scholarly journals Drawing Sequences of Segments in 3D: Kinetic Influences on Arm Configuration

2003 ◽  
Vol 89 (6) ◽  
pp. 3253-3263 ◽  
Author(s):  
Mary D. Klein Breteler ◽  
Jan M. Hondzinski ◽  
Martha Flanders
Keyword(s):  
Data Analysis ◽  
Three Dimensional ◽  
Energetic Efficiency ◽  
Sensorimotor System ◽  
Kinematic Constraints ◽  
3D Space ◽  
Final Approach ◽  
Path Curvature ◽  
Movement Segment ◽  
Segment Data

Complex movements are generally thought to consist of a series of simpler elements. If this is so, how does the sensorimotor system assemble the pieces? This study recorded and evaluated sequences of arm movements to various targets placed in three-dimensional (3D) space. Subjects performed sequences consisting of single, double, or triple segments with the same first target but with different second targets. The data analysis focused on the first movement segment and evaluated hand path curvature, the hand's final approach to the first target, and the whole arm postures at the beginning and end. Although some idiosyncratic differences in approach were observed, only the final arm posture depended, in a consistent way, on which particular movement was to follow as the second segment. This provided evidence for “coarticulation” of the two segments, only at the level of arm posture, and simulations revealed that this anticipatory modification improved the energetic efficiency of the second segment. Data from movements through five consecutive triple segments (i.e., 5 triangles) were assessed to determine whether kinematic constraints, such as Donders' law, apply to repetitive drawing movements. Although such constraints could prevent the accumulation of changes in arm posture, this was not observed. Instead, in most cases, the elbow was a little bit higher at the end of each triangle than at the beginning. Taken together, the results suggest that coarticulation may facilitate the joining of two segments and the efficiency of the second movement, but does not extend over the drawing of several segments.

scholarly journals Design, Fabrication, and Testing of a Novel 3D 3-Fingered Electrothermal Microgripper with Multiple Degrees of Freedom

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 444
Author(s):  
Guoning Si ◽  
Liangying Sun ◽  
Zhuo Zhang ◽  
Xuping Zhang
Keyword(s):  
Degrees Of Freedom ◽  
Dynamic Properties ◽  
Three Dimensional ◽  
Polyimide Film ◽  
Zebrafish Embryos ◽  
Multiple Degrees Of Freedom ◽  
Electrothermal Actuator ◽  
3D Space ◽  
Pick And Place

This paper presents the design, fabrication, and testing of a novel three-dimensional (3D) three-fingered electrothermal microgripper with multiple degrees of freedom (multi DOFs). Each finger of the microgripper is composed of a V-shaped electrothermal actuator providing one DOF, and a 3D U-shaped electrothermal actuator offering two DOFs in the plane perpendicular to the movement of the V-shaped actuator. As a result, each finger possesses 3D mobilities with three DOFs. Each beam of the actuators is heated externally with the polyimide film. The durability of the polyimide film is tested under different voltages. The static and dynamic properties of the finger are also tested. Experiments show that not only can the microgripper pick and place microobjects, such as micro balls and even highly deformable zebrafish embryos, but can also rotate them in 3D space.

A biomimetic 3D airflow sensor made of an array of two piezoelectric metal-core fibers

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 312-321 ◽  
Author(s):  
Yixiang Bian ◽  
Can He ◽  
Kaixuan Sun ◽  
Longchao Dai ◽  
Hui Shen ◽  
...  
Keyword(s):  
Design Methodology ◽  
Spherical Surface ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Piezoceramic Cylinder ◽  
Metal Core ◽  
Content Type ◽  
3D Space ◽  
Highly Sensitive ◽  
Airflow Sensor

Purpose The purpose of this paper is to design and fabricate a three-dimensional (3D) bionic airflow sensing array made of two multi-electrode piezoelectric metal-core fibers (MPMFs), inspired by the structure of a cricket’s highly sensitive airflow receptor (consisting of two cerci). Design/methodology/approach A metal core was positioned at the center of an MPMF and surrounded by a hollow piezoceramic cylinder. Four thin metal films were spray-coated symmetrically on the surface of the fiber that could be used as two pairs of sensor electrodes. Findings In 3D space, four output signals of the two MPMFs arrays can form three “8”-shaped spheres. Similarly, the sensing signals for the same airflow are located on a spherical surface. Originality/value Two MPMF arrays are sufficient to detect the speed and direction of airflow in all three dimensions.

On the Flexural-Torsional Behavior of a Straight Elastic Beam Subject to Terminal Moments

1993 ◽  
Vol 60 (2) ◽  
pp. 498-505 ◽  
Author(s):  
Z. Tan ◽  
J. A. Witz
Keyword(s):  
Coordinate System ◽  
Cross Section ◽  
Equilibrium Equation ◽  
Three Dimensional ◽  
Circular Cross Section ◽  
Elastic Beam ◽  
Cartesian Coordinate System ◽  
Kinematic Constraints ◽  
Torsional Behavior ◽  
Cartesian Coordinate

This paper discusses the large-displacement flexural-torsional behavior of a straight elastic beam with uniform circular cross-section subject to arbitrary terminal bending and twisting moments. The beam is assumed to be free from any kinematic constraints at both ends. The equilibrium equation is solved analytically with the full expression for curvature to obtain the deformed configuration in a three-dimensional Cartesian coordinate system. The results show the influence of the terminal moments on the beam’s deflected configuration.

Three-Dimensional Curve Tracking for Particles Using Gyroscopic Control

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Chuanfeng Wang
Keyword(s):  
Tracking Control ◽  
Three Dimensional ◽  
Smooth Curve ◽  
Autonomous Agent ◽  
Control Law ◽  
Steering Control ◽  
3D Space ◽  
Moving Direction ◽  
Tangent Direction ◽  
Curve Tracking

Curve-tracking control is challenging and fundamental in many robotic applications for an autonomous agent to follow a desired path. In this paper, we consider a particle, representing a fully actuated autonomous robot, moving at unit speed under steering control in the three-dimensional (3D) space. We develop a feedback control law that enables the particle to track any smooth curve in the 3D space. Representing the 3D curve in the natural Frenet frame, we construct the control law under which the moving direction of the particle will be aligned with the tangent direction of the desired curve and the distance between the particle and the desired curve will converge to zero. We demonstrate the effectiveness of the proposed 3D curve-tracking control law in simulations.

Measurement on Reaction Time of Visual Attention in Depth during Driving

2013 ◽  
Vol 319 ◽  
pp. 343-347
Author(s):  
Ru Ting Xia ◽  
Xiao Yan Zhou
Keyword(s):  
Reaction Time ◽  
Visual Attention ◽  
Measurement System ◽  
Low Vision ◽  
Three Dimensional ◽  
Depth Information ◽  
Attention Shifting ◽  
3D Space ◽  
Traffic Environment ◽  
3D Attention

This research aimed to reveal characteristics of visual attention of low-vision drivers. Near and far stimuli were used by means of a three-dimensional (3D) attention measurement system that simulated traffic environment. We measured the reaction time of subjects while attention shifted in three kinds of imitational peripheral environment illuminance (daylight, twilight and dawn conditions). Subjects were required to judge whether the target presented nearer than fixation point or further than it. The results showed that the peripheral environment illuminance had evident influence on the reaction time of drivers, the reaction time was slow in dawn and twilight conditions than in daylight condition, distribution of attention had the advantage in nearer space than farther space, that is, and the shifts of attention in 3D space had an anisotropy characteristic in depth. The results suggested that (1) visual attention might be operated with both precueing paradigm and stimulus controls included the depth information, (2) an anisotropy characteristic of attention shifting depend on the attention moved distance, and it showed remarkably in dawn condition than in daylight and twilight conditions.

scholarly journals Pengaruh Penggunaan Power Point Berbasis Animasi terhadap Hasil Belajar Siswa pada Materi Dimensi Tiga

2020 ◽  
Vol 1 (2) ◽  
pp. 75-82
Author(s):  
Salmun K. Nasib ◽  
Abas Kaluku ◽  
Abdul Wahab Abdullah
Keyword(s):  
Data Analysis ◽  
Experimental Design ◽  
Student Learning ◽  
Learning Outcomes ◽  
Descriptive Analysis ◽  
Three Dimensional ◽  
Sampling Technique ◽  
Student Learning Outcomes ◽  
Power Point ◽  
Cluster Random Sampling

This article discusses the use of PowerPoint animation in learning with the aim of knowing the differences in learning outcomes of students whose learning uses power points and without using power points in three-dimensional topics. The method used is an experimental design with a True Experimental Design, namely Posttest-Only Design. The sampling technique used cluster random sampling. Student learning outcomes data were obtained through the learning outcome test instrument in the form of essays. Data analysis using descriptive analysis techniques and inferential data analysis. Hypothesis testing using a parametric analysis t-test. The results of the analysis show that the average learning outcomes of students who are taught using power points are higher than those of students taught conventionally. One of the factors that support the improvement of student learning outcomes is a learning approach to geometric shapes that involves interesting visualization. Interesting visualization makes students not just imagine something abstract but can directly observe the object being studied.

scholarly journals Efficient Escherichia coli (E. coli) Trapping and Retrieval from Bodily Fluids via a Three-Dimensional (3D) Microbeads Stacked Nano-Device

2019 ◽  
Author(s):  
Xinye Chen ◽  
Abbi miller ◽  
Shengting Cao ◽  
Yu Gan ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Flow Rate ◽  
Magnetic Beads ◽  
Three Dimensional ◽  
E Coli ◽  
Bodily Fluids ◽  
3D Space ◽  
Fluidic Device ◽  
Computational Fluid Dynamics Cfd ◽  
On Chip

<div>A micro- and nano-fluidic device stacked with magnetic beads is developed to efficiently trap, concentrate, and retrieve Escherichia coli (E. coli) from bacteria suspension</div><div>and pig plasma. The small voids between the magnetic beads are used to physically isolate the bacteria in the device. We use computational fluid dynamics (CFD), 3D</div><div>tomography technology, and machine learning to probe and explain the bead stacking in a small 3D space with various flow rates. A combination of beads with different sizes is utilized to achieve a high capture efficiency of ~86% with a flow rate of 50 μL/min. Leveraging the high deformability of this device, the E. coli sample is retrieved from the designated bacteria suspension by applying a higher flow rate, followed by rapid magnetic separation. This unique function is also utilized to concentrate E. coli from the original bacteria suspension. An on-chip concentration</div><div>factor of ~11× is achieved by inputting 1,300 μL of the E. coli sample and then concentrating it in 100 μL buffer.</div><div>Importantly, this multiplexed, miniaturized, inexpensive, and transparent device is easy to fabricate and operate, making it ideal for pathogen separation in both laboratory and pointof- care (POC) settings.</div>

scholarly journals Efficient Escherichia coli (E. coli) Trapping and Retrieval from Bodily Fluids via a Three-Dimensional (3D) Microbeads Stacked Nano-Device

2019 ◽  
Author(s):  
Xinye Chen ◽  
Abbi miller ◽  
Shengting Cao ◽  
Yu Gan ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Flow Rate ◽  
Magnetic Beads ◽  
Three Dimensional ◽  
E Coli ◽  
Bodily Fluids ◽  
3D Space ◽  
Fluidic Device ◽  
Computational Fluid Dynamics Cfd ◽  
On Chip

<div>A micro- and nano-fluidic device stacked with magnetic beads is developed to efficiently trap, concentrate, and retrieve Escherichia coli (E. coli) from bacteria suspension</div><div>and pig plasma. The small voids between the magnetic beads are used to physically isolate the bacteria in the device. We use computational fluid dynamics (CFD), 3D</div><div>tomography technology, and machine learning to probe and explain the bead stacking in a small 3D space with various flow rates. A combination of beads with different sizes is utilized to achieve a high capture efficiency of ~86% with a flow rate of 50 μL/min. Leveraging the high deformability of this device, the E. coli sample is retrieved from the designated bacteria suspension by applying a higher flow rate, followed by rapid magnetic separation. This unique function is also utilized to concentrate E. coli from the original bacteria suspension. An on-chip concentration</div><div>factor of ~11× is achieved by inputting 1,300 μL of the E. coli sample and then concentrating it in 100 μL buffer.</div><div>Importantly, this multiplexed, miniaturized, inexpensive, and transparent device is easy to fabricate and operate, making it ideal for pathogen separation in both laboratory and pointof- care (POC) settings.</div>

Automatic Diagnosis of Alzheimer’s Disease Using Deep Learning Techniques

2021 ◽  
Vol 19 (11) ◽  
pp. 126-140
Author(s):  
Zahraa S. Aaraji ◽  
Hawraa H. Abbas
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Data Analysis ◽  
Binary Classification ◽  
Brain Mri ◽  
Three Dimensional ◽  
Structural Variations ◽  
Automatic Feature Extraction ◽  
Multi Class Classification

Neuroimaging data analysis has attracted a great deal of attention with respect to the accurate diagnosis of Alzheimer’s disease (AD). Magnetic Resonance Imaging (MRI) scanners have thus been commonly used to study AD-related brain structural variations, providing images that demonstrate both morphometric and anatomical changes in the human brain. Deep learning algorithms have already been effectively exploited in other medical image processing applications to identify features and recognise patterns for many diseases that affect the brain and other organs; this paper extends on this to describe a novel computer aided software pipeline for the classification and early diagnosis of AD. The proposed method uses two types of three-dimensional Convolutional Neural Networks (3D CNN) to facilitate brain MRI data analysis and automatic feature extraction and classification, so that pre-processing and post-processing are utilised to normalise the MRI data and facilitate pattern recognition. The experimental results show that the proposed approach achieves 97.5%, 82.5%, and 83.75% accuracy in terms of binary classification AD vs. cognitively normal (CN), CN vs. mild cognitive impairment (MCI) and MCI vs. AD, respectively, as well as 85% accuracy for multi class-classification, based on publicly available data sets from the Alzheimer’s disease Neuroimaging Initiative (ADNI).

Sign in / Sign up

Export Citation Format

Share Document