66 research outputs found

    Emerging technologies for learning (volume 1)

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    Collection of 5 articles on emerging technologies and trend

    IE 655-851: Concurrent Engineering

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    Adapt or Die: Aereo, IVI, and the Right of Control in an Evolving Digital Age

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    The advent of the Internet has had a great effect on the production, distribution, and consumption of television programming. The Supreme Court granted certiorari to ABC, Inc. v. Aereo, Inc. and will now review the issue of unlicensed digital distribution of copyrighted programming in its Spring 2014 term. This Comment will first briefly examine the origins and interconnection between television and digital media, culminating in a discussion of the repercussions of allowing unlicensed over-the-top retransmissions of network broadcast programming to continue to stream over the Internet. It will then examine the decisions in WPIX v. IVI, Inc., ABC, Inc. v. Aereo, Inc., and WNET, Thirteen v. Aereo, Inc.—cases recently decided in the Second Circuit. Each involves the topic of Internet retransmissions of copyrighted programming, but they all result in varying outcomes. Finally, this Comment will examine possible solutions to both maintain the integrity of the copyright holder’s right to control distribution and adapt to the consumer demand for Internet consumption

    Three-dimensional media for mobile devices

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    Cataloged from PDF version of article.This paper aims at providing an overview of the core technologies enabling the delivery of 3-D Media to next-generation mobile devices. To succeed in the design of the corresponding system, a profound knowledge about the human visual system and the visual cues that form the perception of depth, combined with understanding of the user requirements for designing user experience for mobile 3-D media, are required. These aspects are addressed first and related with the critical parts of the generic system within a novel user-centered research framework. Next-generation mobile devices are characterized through their portable 3-D displays, as those are considered critical for enabling a genuine 3-D experience on mobiles. Quality of 3-D content is emphasized as the most important factor for the adoption of the new technology. Quality is characterized through the most typical, 3-D-specific visual artifacts on portable 3-D displays and through subjective tests addressing the acceptance and satisfaction of different 3-D video representation, coding, and transmission methods. An emphasis is put on 3-D video broadcast over digital video broadcasting-handheld (DVB-H) in order to illustrate the importance of the joint source-channel optimization of 3-D video for its efficient compression and robust transmission over error-prone channels. The comparative results obtained identify the best coding and transmission approaches and enlighten the interaction between video quality and depth perception along with the influence of the context of media use. Finally, the paper speculates on the role and place of 3-D multimedia mobile devices in the future internet continuum involving the users in cocreation and refining of rich 3-D media content

    Investigating the potential for new media and new technologies in design and technology undergraduate education

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    Investigating Potential for New Media & New Technologies in Design & Technology Undergraduate Education This research explores potential for New Media and New Technology (NM & NT) in the Design School at Loughborough University. Using action research to investigate potential, this research develops a new way of managing inquiry based on Susman and Evered s five cycles of action research (Susman and Evered, 1978). In particular, it extends the double- helix metaphor (Dick, 2000) for action research. This new way of conducting action research looks at educational and IT- based aspects; in particular, developing strategies, guidelines and materials for implementing video podcasting (Vodcasting) and Really Simple Syndication (RSS) into Design School undergraduate modules. In looking at potential, the research involved 6 lecturer s interviews and thematic analysis. Findings suggest that limitations to the current uses of NM & NT related to lecturers lack of skills in NM & NT and scepticism about what the benefits might be. Some recognised potential for NM & NT to manage module administration. One lecturer wanted to stop students using dubious sources from the Internet for assessment on a Sustainable Design module. This led to using RSS to resolve this problem in a mobile learning scenario. In this research, 98 D and T students were surveyed to identify current uses of mobile technology. Results suggested that students would like module content streamed to their mobile device. Lecturers too could see benefits for NM & NT, if they stopped lecturers from having to repeat themselves to students. This led to using Vodcasting to resolve this problem in a mobile learning scenario. Video observational data was collected from 6 students using RSS to perform mobile learning tasks for a Sustainable Design module. The findings suggested that the technology at the time of study was not quite up to the task, although some NM & NT learning resources relating to Sustainable Design were found by students using RSS. Similarly, video observation data was collected from 4 students using Vodcasts to design electronic circuits. Findings showed more technological competence with this technology and students suggested future modules where this type of NM & NT would have further educational potential. Through exploring potential, this research develops new strategies, guidelines and materials for design and technology educators. This research reveals the educational benefits of Vodcasting and RSS in labs and workshops, and concludes that there is potential for NM & NT in D and T education

    Semantics for virtual humans

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    Population of Virtual Worlds with Virtual Humans is increasing rapidly by people who want to create a virtual life parallel to the real one (i.e. Second Life). The evolution of technology is smoothly providing the necessary elements to increase realism within these virtual worlds by creating believable Virtual Humans. However, creating the amount of resources needed to succeed this believability is a difficult task, mainly because of the complexity of the creation process of Virtual Humans. Even though there are many existing available resources, their reusability is difficult because there is not enough information provided to evaluate if a model contains the desired characteristics to be reused. Additionally, the knowledge involved in the creation of Virtual Humans is not well known, nor well disseminated. There are several different creation techniques, different software components, and several processes to carry out before having a Virtual Human capable of populating a virtual environment. The creation of Virtual Humans involves: a geometrical representation with an internal control structure, the motion synthesis with different animation techniques, higher level controllers and descriptors to simulate human-like behavior such individuality, cognition, interaction capabilities, etc. All these processes require the expertise from different fields of knowledge such as mathematics, artificial intelligence, computer graphics, design, etc. Furthermore, there is neither common framework nor common understanding of how elements involved in the creation, development, and interaction of Virtual Humans features are done. Therefore, there is a need for describing (1) existing resources, (2) Virtual Human's composition and features, (3) a creation pipeline and (4) the different levels/fields of knowledge comprehended. This thesis presents an explicit representation of the Virtual Humans and their features to provide a conceptual framework that will interest to all people involved in the creation and development of these characters. This dissertation focuses in a semantic description of Virtual Humans. The creation of a semantic description involves gathering related knowledge, agreement among experts in the definition of concepts, validation of the ontology design, etc. In this dissertation all these procedures are presented, and an Ontology for Virtual Humans is described in detail together with the validations that conducted to the resulted ontology. The goal of creating such ontology is to promote reusability of existing resources; to create a shared knowledge of the creation and composition of Virtual Humans; and to support new research of the fields involved in the development of believable Virtual Humans and virtual environments. Finally, this thesis presents several developments that aim to demonstrate the ontology usability and reusability. These developments serve particularly to support the research on specialized knowledge of Virtual Humans, the population of virtual environments, and improve the believability of these characters

    Application of Common Sense Computing for the Development of a Novel Knowledge-Based Opinion Mining Engine

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    The ways people express their opinions and sentiments have radically changed in the past few years thanks to the advent of social networks, web communities, blogs, wikis and other online collaborative media. The distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand, or organisation. These online social data, however, remain hardly accessible to computers, as they are specifically meant for human consumption. The automatic analysis of online opinions, in fact, involves a deep understanding of natural language text by machines, from which we are still very far. Hitherto, online information retrieval has been mainly based on algorithms relying on the textual representation of web-pages. Such algorithms are very good at retrieving texts, splitting them into parts, checking the spelling and counting their words. But when it comes to interpreting sentences and extracting meaningful information, their capabilities are known to be very limited. Existing approaches to opinion mining and sentiment analysis, in particular, can be grouped into three main categories: keyword spotting, in which text is classified into categories based on the presence of fairly unambiguous affect words; lexical affinity, which assigns arbitrary words a probabilistic affinity for a particular emotion; statistical methods, which calculate the valence of affective keywords and word co-occurrence frequencies on the base of a large training corpus. Early works aimed to classify entire documents as containing overall positive or negative polarity, or rating scores of reviews. Such systems were mainly based on supervised approaches relying on manually labelled samples, such as movie or product reviews where the opinionist’s overall positive or negative attitude was explicitly indicated. However, opinions and sentiments do not occur only at document level, nor they are limited to a single valence or target. Contrary or complementary attitudes toward the same topic or multiple topics can be present across the span of a document. In more recent works, text analysis granularity has been taken down to segment and sentence level, e.g., by using presence of opinion-bearing lexical items (single words or n-grams) to detect subjective sentences, or by exploiting association rule mining for a feature-based analysis of product reviews. These approaches, however, are still far from being able to infer the cognitive and affective information associated with natural language as they mainly rely on knowledge bases that are still too limited to efficiently process text at sentence level. In this thesis, common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques on two common sense knowledge bases was exploited to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data. The engine was tested on three different resources, namely a Twitter hashtag repository, a LiveJournal database and a PatientOpinion dataset, and its performance compared both with results obtained using standard sentiment analysis techniques and using different state-of-the-art knowledge bases such as Princeton’s WordNet, MIT’s ConceptNet and Microsoft’s Probase. Differently from most currently available opinion mining services, the developed engine does not base its analysis on a limited set of affect words and their co-occurrence frequencies, but rather on common sense concepts and the cognitive and affective valence conveyed by these. This allows the engine to be domain-independent and, hence, to be embedded in any opinion mining system for the development of intelligent applications in multiple fields such as Social Web, HCI and e-health. Looking ahead, the combined novel use of different knowledge bases and of common sense reasoning techniques for opinion mining proposed in this work, will, eventually, pave the way for development of more bio-inspired approaches to the design of natural language processing systems capable of handling knowledge, retrieving it when necessary, making analogies and learning from experience
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