Keeping it Real: Encountering Mixed Reality in igloo’s SwanQuake: House

This paper employs the writings of early twentieth-century phenomenologists to examine physical/virtual dualism a century later. It considers the nature of embodied experience in mixed reality environments through an analysis of the author’s encounter with an art installation. The paper reflects on post-Cartesian approaches to the body and new media, noting the resistance of the language of philosophy to the articulation of mixed reality as a concept. If the language of the field constructs dualism, and the cyborgian unitization of human/technology invokes responses of horror or pity, are we prepared socially or culturally to inhabit mixed reality environments as embodied beings

Dance-making on the internet: can on-line choreographic projects foster creativity in the user-participant?

Interactive Internet artworks invite viewers to become involved as user-participants as the creative process unfolds. Through analysis of selected Internet projects, the authors discuss the potential for facilitating an interactive, creative experience for participants in the process of making dance. This study was carried out in 1998 and 1999, but the findings remain relevant, as there have been few subsequent developments in the field

Exploring Latent Semantic Factors to Find Useful Product Reviews

Online reviews provided by consumers are a valuable asset for e-Commerce platforms, influencing potential consumers in making purchasing decisions. However, these reviews are of varying quality, with the useful ones buried deep within a heap of non-informative reviews. In this work, we attempt to automatically identify review quality in terms of its helpfulness to the end consumers. In contrast to previous works in this domain exploiting a variety of syntactic and community-level features, we delve deep into the semantics of reviews as to what makes them useful, providing interpretable explanation for the same. We identify a set of consistency and semantic factors, all from the text, ratings, and timestamps of user-generated reviews, making our approach generalizable across all communities and domains. We explore review semantics in terms of several latent factors like the expertise of its author, his judgment about the fine-grained facets of the underlying product, and his writing style. These are cast into a Hidden Markov Model -- Latent Dirichlet Allocation (HMM-LDA) based model to jointly infer: (i) reviewer expertise, (ii) item facets, and (iii) review helpfulness. Large-scale experiments on five real-world datasets from Amazon show significant improvement over state-of-the-art baselines in predicting and ranking useful reviews

Heat sterilizable Ni-Cd battery development Quarterly report, 1 Jul. - 30 Sep. 1967

Effect of heat sterilization on electrochemistry of nickel-cadmium batterie

Heat sterilizable Ni-Cd battery development Quarterly progress report, 1 Oct. - 31 Dec. 1967

Microscopic, X ray diffraction, porosity, and pore size distribution data for heat sterilizable Ni-Cd batter

Heat sterilizable Ni-Cd battery development Quarterly report, 1 Apr. - 30 Jun. 1968

Development of heat sterilizable, hermetically sealed nickel cadmium batteries for space application

Building artificial personalities: expressive communication channels based on an interlingua for a human-robot dance

The development of artificial personalities requires that we develop a further understanding of how personality is communicated. This can be done through developing humanrobot interaction (HRI). In this paper we report on the development of the SpiderCrab robot. This uses an interlingua based on Laban Movement Analysis (LMA) to intermediate a human-robot dance. Specifically, we developed measurements to analyse data in real time from a simple vision system and implemented a simple stochastic dancing algorithm on a custom built robot. This shows how, through some simple rules, a personality can emerge by biasing random behaviour. The system was tested with professional dancers and members of the public and the results (formal and anecdotal) are presented herein

Missing in Action: Embodied Experience and Virtual Reality

This essay examines embodied experience in virtual reality (VR) theatre, performance art, and installations in one-to-one engagements with virtual worlds and in telematic interactions with other people. It proposes that bodies in VR are blurred, virtual and physical, absent and present, compounded and indivisible, even though body and environment have different materialities. This blurring can cause confusion in the ethics of embodiment that usually govern physical interactions between audience and performer—when, and if, to touch or be touched—since embodied experience confounds cognitive separation between the physical and virtual. Such confusion can result in a mismatch between the embodied self and disembodied Other that the gaming world is poorly equipped to negotiate, but that could have profound effects on VR users. Theatre, on the other hand, is well-versed in the negotiation of the real and the virtual, and virtual environments allow us to ask questions about embodiment and humanity through the experiences of individual bodies in ways that were never previously achievable. How can theatre and performance help us to understand the nature of embodied experience in VR when anything can be done but the body is apparently missing? It becomes possible to explore impossible situations and experiences through the eyes of others. Yet, is it ethically defensible to engage in any experience or action that would not be viable, or perhaps condoned, in the physical world on the basis that it is not “real”? The essay examines the nature of embodied experience in VR and considers the implications for theatre

Sequence-to-Label Script Identification for Multilingual OCR

We describe a novel line-level script identification method. Previous work repurposed an OCR model generating per-character script codes, counted to obtain line-level script identification. This has two shortcomings. First, as a sequence-to-sequence model it is more complex than necessary for the sequence-to-label problem of line script identification. This makes it harder to train and inefficient to run. Second, the counting heuristic may be suboptimal compared to a learned model. Therefore we reframe line script identification as a sequence-to-label problem and solve it using two components, trained end-toend: Encoder and Summarizer. The encoder converts a line image into a feature sequence. The summarizer aggregates the sequence to classify the line. We test various summarizers with identical inception-style convolutional networks as encoders. Experiments on scanned books and photos containing 232 languages in 30 scripts show 16% reduction of script identification error rate compared to the baseline. This improved script identification reduces the character error rate attributable to script misidentification by 33%.Comment: ICDAR2017, The 14th IAPR International Conference on Document Analysis and Recognition, Kyoto, Japa