scholarly journals Forming Suitable Groups in MCSCL Environments

2021 ◽  
Vol 17 (1) ◽  
pp. 42-56
Author(s):  
Sofiane Amara ◽  
Fatima Bendella ◽  
Joaquim Macedo ◽  
Alexandre Santos
Keyword(s):  
Learning Environments ◽  
Real World ◽  
Group Formation ◽  
Computer Supported Collaborative Learning ◽  
Mobile Computer ◽  
Homogeneous Groups ◽  
Cluster Distance ◽  
Mixed Groups ◽  
World Environment ◽  
Grouping Algorithm

Given the peculiarities of mobile computer-supported collaborative learning (MCSCL) environments, forming suitable groups in such learning environments represents a hard and time-consuming task. This is because many conditions related to mobile learners, devices, and environment should be considered. Unlike the existing solutions, the present paper shows a grouping approach that allows a customizable formation of (1) homogeneous groups, (2) heterogeneous groups, and (3) mixed groups. The proposed solution does not only help instructors to dynamically form appropriate MCSCL groups, but it also allows to continually control the learners' learning, psychological, and social developments. To assess the effectiveness of the proposed solution, three metrics were used: (1) comparison between the characteristics of the existing group formation tools, (2) average intra-cluster distance of each grouping algorithm, and (3) an experimental evaluation in a real world environment. The obtained results show a great superiority of the proposed solution compared to the existing ones.

Dynamic Group Formation based on a Natural Phenomenon

2016 ◽  
Vol 14 (4) ◽  
pp. 13-26 ◽  
Author(s):  
Amina Zedadra ◽  
Yacine Lafifi ◽  
Ouarda Zedadra
Keyword(s):  
Collaborative Learning ◽  
Group Formation ◽  
Winter Season ◽  
Learning Systems ◽  
Learning System ◽  
Natural Phenomenon ◽  
Cognitive Profiles ◽  
New Approach ◽  
Homogeneous Groups ◽  
Grouping Algorithm

This paper presents a new approach of learners grouping in collaborative learning systems. This grouping process is based on traces left by learners. The goal is the circular dynamic grouping to achieve collaborative projects. The proposed approach consists of two main algorithms: (1) the circular grouping algorithm and (2) the dynamic grouping algorithm (used to update groups). The circular grouping is a novel algorithm to group learners based on their learning and collaborative traces. So, the aim is to form heterogeneous groups based on their profiles. The dynamic grouping algorithm is based on the behavior of penguins when they are moving in the winter season to secure their lives. The new proposed approach used the same behavior of penguins' colony. The proposed approach was applied on a collaborative learning system called LETline 2.0 (http://www.labstic.com/letline/). The developed system was experimented at an Algerian university. After the experiment, the authors observed that their system groups automatically the learners into homogeneous groups and improves their cognitive profiles.

Real-world environment affects the color appearance of virtual stimuli produced by augmented reality

2019 ◽  
Vol 2019 (1) ◽  
pp. 237-242
Author(s):  
Siyuan Chen ◽  
Minchen Wei
Keyword(s):  
Augmented Reality ◽  
Real World ◽  
Mixed Reality ◽  
Rapid Development ◽  
Light Level ◽  
Color Appearance ◽  
Chromatic Adaptation ◽  
Lighting Condition ◽  
The Real ◽  
World Environment

Color appearance models have been extensively studied for characterizing and predicting the perceived color appearance of physical color stimuli under different viewing conditions. These stimuli are either surface colors reflecting illumination or self-luminous emitting radiations. With the rapid development of augmented reality (AR) and mixed reality (MR), it is critically important to understand how the color appearance of the objects that are produced by AR and MR are perceived, especially when these objects are overlaid on the real world. In this study, nine lighting conditions, with different correlated color temperature (CCT) levels and light levels, were created in a real-world environment. Under each lighting condition, human observers adjusted the color appearance of a virtual stimulus, which was overlaid on a real-world luminous environment, until it appeared the whitest. It was found that the CCT and light level of the real-world environment significantly affected the color appearance of the white stimulus, especially when the light level was high. Moreover, a lower degree of chromatic adaptation was found for viewing the virtual stimulus that was overlaid on the real world.

scholarly journals Learning log-based automatic group formation: system design and classroom implementation study

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Changhao Liang ◽  
Rwitajit Majumdar ◽  
Hiroaki Ogata
Keyword(s):  
Collaborative Learning ◽  
Group Work ◽  
Intelligent System ◽  
Group Formation ◽  
Modern Society ◽  
Computer Supported Collaborative Learning ◽  
Classroom Implementation ◽  
Actual Learning ◽  
Group Member ◽  
Learning Log

AbstractCollaborative learning in the form of group work is becoming increasingly significant in education since interpersonal skills count in modern society. However, teachers often get overwhelmed by the logistics involved in conducting any group work. Valid support for executing and managing such activities in a timely and informed manner becomes imperative. This research introduces an intelligent system focusing on group formation which consists of a parameter setting module and the group member visualization panel where the results of the created group are shown to the user and can be graded. The system supports teachers by applying algorithms to actual learning log data thereby simplifying the group formation process and saving time for them. A pilot study in a primary school mathematics class proved to have a positive effect on students’ engagement and affections while participating in group activities based on the system-generated groups, thus providing empirical evidence to the practice of Computer-Supported Collaborative Learning (CSCL) systems.

scholarly journals Impact of Position and Orientation of RFID Tags on Real Time Asset Tracking in a Supply Chain

2008 ◽  
Vol 3 (1) ◽  
pp. 1-12
Author(s):  
Sidney D’Mello ◽  
Eric Mathews ◽  
Lee McCauley ◽  
James Markham
Keyword(s):  
Supply Chain ◽  
Real World ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Rfid Tags ◽  
Vertical Orientation ◽  
Fine Grained ◽  
Asset Tracking ◽  
Transverse Electromagnetic ◽  
World Environment

We studied the characteristics of four commercially available RFID tags such as their orientation on an asset and their position in a three dimensional real world environment to obtain comprehensive data to substantiate a baseline for the use of RFID technology in a diverse supply chain management setting. Using RFID tags manufactured by four different vendors and a GHz Transverse Electromagnetic (GTEM) cell, in which an approximately constant electromagnetic (EM) field was maintained, we characterized the tags based on horizontal and vertical orientation on a simulated asset. With these baseline characteristics determined, we moved two of the four tags through a real world environment in three dimensions using an industrial robotic system to determine the effect of asset position in relation to the reader on tag readability. Combining the data collected over these two studies, we provide a rich analysis of the feasibility of asset tracking in a real world supply chain, where there would likely be multiple tag types. We offer fine grained analyses of the tag types and make recommendations for diverse supply chain asset tracking.

An autonomous excavator system for material loading tasks

2021 ◽  
Vol 6 (55) ◽  
pp. eabc3164
Author(s):  
Liangjun Zhang ◽  
Jinxin Zhao ◽  
Pinxin Long ◽  
Liyang Wang ◽  
Lingfeng Qian ◽  
...  
Keyword(s):  
Real World ◽  
Material Handling ◽  
Texture Classification ◽  
Detection Algorithms ◽  
Unstructured Environments ◽  
Ground Collapse ◽  
Dump Trucks ◽  
Multimodal Perception ◽  
World Environment ◽  
Indoor And Outdoor

Excavators are widely used for material handling applications in unstructured environments, including mining and construction. Operating excavators in a real-world environment can be challenging due to extreme conditions—such as rock sliding, ground collapse, or excessive dust—and can result in fatalities and injuries. Here, we present an autonomous excavator system (AES) for material loading tasks. Our system can handle different environments and uses an architecture that combines perception and planning. We fuse multimodal perception sensors, including LiDAR and cameras, along with advanced image enhancement, material and texture classification, and object detection algorithms. We also present hierarchical task and motion planning algorithms that combine learning-based techniques with optimization-based methods and are tightly integrated with the perception modules and the controller modules. We have evaluated AES performance on compact and standard excavators in many complex indoor and outdoor scenarios corresponding to material loading into dump trucks, waste material handling, rock capturing, pile removal, and trenching tasks. We demonstrate that our architecture improves the efficiency and autonomously handles different scenarios. AES has been deployed for real-world operations for long periods and can operate robustly in challenging scenarios. AES achieves 24 hours per intervention, i.e., the system can continuously operate for 24 hours without any human intervention. Moreover, the amount of material handled by AES per hour is closely equivalent to an experienced human operator.

scholarly journals Real-Time Swarm Search Method for Real-World Quadcopter Drones

2018 ◽  
Vol 8 (7) ◽  
pp. 1169 ◽  
Author(s):  
Ki-Baek Lee ◽  
Young-Joo Kim ◽  
Young-Dae Hong
Keyword(s):  
Real Time ◽  
Optimization Algorithm ◽  
Real World ◽  
Particle Swarm Optimization Algorithm ◽  
Search Method ◽  
Air Pollutant ◽  
Function Optimization ◽  
Benchmark Function ◽  
World Environment ◽  
Repeated Test

This paper proposes a novel search method for a swarm of quadcopter drones. In the proposed method, inspired by the phenomena of swarms in nature, drones effectively look for the search target by investigating the evidence from the surroundings and communicating with each other. The position update mechanism is implemented using the particle swarm optimization algorithm as the swarm intelligence (a well-known swarm-based optimization algorithm), as well as a dynamic model for the drones to take the real-world environment into account. In addition, the mechanism is processed in real-time along with the movements of the drones. The effectiveness of the proposed method was verified through repeated test simulations, including a benchmark function optimization and air pollutant search problems. The results show that the proposed method is highly practical, accurate, and robust.

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