A new approach to performing paper-based children’s spelling tests on mobile devices

2020 ◽  
Author(s):  
Jaline Mombach ◽  
Afonso U. Fonseca ◽  
Thamer H. Nascimento ◽  
Welington Galvao Rodrigues ◽  
Henrique Gressler ◽  
...  
Keyword(s):  
Mobile Devices ◽  
New Approach

Distributed Learning on Mobile Devices: a New Approach to Data Mining in the Internet of Things

2020 ◽  
pp. 1-1
Author(s):  
Xiongtao Zhang ◽  
Xiaomin Zhu ◽  
Weidong Bao ◽  
Laurence T. Yang ◽  
Ji Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Mobile Devices ◽  
Distributed Learning ◽  
The Internet ◽  
New Approach ◽  
The Internet Of Things

scholarly journals A Preliminary Investigation of Malaysian Student’s Daily Use of Mobile Devices as Potential Tools for STEM in a Local University Context

2018 ◽  
Vol 12 (2) ◽  
pp. 80
Author(s):  
Shamsul Arrieya Ariffin ◽  
Salman Firdaus Sidek ◽  
Mohd Fadhil Harfiez Mutalib
Keyword(s):  
Mobile Devices ◽  
Mobile Learning ◽  
Mobile Phones ◽  
Preliminary Investigation ◽  
New Approach ◽  
Preliminary Information ◽  
Science Technology ◽  
Educational Paradigm ◽  
And Mathematics ◽  
Descriptive Survey

<p>Mobile learning is a fairly new approach to the educational paradigm where learning is concerned.  The usage of mobile learning may also be extended to various fields including Science, Technology, Engineering, and Mathematics (STEM).   As Malaysia is lagging behind in STEM, this research is conducted to study preliminary information concerning mobile learning in a local university context, particularly, STEM. The method for this research is a descriptive survey. The results indicate that students already have some skills in using mobile phones, particularly multimedia skills, which can be applied to STEM.</p>

MagiThings

2013 ◽  
Vol 5 (3) ◽  
pp. 23-41 ◽  
Author(s):  
Hamed Ketabdar ◽  
Amin Haji-Abolhassani ◽  
Mehran Roshandel
Keyword(s):  
Magnetic Field ◽  
User Interface ◽  
Mobile Devices ◽  
Mobile Device ◽  
Data Entry ◽  
Field Pattern ◽  
New Approach ◽  
Wide Range ◽  
Device Interaction ◽  
The Magnetic Field

The theory of around device interaction (ADI) has recently gained a lot of attention in the field of human computer interaction (HCI). As an alternative to the classic data entry methods, such as keypads and touch screens interaction, ADI proposes a touchless user interface that extends beyond the peripheral area of a device. In this paper, the authors propose a new approach for around mobile device interaction based on magnetic field. Our new approach, which we call it “MagiThings”, takes the advantage of digital compass (a magnetometer) embedded in new generation of mobile devices such as Apple’s iPhone 3GS/4G, and Google’s Nexus. The user movements of a properly shaped magnet around the device deform the original magnetic field. The magnet is taken or worn around the fingers. The changes made in the magnetic field pattern around the device constitute a new way of interacting with the device. Thus, the magnetic field encompassing the device plays the role of a communication channel and encodes the hand/finger movement patterns into temporal changes sensed by the compass sensor. The mobile device samples momentary status of the field. The field changes, caused by hand (finger) gesture, is used as a basis for sending interaction commands to the device. The pattern of change is matched against pre-recorded templates or trained models to recognize a gesture. The proposed methodology has been successfully tested for a variety of applications such as interaction with user interface of a mobile device, character (digit) entry, user authentication, gaming, and touchless mobile music synthesis. The experimental results show high accuracy in recognizing simple or complex gestures in a wide range of applications. The proposed method provides a practical and simple framework for touchless interaction with mobile devices relying only on an internally embedded sensor and a magnet.

Learning on the Move in the Web 2.0

2013 ◽  
pp. 1693-1714
Author(s):  
Carlos Baladrón ◽  
Javier M. Aguiar ◽  
Lorena Calavia ◽  
Belén Carro ◽  
Antonio Sánchez-Esguevillas
Keyword(s):  
Web 2.0 ◽  
Mobile Devices ◽  
State Of The Art ◽  
New Approach ◽  
Collaborative Tools ◽  
Research And Innovation ◽  
Current State ◽  
Pros And Cons ◽  
Approach To Teaching ◽  
The Web

This work aims at presenting the current state of the art of the m-learning trend, an innovative new approach to teaching focused on taking advantage of mobile devices for learning anytime, anywhere and anyhow, usually employing collaborative tools. However, this new trend is still young, and research and innovation results are still fragmented. This work aims at providing an overview of the state of the art through the analysis of the most interesting initiatives published and reported, studying the different approaches followed, their pros and cons, and their results. And after that, this chapter provides a discussion of where we stand nowadays regarding m-learning, what has been achieved so far, which are the open challenges and where we are heading.

scholarly journals Harmful Content Detection Based on Cascaded Adaptive Boosting

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Seok-Woo Jang ◽  
Sang-Hong Lee
Keyword(s):  
Mobile Devices ◽  
High Performance ◽  
Positional Information ◽  
Detection Algorithm ◽  
Input Image ◽  
Color Information ◽  
Adaptive Boosting ◽  
New Approach ◽  
Adaboost Algorithm ◽  
Harmful Content

Recently, it has become very easy to acquire various types of image contents through mobile devices with high-performance visual sensors. However, harmful image contents such as nude pictures and videos are also distributed and spread easily. Therefore, various methods for effectively detecting and filtering such image contents are being introduced continuously. In this paper, we propose a new approach to robustly detect the human navel area, which is an element representing the harmfulness of the image, using Haar-like features and a cascaded AdaBoost algorithm. In the proposed method, the nipple area of a human is detected first using the color information from the input image and the candidate navel regions are detected using positional information relative to the detected nipple area. Nonnavel areas are then removed from the candidate navel regions and only the actual navel areas are robustly detected through filtering using the Haar-like feature and the cascaded AdaBoost algorithm. The experimental results show that the proposed method extracts nipple and navel areas more precisely than the conventional method. The proposed navel area detection algorithm is expected to be used effectively in various applications related to the detection of harmful contents.

scholarly journals A mobile visual analytics approach for instant trend analysis in mobile contexts

2019 ◽  
Author(s):  
Dirk Burkhardt ◽  
Kawa Nazemi ◽  
Arjan Kuijper ◽  
Egils Ginters
Keyword(s):  
Trend Analysis ◽  
Mobile Devices ◽  
Interaction Design ◽  
Visual Analytics ◽  
Market Analysis ◽  
Analysis Approach ◽  
New Approach ◽  
Business Executives ◽  
Market Trends

"The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design."

Learning on the Move in the Web 2.0

2013 ◽  
pp. 437-458
Author(s):  
Carlos Baladrón ◽  
Javier M. Aguiar ◽  
Lorena Calavia ◽  
Belén Carro ◽  
Antonio Sánchez-Esguevillas
Keyword(s):  
Web 2.0 ◽  
Mobile Devices ◽  
State Of The Art ◽  
New Approach ◽  
Collaborative Tools ◽  
Research And Innovation ◽  
Current State ◽  
Pros And Cons ◽  
Approach To Teaching ◽  
The Web

This work aims at presenting the current state of the art of the m-learning trend, an innovative new approach to teaching focused on taking advantage of mobile devices for learning anytime, anywhere and anyhow, usually employing collaborative tools. However, this new trend is still young, and research and innovation results are still fragmented. This work aims at providing an overview of the state of the art through the analysis of the most interesting initiatives published and reported, studying the different approaches followed, their pros and cons, and their results. And after that, this chapter provides a discussion of where we stand nowadays regarding m-learning, what has been achieved so far, which are the open challenges and where we are heading.

Optimized PCA Based Face Recognition for Mobile Devices

2013 ◽  
Vol 427-429 ◽  
pp. 1682-1686
Author(s):  
Dai Kun Zou ◽  
Wei Hu ◽  
Hong Wei Xia ◽  
Wen Fei Li ◽  
Zhuo Min Yao ◽  
...  
Keyword(s):  
Information Processing ◽  
Face Recognition ◽  
Mobile Devices ◽  
Rapid Development ◽  
Limited Resources ◽  
Basic Information ◽  
Basic Algorithm ◽  
New Approach ◽  
Novel Approach ◽  
Pca Algorithm

With the rapid development of embedded technology, mobile devices have been widely used than before. Face recognition has also been taken as a key application with PCA as the basic algorithm. Though PCA can provide basic information processing, it still has some problems to be used for mobile devices. The movement of the faces increases the difficulty of the recognition and the limited resources of mobile devices propose more constraints to traditional PCA algorithm. A novel approach is presented to optimize PCA based face recognition for better performance and faster recognition speed. The experiments show that the new approach can achieve its target though the optimization.

scholarly journals Autonomous Charging of Electric Vehicles in Industrial Environment

2021 ◽  
Vol 15 (2) ◽  
pp. 220-225
Author(s):  
Mario Hirz ◽  
Bernhard Walzel ◽  
Helmut Brunner
Keyword(s):  
Mobile Devices ◽  
Electric Vehicles ◽  
Vision System ◽  
Robotic System ◽  
New Approach ◽  
Production Logistics ◽  
Industrial Environment ◽  
Industrial Manufacturing ◽  
Different Types ◽  
Electric Powertrains

Modern industrial manufacturing involves several manually and automated driven vehicles - not only for logistics and production purposes, but also for services, maintenance, resources supply and cleaning. These different types of vehicles are increasingly driven by electric powertrains that operate in the production halls, warehouses and other involved areas. Today, electric charging of these mobile devices is accomplished mainly manually and by use of a number of different not standardized charging interfaces, which leads to increased time and cost efforts. The paper evaluates different charging technologies for the use in industrial environments and introduces a new approach for automated, robot-controlled charging of electric vehicles, which is based on a standardized charging interface. The technology has been developed to fully automated charge different types of cars and other vehicles and consists of a vision system to identify the vehicle and the charging connector position in combination with a fully-controlled robotic system that plugs-in and -off the charging connector. In this way, the system is universally applicable for different types of autonomously and manually driven vehicles in a professional context, e.g. in production, logistics and warehouses.

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