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Register a new userCustomization and modifications of SignWriting by LIS users
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Added by
Claudia Savina Bianchini
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Historically, the various sign languages (SL) have not developed an own writing system; nevertheless, some systems exist, among which the SignWriting (SW) is a powerful and flexible one. In this paper, we present the mechanisms adopted by signers of the Italian Sign Language (LIS), expert users of SW, to modify the standard SW glyphs and increase their writing skills and/or represent peculiar linguistic phenomena. We identify these glyphs and show which characteristics make them acceptable by the expert community. Eventually, we analyze the potentialities of these glyphs in hand writing and in computer-assisted writing, focusing on SWift, a software designed to allow the electronic writing-down of user-modified glyphs.
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We present SWift (SignWriting improved fast transcriber), an advanced editor for computer-aided writing and transcribing using SignWriting (SW). SW is devised to allow deaf people and linguists alike to exploit an easy-to-grasp written form of (any) sign language. Similarly, SWift has been developed for everyone who masters SW, and is not exclusively deaf-oriented. Using SWift, it is possible to compose and save any sign, using elementary components called glyphs. A guided procedure facilitates the composition process. SWift is aimed at helping to break down the electronic barriers that keep the deaf community away from Information and Communication Technology (ICT). The editor has been developed modularly and can be integrated everywhere the use of SW, as an alternative to written vocal language, may be advisable.
The dissemination of fake news significantly affects personal reputation and public trust. Recently, fake news detection has attracted tremendous attention, and previous studies mainly focused on finding clues from news content or diffusion path. However, the required features of previous models are often unavailable or insufficient in early detection scenarios, resulting in poor performance. Thus, early fake news detection remains a tough challenge. Intuitively, the news from trusted and authoritative sources or shared by many users with a good reputation is more reliable than other news. Using the credibility of publishers and users as prior weakly supervised information, we can quickly locate fake news in massive news and detect them in the early stages of dissemination. In this paper, we propose a novel Structure-aware Multi-head Attention Network (SMAN), which combines the news content, publishing, and reposting relations of publishers and users, to jointly optimize the fake news detection and credibility prediction tasks. In this way, we can explicitly exploit the credibility of publishers and users for early fake news detection. We conducted experiments on three real-world datasets, and the results show that SMAN can detect fake news in 4 hours with an accuracy of over 91%, which is much faster than the state-of-the-art models.
Users of electronic devices, e.g., laptop, smartphone, etc. have characteristic behaviors while surfing the Web. Profiling this behavior can help identify the person using a given device. In this paper, we introduce a technique to profile users based on their web transactions. We compute several features extracted from a sequence of web transactions and use them with one-class classification techniques to profile a user. We assess the efficacy and speed of our method at differentiating 25 users on a dataset representing 6 months of web traffic monitoring from a small company network.
Highly ordered periodic arrays of silver nanoparticles have been fabricated which exhibit surface plasmon resonances in the visible spectrum. We demonstrate the ability of these structures to alter the fluorescence properties of vicinal dye molecules by providing an additional radiative decay channel. Using fluorescence lifetime imaging microscopy (FLIM), we have created high resolution spatial maps of the molecular lifetime components; these show an order of magnitude increase in decay rate from a localized volume around the nanoparticles, resulting in a commensurate enhancement in the fluorescence emission intensity.
Inactivation of microorganisms on sensitive surfaces by cold atmospheric plasma (CAP) is one major application in the field of plasma medicine because it provides a simple and effective way to sterilize heat-sensitive materials. Therefore, one has to know whether plasma treatment affects the treated surfaces, and thus causes long-term surface modifications. In this contribution, the effect of cold atmospheric Surface Micro-Discharge (SMD) plasma on different materials and its sporicidal behavior was investigated. Hence, different material samples (stainless steel, different polymers and glass) were plasma-treated for 16 hours, simulating multiple plasma treatments using an SMD plasma device. Afterwards, the material samples were analyzed using surface analysis methods such as laser microscopy, contact angle measurements and X-ray photoelectron spectroscopy (XPS). Furthermore, the device was used to investigate the behavior of Bacillus atrophaeus endospores inoculated on material samples at different treatment times. The interaction results for plasma-treated endospores show, that a log reduction of the spore count between 4.3 and 6.2 can be achieved within 15 min of plasma treatment. Besides, the surface analysis revealed, that there were three different types of reactions the probed materials showed to plasma treatment, ranging from no changes to shifts of the materials free surface energies and oxidation. As a consequence, it should be taken into account that even though cold atmospheric plasma treatment is a non-thermal method to inactivate microorganisms on heatsensitive materials, it still affects surface properties of the treated materials. Therefore, the focus of future work must be a further classification of plasma-caused material modifications.
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