Learning on the Move in the Web 2.0

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.

Download Full-text

Soft Threshold Ternary Networks

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2020/318 ◽

2020 ◽

Author(s):

Weixiang Xu ◽

Xiangyu He ◽

Tianli Zhao ◽

Qinghao Hu ◽

Peisong Wang ◽

...

Keyword(s):

Neural Networks ◽

Mobile Devices ◽

State Of The Art ◽

Performance Gap ◽

Training Time ◽

Current State ◽

The Arts ◽

Soft Threshold ◽

And Storage ◽

Selection Of

Large neural networks are difficult to deploy on mobile devices because of intensive computation and storage. To alleviate it, we study ternarization, a balance between efficiency and accuracy that quantizes both weights and activations into ternary values. In previous ternarized neural networks, a hard threshold Δ is introduced to determine quantization intervals. Although the selection of Δ greatly affects the training results, previous works estimate Δ via an approximation or treat it as a hyper-parameter, which is suboptimal. In this paper, we present the Soft Threshold Ternary Networks (STTN), which enables the model to automatically determine quantization intervals instead of depending on a hard threshold. Concretely, we replace the original ternary kernel with the addition of two binary kernels at training time, where ternary values are determined by the combination of two corresponding binary values. At inference time, we add up the two binary kernels to obtain a single ternary kernel. Our method dramatically outperforms current state-of-the-arts, lowering the performance gap between full-precision networks and extreme low bit networks. Experiments on ImageNet with AlexNet (Top-1 55.6%), ResNet-18 (Top-1 66.2%) achieves new state-of-the-art.

Download Full-text

Personalized health applications in the Web 2.0: The emergence of a new approach

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology ◽

10.1109/iembs.2010.5628087 ◽

2010 ◽

Cited By ~ 5

Author(s):

L Fernandez-Luque ◽

R Karlsen ◽

T Krogstad ◽

T M Burkow ◽

L K Vognild

Keyword(s):

Web 2.0 ◽

New Approach ◽

Personalized Health ◽

The Web ◽

Health Applications

Download Full-text

Why we need a new approach to teaching digital literacy

Phi Delta Kappan ◽

10.1177/0031721718762419 ◽

2018 ◽

Vol 99 (6) ◽

pp. 27-32 ◽

Cited By ~ 16

Author(s):

Joel Breakstone ◽

Sarah McGrew ◽

Mark Smith ◽

Teresa Ortega ◽

Sam Wineburg

Keyword(s):

Higher Education ◽

Presidential Election ◽

Digital Literacy ◽

Web Searching ◽

Main Approach ◽

New Approach ◽

Approach To Teaching ◽

K 12 ◽

Shed Light ◽

The Web

In recent years — and especially since the 2016 presidential election — numerous media organizations, newspapers, and policy advocates have made efforts to help Americans become more careful consumers of the information they see online. In K-12 and higher education, the main approach has been to provide students with checklists they can use to assess the credibility of individual websites. However, the checklist approach is outdated. It would be far better to teach young people to follow the lead of professional fact-checkers: When confronted by a new and unfamiliar website, they begin by looking elsewhere on the web, searching for any information that might shed light on who created the site in question and for what purpose.

Download Full-text

Unsupervised Action Proposals Using Support Vector Classifiers for Online Video Processing

Sensors ◽

10.3390/s20102953 ◽

2020 ◽

Vol 20 (10) ◽

pp. 2953

Author(s):

Marcos Baptista Ríos ◽

Roberto Javier López-Sastre ◽

Francisco Javier Acevedo-Rodríguez ◽

Pilar Martín-Martín ◽

Saturnino Maldonado-Bascón

Keyword(s):

Video Processing ◽

State Of The Art ◽

Learning To Rank ◽

Support Vector ◽

New Approach ◽

Support Vector Classifier ◽

Current State ◽

Video Frames ◽

Unsupervised Approach ◽

Video Sensor

In this work, we introduce an intelligent video sensor for the problem of Action Proposals (AP). AP consists of localizing temporal segments in untrimmed videos that are likely to contain actions. Solving this problem can accelerate several video action understanding tasks, such as detection, retrieval, or indexing. All previous AP approaches are supervised and offline, i.e., they need both the temporal annotations of the datasets during training and access to the whole video to effectively cast the proposals. We propose here a new approach which, unlike the rest of the state-of-the-art models, is unsupervised. This implies that we do not allow it to see any labeled data during learning nor to work with any pre-trained feature on the used dataset. Moreover, our approach also operates in an online manner, which can be beneficial for many real-world applications where the video has to be processed as soon as it arrives at the sensor, e.g., robotics or video monitoring. The core of our method is based on a Support Vector Classifier (SVC) module which produces candidate segments for AP by distinguishing between sets of contiguous video frames. We further propose a mechanism to refine and filter those candidate segments. This filter optimizes a learning-to-rank formulation over the dynamics of the segments. An extensive experimental evaluation is conducted on Thumos’14 and ActivityNet datasets, and, to the best of our knowledge, this work supposes the first unsupervised approach on these main AP benchmarks. Finally, we also provide a thorough comparison to the current state-of-the-art supervised AP approaches. We achieve 41% and 59% of the performance of the best-supervised model on ActivityNet and Thumos’14, respectively, confirming our unsupervised solution as a correct option to tackle the AP problem. The code to reproduce all our results will be publicly released upon acceptance of the paper.

Download Full-text

A Guideline for Effectively Synthesizing and Characterizing Magnetic Nanoparticles for Advancing Nanobiotechnology: A Review

Sensors ◽

10.3390/s20092554 ◽

2020 ◽

Vol 20 (9) ◽

pp. 2554 ◽

Cited By ~ 4

Author(s):

Mohammad Reza Zamani Kouhpanji ◽

Bethanie J. H. Stadler

Keyword(s):

Magnetic Nanoparticles ◽

Biomedical Applications ◽

State Of The Art ◽

Future Directions ◽

Current State ◽

Pros And Cons ◽

Synthesis Routes ◽

Size And Morphology ◽

Excellent Source ◽

Source Of Information

The remarkable multimodal functionalities of magnetic nanoparticles, conferred by their size and morphology, are very important in resolving challenges slowing the progression of nanobiotechnology. The rapid and revolutionary expansion of magnetic nanoparticles in nanobiotechnology, especially in nanomedicine and therapeutics, demands an overview of the current state of the art for synthesizing and characterizing magnetic nanoparticles. In this review, we explain the synthesis routes for tailoring the size, morphology, composition, and magnetic properties of the magnetic nanoparticles. The pros and cons of the most popularly used characterization techniques for determining the aforementioned parameters, with particular focus on nanomedicine and biosensing applications, are discussed. Moreover, we provide numerous biomedical applications and highlight their challenges and requirements that must be met using the magnetic nanoparticles to achieve the most effective outcomes. Finally, we conclude this review by providing an insight towards resolving the persisting challenges and the future directions. This review should be an excellent source of information for beginners in this field who are looking for a groundbreaking start but they have been overwhelmed by the volume of literature.

Download Full-text

From Community Detection to Mentor Selection in Rating-Free Collaborative Filtering

Advances in Multimedia ◽

10.1155/2011/852518 ◽

2011 ◽

Vol 2011 ◽

pp. 1-19

Author(s):

Armelle Brun ◽

Sylvain Castagnos ◽

Anne Boyer

Keyword(s):

Collaborative Filtering ◽

Recommender Systems ◽

Community Detection ◽

Local Community ◽

State Of The Art ◽

New Approach ◽

Detection Algorithms ◽

Local Community Detection ◽

The Web ◽

Filtering Approach

The number of items that users can now access when navigating on the Web is so huge that these might feel lost. Recommender systems are a way to cope with this profusion of data by suggesting items that fit the users needs. One of the most popular techniques for recommender systems is the collaborative filtering approach that relies on the preferences of items expressed by users, usually under the form of ratings. In the absence of ratings, classical collaborative filtering techniques cannot be applied. Fortunately, the behavior of users, such as their consultations, can be collected. In this paper, we present a new approach to perform collaborative filtering when no rating is available but when user consultations are known. We propose to take inspiration from local community detection algorithms to form communities of users and deduce the set of mentors of a given user. We adapt one state-of-the-art algorithm so as to fit the characteristics of collaborative filtering. Experiments conducted show that the precision achieved is higher then the baseline that does not perform any mentor selection. In addition, our model almost offsets the absence of ratings by exploiting a reduced set of mentors.

Download Full-text

Modern Scientific Visualizations on the Web

Informatics ◽

10.3390/informatics7040037 ◽

2020 ◽

Vol 7 (4) ◽

pp. 37

Author(s):

Loraine Franke ◽

Daniel Haehn

Keyword(s):

Scientific Visualization ◽

State Of The Art ◽

Three Dimensional ◽

Emerging Technology ◽

Research Field ◽

Future Directions ◽

Web Based ◽

Current State ◽

Visualization Systems ◽

The Web

Modern scientific visualization is web-based and uses emerging technology such as WebGL (Web Graphics Library) and WebGPU for three-dimensional computer graphics and WebXR for augmented and virtual reality devices. These technologies, paired with the accessibility of websites, potentially offer a user experience beyond traditional standalone visualization systems. We review the state-of-the-art of web-based scientific visualization and present an overview of existing methods categorized by application domain. As part of this analysis, we introduce the Scientific Visualization Future Readiness Score (SciVis FRS) to rank visualizations for a technology-driven disruptive tomorrow. We then summarize challenges, current state of the publication trend, future directions, and opportunities for this exciting research field.

Download Full-text

Technology in the Cities

Encyclopedia of Information Technology Curriculum Integration ◽

10.4018/978-1-59904-881-9.ch138 ◽

2011 ◽

pp. 881-887

Author(s):

Susan A. Elwood ◽

Marsha Grace ◽

Claudia Lichtenberger

Keyword(s):

Web 2.0 ◽

Mobile Devices ◽

Internet Use ◽

Instant Messaging ◽

Cell Phones ◽

Software Applications ◽

Collaborative Software ◽

Physical Presence ◽

E Mail ◽

The Web

We are making progressive advances towards Weiser’s vision. Technologies are already being embedded into our environment. Smart floors can sense when a person has fallen and immediately send vital information to paramedic support (Abowd, Atkeson, Bobick, Essa, MacIntyre, Mynatt, & Starner, 2000). People are using mobile devices, such as cell phones for e-mail, instant messaging, Web browsing, games, and MP3 playback (Lendino, 2006). Presence technologies are already informing us as to our IM buddy’s physical presence, such as online, off-line, busy, or away from the desk. Current uses of the Web for searching, photos, music, video, various levels of electronic communities, and online, collaborative software applications are preparing users to advance to the next Web 2.0 level of Internet use. Combine Web 2.0 with expanded WiFi capabilities, and we won’t need large computing devices for sharing large amounts of data within virtual, collaborative environments.

Download Full-text

COMPENDIUM: a text summarisation tool for generating summaries of multiple purposes, domains, and genres

Natural Language Engineering ◽

10.1017/s1351324912000198 ◽

2012 ◽

Vol 19 (2) ◽

pp. 147-186 ◽

Cited By ~ 6

Author(s):

ELENA LLORET ◽

MANUEL PALOMAR

Keyword(s):

Web 2.0 ◽

State Of The Art ◽

The State ◽

Textual Entailment ◽

Oriented Approach ◽

The Web

AbstractIn this paper, we present a Text Summarisation tool, compendium, capable of generating the most common types of summaries. Regarding the input, single- and multi-document summaries can be produced; as the output, the summaries can be extractive or abstractive-oriented; and finally, concerning their purpose, the summaries can be generic, query-focused, or sentiment-based. The proposed architecture for compendium is divided in various stages, making a distinction between core and additional stages. The former constitute the backbone of the tool and are common for the generation of any type of summary, whereas the latter are used for enhancing the capabilities of the tool. The main contributions of compendium with respect to the state-of-the-art summarisation systems are that (i) it specifically deals with the problem of redundancy, by means of textual entailment; (ii) it combines statistical and cognitive-based techniques for determining relevant content; and (iii) it proposes an abstractive-oriented approach for facing the challenge of abstractive summarisation. The evaluation performed in different domains and textual genres, comprising traditional texts, as well as texts extracted from the Web 2.0, shows that compendium is very competitive and appropriate to be used as a tool for generating summaries.

Download Full-text