Studying vision-based multiple-user interaction with in-home large displays

Recently, event-based social networks(EBSN) such as Meetup, Plancast, and Douban have become popular. As users in the networks usually take groups as an unit to participate in events, it is necessary and meaningful to study effective strategies for recommending events to groups. Existing research on group event recommendation either has the problems of data sparse and cold start due to without considering of social relationships in the networks or makes the assumption that the influence weights between any pair of nodes in the user social graph are equal. In this paper, inspired by the graph neural network and attention mechanism, we propose a novel recommendation model named leveraging social relationship-based graph attention model (SRGAM) for group event recommendation. Specifically, we not only construct a user-event interaction graph and an event-user interaction graph, but also build a user-user social graph and an event-event social graph, to alleviate the problems of data sparse and cold start. In addition, by using a graph attention neural network to learn graph data, we can calculate the influence weight of each node in the graph, thereby generating more reasonable user latent vectors and event latent vectors. Furthermore, we use an attention mechanism to fuse multiple user vectors in a group, so as to generate a high-level group latent vector for rating prediction. Extensive experiments on real-world Meetup datasets demonstrate the effectiveness of the proposed model.

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Plug-in scripts for EFTEM automation

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100165197 ◽

1996 ◽

Vol 54 ◽

pp. 546-547

Author(s):

N. D. Evans ◽

M. K. Kundmann

Keyword(s):

Electron Microscopy ◽

National Laboratory ◽

Oak Ridge ◽

Multiple User ◽

Transmission Electron ◽

Short Period ◽

User Facility ◽

Instrument Control ◽

And Control ◽

Research Equipment

Post-column energy-filtered transmission electron microscopy (EFTEM) is inherently challenging as it requires the researcher to setup, align, and control both the microscope and the energy-filter. The software behind an EFTEM system is therefore critical to efficient, day-to-day application of this technique. This is particularly the case in a multiple-user environment such as at the Shared Research Equipment (SHaRE) User Facility at Oak Ridge National Laboratory. Here, visiting researchers, who may oe unfamiliar with the details of EFTEM, need to accomplish as much as possible in a relatively short period of time.We describe here our work in extending the base software of a commercially available EFTEM system in order to automate and streamline particular EFTEM tasks. The EFTEM system used is a Philips CM30 fitted with a Gatan Imaging Filter (GIF). The base software supplied with this system consists primarily of two Macintosh programs and a collection of add-ons (plug-ins) which provide instrument control, imaging, and data analysis facilities needed to perform EFTEM.

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Serial thin sectioning for pre- and post-embedding immunohistochemistry: Achieving consistent and reliable results for a 3-D reconstruction

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010014748x ◽

1993 ◽

Vol 51 ◽

pp. 328-329

Author(s):

Antonia M. Milroy

Keyword(s):

Nervous System ◽

Computer Assisted ◽

Serial Sectioning ◽

Electron Microscopic ◽

High Quality ◽

New Techniques ◽

3 Dimensional ◽

Multiple User ◽

Thin Sectioning ◽

Subcellular Level

In recent years many new techniques and instruments for 3-Dimensional visualization of electron microscopic images have become available. Higher accelerating voltage through thicker sections, photographed at a tilt for stereo viewing, or the use of confocal microscopy, help to analyze biological material without the necessity of serial sectioning. However, when determining the presence of neurotransmitter receptors or biochemical substances present within the nervous system, the need for good serial sectioning (Fig. 1+2) remains. The advent of computer assisted reconstruction and the possibility of feeding information from the specimen viewing chamber directly into a computer via a camera mounted on the electron microscope column, facilitates serial analysis. Detailed information observed at the subcellular level is more precise and extensive and the complexities of interactions within the nervous system can be further elucidated.We emphasize that serial ultra thin sectioning can be performed routinely and consistently in multiple user electron microscopy laboratories. Initial tissue fixation and embedding must be of high quality.

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Classification of means and methods of the Web semantic retrieval

PROBLEMS IN PROGRAMMING ◽

10.15407/pp2017.01.030 ◽

2017 ◽

pp. 030-050

Author(s):

J.V. Rogushina ◽

Keyword(s):

Search Engines ◽

Domain Knowledge ◽

Information Needs ◽

Web Search ◽

User Interaction ◽

Query Languages ◽

Semantic Search ◽

Semantic Retrieval ◽

The Web

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

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