scholarly journals The Smart Skeleton: an open-source, interactive tool for teaching muscle actions and joint movements

2021 ◽  
Vol 45 (2) ◽  
pp. 327-332
Author(s):  
John M. Pattillo
Keyword(s):  
Open Source ◽  
Physical Model ◽  
Software Tool ◽  
Limb Movements ◽  
Anatomy And Physiology ◽  
Interactive Tool ◽  
Open Source Hardware ◽  
Muscle Actions ◽  
Physiology Students ◽  
Design Construction

This paper describes the design, construction, and use of an open-source hardware and software tool intended to help Anatomy and Physiology students test their knowledge of muscle actions and joint movements. Orientation sensors are attached to a model skeleton to turn the skeleton into an interactive, physical model for teaching limb movements. A detailed description of the construction of the tool is provided, as well as the configuration and use of companion software.

scholarly journals Micro-Meta App: an interactive tool for collecting microscopy metadata based on community specifications

2021 ◽  
Vol 18 (12) ◽  
pp. 1489-1495 ◽  
Author(s):  
Alessandro Rigano ◽  
Shannon Ehmsen ◽  
Serkan Utku Öztürk ◽  
Joel Ryan ◽  
Alexander Balashov ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Open Source ◽  
Open Source Software ◽  
Software Tool ◽  
Sharing Value ◽  
Interactive Tool ◽  
Tiered System ◽  
Microscopy Images

AbstractFor quality, interpretation, reproducibility and sharing value, microscopy images should be accompanied by detailed descriptions of the conditions that were used to produce them. Micro-Meta App is an intuitive, highly interoperable, open-source software tool that was developed in the context of the 4D Nucleome (4DN) consortium and is designed to facilitate the extraction and collection of relevant microscopy metadata as specified by the recent 4DN-BINA-OME tiered-system of Microscopy Metadata specifications. In addition to substantially lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training purposes.

ON METHODS OF OBJECT DETECTION IN VIDEO STREAMS

2017 ◽  
Vol 2 (1) ◽  
pp. 80-87
Author(s):  
Puyda V. ◽  
◽  
Stoian. A.
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Open Source ◽  
Feature Detection ◽  
Video Stream ◽  
Object Identification ◽  
Vision Systems ◽  
Modern Computer ◽  
Computer Vision Systems ◽  
Open Source Hardware

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color

scholarly journals Shock tube data processing tools using open source hardware and software platforms

2020 ◽  
Author(s):  
K. Thirumalesh ◽  
Salgeri Puttaswamy Raju ◽  
Hiriyur Mallaiah Somashekarappa ◽  
Kumaraswamy Swaroop
Keyword(s):  
Data Processing ◽  
Shock Tube ◽  
Open Source ◽  
Software Platforms ◽  
Open Source Hardware

scholarly journals Monitoring System for Tracking a PV Generator in an Experimental Smart Microgrid: An Open-Source Solution

2021 ◽  
Vol 13 (15) ◽  
pp. 8182
Author(s):  
José María Portalo ◽  
Isaías González ◽  
Antonio José Calderón
Keyword(s):  
Open Source ◽  
Monitoring System ◽  
Smart Grids ◽  
Raspberry Pi ◽  
Operator Interface ◽  
Open Source Hardware ◽  
Real Time Information ◽  
And Storage ◽  
Time Information ◽  
Pv Generator

Smart grids and smart microgrids (SMGs) require proper monitoring for their operation. To this end, measuring, data acquisition, and storage, as well as remote online visualization of real-time information, must be performed using suitable equipment. An experimental SMG is being deployed that combines photovoltaics and the energy carrier hydrogen through the interconnection of photovoltaic panels, electrolyser, fuel cell, and load around a voltage bus powered by a lithium battery. This paper presents a monitoring system based on open-source hardware and software for tracking the temperature of the photovoltaic generator in such an SMG. In fact, the increases in temperature in PV modules lead to a decrease in their efficiency, so this parameter needs to be measured in order to monitor and evaluate the operation. Specifically, the developed monitoring system consists of a network of digital temperature sensors connected to an Arduino microcontroller, which feeds the acquired data to a Raspberry Pi microcomputer. The latter is accessed by a cloud-enabled user/operator interface implemented in Grafana. The monitoring system is expounded and experimental results are reported to validate the proposal.

An exploration of the factors that contribute to learning satisfaction of first-year anatomy and physiology students

2015 ◽  
Vol 39 (3) ◽  
pp. 158-166 ◽  
Author(s):  
Saramarie Eagleton
Keyword(s):  
Learning Community ◽  
Teaching And Learning ◽  
Community Support ◽  
First Year ◽  
Learning Effectiveness ◽  
Anatomy And Physiology ◽  
Learning Satisfaction ◽  
Use Of Technology ◽  
Teaching Anatomy ◽  
Physiology Students

Lecturers have reverted to using a “blended” approach when teaching anatomy and physiology. Student responses as to how this contributes to their learning satisfaction were investigated using a self-administered questionnaire. The questionnaire consisted of closed- and open-ended questions that were based on three determinants of learning satisfaction: perceived course learnability, learning community support, and perceived learning effectiveness. Regarding course learnability, students responded positively on questions regarding the relevance of the subject for their future careers. However, students identified a number of distractions that prevented them from paying full attention to their studies. As far as learning community support was concerned, respondents indicated that they were more comfortable asking a peer for support if they were unsure of concepts than approaching the lecturing staff. Most of the students study in their second language, and this was identified as a stumbling block for success. There was a difference in opinion among students regarding the use of technology for teaching and learning of anatomy and physiology. From students' perceptions regarding learning effectiveness, it became clear that students' expectations of anatomy and physiology were unrealistic; they did not expect the module to be so comprehensive. Many of the students were also “grade oriented” rather than “learning oriented” as they indicated that they were more concerned about results than “owning” the content of the module. Asking students to evaluate aspects of the teaching and learning process have provided valuable information to improve future offerings of anatomy and physiology.

Retrieval practice is an efficient method of enhancing the retention of anatomy and physiology information

2013 ◽  
Vol 37 (2) ◽  
pp. 184-191 ◽  
Author(s):  
John L. Dobson
Keyword(s):  
Empirical Evidence ◽  
Efficient Method ◽  
Retrieval Practice ◽  
Effective Means ◽  
Control Group ◽  
Effective Strategy ◽  
Anatomy And Physiology ◽  
Or Groups ◽  
Physiology Students ◽  
Initial Retrieval

Although a great deal of empirical evidence has indicated that retrieval practice is an effective means of promoting learning and memory, very few studies have investigated the strategy in the context of an actual class. The primary purpose of this study was to determine if a series of very brief retrieval quizzes could significantly improve the retention of previously tested information throughout an anatomy and physiology course. A second purpose was to determine if there were any significant differences between expanding and uniform patterns of retrieval that followed a standardized initial retrieval delay. Anatomy and physiology students were assigned to either a control group or groups that were repeatedly prompted to retrieve a subset of previously tested course information via a series of quizzes that were administered on either an expanding or a uniform schedule. Each retrieval group completed a total of 10 retrieval quizzes, and the series of quizzes required (only) a total of 2 h to complete. Final retention of the exam subset material was assessed during the last week of the semester. There were no significant differences between the expanding and uniform retrieval groups, but both retained an average of 41% more of the subset material than did the control group (ANOVA, F = 129.8, P = 0.00, ηp2 = 0.36). In conclusion, retrieval practice is a highly efficient and effective strategy for enhancing the retention of anatomy and physiology material.

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