A Semantic-Driven Model for Ranking Digital Learning Objects Based on Diversity in the User Comments

This paper presents a computational model for measuring diversity in terms of variety, balance and disparity. This model is informed by the Stirling’s framework for understanding diversity from social science and underpinned by semantic techniques from computer science. A case study in learning is used to illustrate the application of the model. It is driven by the desire to broaden learners’ perspectives in an increasingly diverse and inclusive society. For example, interpreting body language in a job interview may be influenced by the different background of observers. With the explosion of digital objects on social platforms, selecting the appropriate ones for learning can be challenging and time consuming. The case study uses over 2000 annotated comments from 51 YouTube videos on job interviews. Diversity indicators are produced based on the comments for each video, which in turn facilitate the ranking of the videos according to the degree of diversity in the comments for the selected domain

A survey of free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle

The objective of this paper is to analyze free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle (UAV). Free software is the best choice when the reduction of production costs is necessary; nevertheless, the quality of free software may vary. This paper probably does not include all of the free software, but tries to describe or mention at least the most interesting programs. The first part of this paper summarizes the essential knowledge about UAVs, including the fundamentals of flight mechanics and aerodynamics, and the structure of a UAV system. The second section generally explains the modelling and simulation of a UAV. In the main section, more than 50 free programs for the design, analysis, modelling, and simulation of a UAV are described. Although the selection of the free software has been focused on small subsonic UAVs, the software can also be used for other categories of aircraft in some cases; e.g. for MAVs and large gliders. The applications with an historical importance are also included. Finally, the results of the analysis are evaluated and discussed—a block diagram of the free software is presented, possible connections between the programs are outlined, and future improvements of the free software are suggested. © 2015, CIMNE, Barcelona, Spain.Internal Grant Agency of Tomas Bata University in Zlin [IGA/FAI/2015/001, IGA/FAI/2014/006

History-Dependent Excitability as a Single-Cell Substrate of Transient Memory for Information Discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron “sees” through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types

Manufacture Techniques of Chitosan-Based Microcapsules to Enhance Functional Properties of Textiles

In recent years, the textile industry has been moving to novel concepts of products, which could deliver to the user, improved performances. Such smart textiles have been proven to have the potential to integrate within a commodity garment advanced feature and functional properties of different kinds. Among those functionalities, considerable interest has been played in functionalizing commodity garments in order to make them positively interact with the human body and therefore being beneficial to the user health. This kind of functionalization generally exploits biopolymers, a class of materials that possess peculiar properties such as biocompatibility and biodegradability that make them suitable for bio-functional textile production. In the context of biopolymer chitosan has been proved to be an excellent potential candidate for this kind of application given its abundant availability and its chemical properties that it positively interacts with biological tissue. Notwithstanding the high potential of chitosan-based technologies in the textile sectors, several issues limit the large-scale production of such innovative garments. In facts the morphologies of chitosan structures should be optimized in order to make them better exploit the biological activity; moreover a suitable process for the application of chitosan structures to the textile must be designed. The application process should indeed not only allow an effective and durable fixation of chitosan to textile but also comply with environmental rules concerning pollution emission and utilization of harmful substances. This chapter reviews the use of microencapsulation technique as an approach to effectively apply chitosan to the textile material while overcoming the significant limitations of finishing processes. The assembly of chitosan macromolecules into microcapsules was proved to boost the biological properties of the polymer thanks to a considerable increase in the surface area available for interactions with the living tissues. Moreover, the incorporation of different active substances into chitosan shells allows the design of multifunctional materials that effectively combine core and shell properties. Based on the kind of substances to be incorporated, several encapsulation processes have been developed. The literature evidences how the proper choices concerning encapsulation technology, chemical formulations, and process parameter allow tuning the properties and the performances of the obtained microcapsules. Furthermore, the microcapsules based finishing process have been reviewed evidencing how the microcapsules morphology can positively interact with textile substrate allowing an improvement in the durability of the treatment. The application of the chitosan shelled microcapsules was proved to be capable of imparting different functionalities to textile substrates opening possibilities for a new generation of garments with improved performances and with the potential of protecting the user from multiple harms. Lastly, a continuous interest was observed in improving the process and formulation design in order to avoid the usage of toxic substances, therefore, complying with an environmentally friendly approach

Am¯ir-i kab¯ir / A

A large amount of social feedback expressed by social signals (e.g. like, +1, rating) are assigned to web resources. These signals are often exploited as additional sources of evidence in search engines. Our objective in this paper is to study the impact of the new social signals, called Facebook reactions (love, haha, angry, wow, sad) in the retrieval. These reactions allow users to express more nuanced emotions compared to classic signals (e.g. like, share). First, we analyze these reactions and show how users use these signals to interact with posts. Second, we evaluate the impact of each such reaction in the retrieval, by comparing them to both the textual model without social features and the first classical signal (like-based model). These social features are modeled as document prior and are integrated into a language model. We conducted a series of experiments on IMDb dataset. Our findings reveal that incorporating social features is a promising approach for improving the retrieval ranking performance

Get Your Game On @ the Library: Collaboration Between the Learning Commons and Office of Information Technologies

Get Your Game On @ the Library is an event series collaboration between the Learning Commons and the Office of Information Technologies geared to increase student comfort and familiarity with library spaces and staff, and build community across campus groups and departments through tabletop, board, card, and video games. This session will look a the planning, workflow and implementation of the series, with multimedia examples and video testimonials

Heterogeneous sulfoxidation of thioethers by hydrogen peroxide over layered double hydroxides as catalysts

International audienceA new method for mild oxidation of thioethers with hydrogen peroxide in heterogeneous catalysis is described. The layered double hydroxides (or hydrotalcite-like materials) act as basic catalysts for the sulfoxidation reaction with hydrogen peroxide in the presence of acetonitrile. The influence of the nature of thioether, the type of catalyst, the reaction temperature and reaction time on the catalytic activity and selectivity in this reaction has been investigated. A mechanism of the sulfoxidation reaction is proposed. © 2001 Elsevier Science B.V

Analyzing and Mining Comments and Comment Ratings on the Social Web

An analysis of the social video sharing platform YouTube and the news aggregator Yahoo! News reveals the presence of vast amounts of community feedback through comments for published videos and news stories, as well as through metaratings for these comments. This article presents an in-depth study of commenting and comment rating behavior on a sample of more than 10 million user comments on YouTube and Yahoo! News. In this study, comment ratings are considered first-class citizens. Their dependencies with textual content, thread structure of comments, and associated content (e.g., videos and their metadata) are analyzed to obtain a comprehensive understanding of the community commenting behavior. Furthermore, this article explores the applicability of machine learning and data mining to detect acceptance of comments by the community, comments likely to trigger discussions, controversial and polarizing content, and users exhibiting offensive commenting behavior. Results from this study have potential application in guiding the design of community-oriented online discussion platforms