Ling Hwang
Keyword(s):  
Human Factor ◽  
Autostereoscopic Displays ◽  
Factor Study

An Analysis of and Human Factor Study on Access Delay Time to Home Bus

1985 ◽  
Vol CE-31 (3) ◽  
pp. 528-537 ◽  
Author(s):  
N. Ayugase ◽  
H. Kishimoto ◽  
S. Nishimura
Keyword(s):  
Delay Time ◽  
Human Factor ◽  
Access Delay ◽  
Factor Study

scholarly journals Variable Length K-SVD: A New Dictionary Learning Approach and Multi-Stage OMP Method for Sparse Representation

2021 ◽  
Author(s):  
Mahdi Marsousi
Keyword(s):  
Sparse Representation ◽  
Dictionary Learning ◽  
Input Data ◽  
Matching Pursuit ◽  
Computational Cost ◽  
Research Field ◽  
Learning Approach ◽  
Data Set ◽  
Multi Stage ◽  
Blocking Artifact

The Sparse representation research field and applications have been rapidly growing during the past 15 years. The use of overcomplete dictionaries in sparse representation has gathered extensive attraction. Sparse representation was followed by the concept of adapting dictionaries to the input data (dictionary learning). The K-SVD is a well-known dictionary learning approach and is widely used in different applications. In this thesis, a novel enhancement to the K-SVD algorithm is proposed which creates a learnt dictionary with a specific number of atoms adapted for the input data set. To increase the efficiency of the orthogonal matching pursuit (OMP) method, a new sparse representation method is proposed which applies a multi-stage strategy to reduce computational cost. A new phase included DCT (PI-DCT) dictionary is also proposed which significantly reduces the blocking artifact problem of using the conventional DCT. The accuracy and efficiency of the proposed methods are then compared with recent approaches that demonstrate the promising performance of the methods proposed in this thesis.

scholarly journals EVALUATING PRODUCTIVITY TARGET AND ERGONOMICS SAFEGUARD: A HUMAN FACTOR STUDY OF BOTTLE MAKING INDUSTRY

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
HEZEKIAH OLUWOLE ADEYEMI OLUWOLE ADEYEMI
Keyword(s):  
Key Words ◽  
Human Factor ◽  
Health And Safety ◽  
T Test ◽  
Ratio Scale ◽  
Subjective Perceptions ◽  
Factor Study ◽  
Southwest Nigeria ◽  
One Year ◽  
The Relationship

This study evaluated the relationship between machinery operators’ productivity efficiency (MOPE) and the machinery operators’ on-the-job ergonomics satisfactions (MOOES) in Southwest Nigeria bottle making industry (BMI). The MOPE, for a period of one year, was computed for 50 semi-automatic PET blow machines operators in 12 bottle making industries. The subjective perceptions of the workers (category ratio scale - (CRS)) with respect to workloads elements and exposures to machine related hazards were measured using a questionnaire. MOPE results showed 78% of the studied subjects scored about 50% and their productivity were rated average. However, more than 92% of the operators suffered from mental, physical and environmental workload elements. With t- test, MOPE showed statistically significantly higher means value (54.22 ± 2.5, SEM= 1.8) compared to MOOES (34.40 ± 2.75, SEM=.125), t(98) = 23.309, p = .001 hence, were significantly different t- confirming a gap between machinery operators’ ergonomics satisfactions and their productivity levels. The study suggested development of administrative measures capable of bridging the gap to enhance health and safety of the workers. Key words: ergonomics, satisfaction, machinery, operators, productivity, bottle, industry.

scholarly journals Direct micro-seismic event location and characterization from passive seismic data using convolutional neural networks

Geophysics ◽  
2021 ◽  
pp. 1-77
Author(s):  
Hanchen Wang ◽  
Tariq Alkhalifah
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Event Detection ◽  
Seismic Data ◽  
High Performance ◽  
Input Data ◽  
Waveform Inversion ◽  
Computational Cost ◽  
Seismic Events

The ample size of time-lapse data often requires significant event detection and source location efforts, especially in areas like shale gas exploration regions where a large number of micro-seismic events are often recorded. In many cases, the real-time monitoring and locating of these events are essential to production decisions. Conventional methods face considerable drawbacks. For example, traveltime-based methods require traveltime picking of often noisy data, while migration and waveform inversion methods require expensive wavefield solutions and event detection. Both tasks require some human intervention, and this becomes a big problem when too many sources need to be located, which is common in micro-seismic monitoring. Machine learning has recently been used to identify micro-seismic events or locate their sources once they are identified and picked. We propose to use a novel artificial neural network framework to directly map seismic data, without any event picking or detection, to their potential source locations. We train two convolutional neural networks on labeled synthetic acoustic data containing simulated micro-seismic events to fulfill such requirements. One convolutional neural network, which has a global average pooling layer to reduce the computational cost while maintaining high-performance levels, aims to classify the number of events in the data. The other network predicts the source locations and other source features such as the source peak frequencies and amplitudes. To reduce the size of the input data to the network, we correlate the recorded traces with a central reference trace to allow the network to focus on the curvature of the input data near the zero-lag region. We train the networks to handle single, multi, and no event segments extracted from the data. Tests on a simple vertical varying model and a more realistic Otway field model demonstrate the approach's versatility and potential.

scholarly journals STL file format MeshIO class for ITK

2014 ◽  
Author(s):  
Luis Ibanez
Keyword(s):  
Input Data ◽  
Source Code ◽  
Fundamental Principle ◽  
File Format ◽  
Output Data ◽  
Scientific Publications ◽  
Reading And Writing ◽  
Stl File ◽  
3D Space

This document describes the implementation of an ITK class to support the reading and writing of Meshes in STL file format. The Meshes are assumed to contain 2D manifolds embedded in a 3D space. In practice, it would be desirable to use this class mostly to read and write QuadEdgeMeshes.This paper is accompanied with the source code, input data, parameters and output data that the authors used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results.

scholarly journals Why Shape Matters—On the Inherent Qualities of Geometric Shapes for Cartographic Representations

2019 ◽  
Vol 8 (5) ◽  
pp. 217 ◽  
Author(s):  
Silvia Klettner
Keyword(s):  
User Study ◽  
Dimensional Space ◽  
Behavioral Strategies ◽  
Human Communication ◽  
Geometric Shapes ◽  
Qualitative And Quantitative ◽  
Shared Set ◽  
Visual Variables ◽  
Cluster Configuration ◽  
Similarity Judgments

All human communication involves the use of signs. By following a mutually shared set of signs and rules, meaning can be conveyed from one entity to another. Cartographic semiology provides such a theoretical framework, suggesting how to apply visual variables with respect to thematic content. However, semiotics does not address how the choice and composition of such visual variables may lead to different connotations, interpretations, or judgments. The research herein aimed to identify perceived similarities between geometric shape symbols as well as strategies and processes underlying these similarity judgments. Based on a user study with 38 participants, the (dis)similarities of a set of 12 basic geometric shapes (e.g., circle, triangle, square) were examined. Findings from cluster analysis revealed a three-cluster configuration, while multidimensional scaling further quantified the proximities between the geometric shapes in a two-dimensional space. Qualitative and quantitative content analyses identified four strategies underlying the participants’ similarity judgments, namely visual, affective, associative, and behavioral strategies. With the findings combined, this research provides a differentiated perspective on shape proximities, cognitive relations, and the processes involved.

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