13,593 research outputs found
Utilizing a 3D game engine to develop a virtual design review system
A design review process is where information is exchanged between the designers and design reviewers to resolve any potential design related issues, and to ensure that the interests and goals of the owner are met. The effective execution of design review will minimize potential errors or conflicts, reduce the time for review, shorten the project life-cycle, allow for earlier occupancy, and ultimately translate into significant total project savings to the owner. However, the current methods of design review are still heavily relying on 2D paper-based format, sequential and lack central and integrated information base for efficient exchange and flow of information. There is thus a need for the use of a new medium that allow for 3D visualization of designs, collaboration among designers and design reviewers, and early and easy access to design review information. This paper documents the innovative utilization of a 3D game engine, the Torque Game Engine as the underlying tool and enabling technology for a design review system, the Virtual Design Review System for architectural designs. Two major elements are incorporated; 1) a 3D game engine as the driving tool for the development and implementation of design review processes, and 2) a virtual environment as the medium for design review, where visualization of design and design review information is based on sound principles of GUI design. The development of the VDRS involves two major phases; firstly, the creation of the assets and the assembly of the virtual environment, and secondly, the modification of existing functions or introducing new functionality through programming of the 3D game engine in order to support design review in a virtual environment. The features that are included in the VDRS are support for database, real-time collaboration across network, viewing and navigation modes, 3D object manipulation, parametric input, GUI, and organization for 3D objects
Pyndri: a Python Interface to the Indri Search Engine
We introduce pyndri, a Python interface to the Indri search engine. Pyndri
allows to access Indri indexes from Python at two levels: (1) dictionary and
tokenized document collection, (2) evaluating queries on the index. We hope
that with the release of pyndri, we will stimulate reproducible, open and
fast-paced IR research.Comment: ECIR2017. Proceedings of the 39th European Conference on Information
Retrieval. 2017. The final publication will be available at Springe
Report on the Information Retrieval Festival (IRFest2017)
The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017
Learning to Attend, Copy, and Generate for Session-Based Query Suggestion
Users try to articulate their complex information needs during search
sessions by reformulating their queries. To make this process more effective,
search engines provide related queries to help users in specifying the
information need in their search process. In this paper, we propose a
customized sequence-to-sequence model for session-based query suggestion. In
our model, we employ a query-aware attention mechanism to capture the structure
of the session context. is enables us to control the scope of the session from
which we infer the suggested next query, which helps not only handle the noisy
data but also automatically detect session boundaries. Furthermore, we observe
that, based on the user query reformulation behavior, within a single session a
large portion of query terms is retained from the previously submitted queries
and consists of mostly infrequent or unseen terms that are usually not included
in the vocabulary. We therefore empower the decoder of our model to access the
source words from the session context during decoding by incorporating a copy
mechanism. Moreover, we propose evaluation metrics to assess the quality of the
generative models for query suggestion. We conduct an extensive set of
experiments and analysis. e results suggest that our model outperforms the
baselines both in terms of the generating queries and scoring candidate queries
for the task of query suggestion.Comment: Accepted to be published at The 26th ACM International Conference on
Information and Knowledge Management (CIKM2017
Systematic review and network meta-analysis on the efficacy of evolocumab and other therapies for the management of lipid levels in hyperlipidemia
Background: The proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors evolocumab and alirocumab substantially reduce lowâdensity lipoprotein cholesterol (LDLâC) when added to statin therapy in patients who need additional LDLâC reduction.
Methods and Results: We conducted a systematic review and network metaâanalysis of randomized trials of lipidâlowering therapies from database inception through August 2016 (45 058 records retrieved). We found 69 trials of lipidâlowering therapies that enrolled patients requiring further LDLâC reduction while on maximally tolerated mediumâ or highâintensity statin, of which 15 could be relevant for inclusion in LDLâC reduction networks with evolocumab, alirocumab, ezetimibe, and placebo as treatment arms. PCSK9 inhibitors significantly reduced LDLâC by 54% to 74% versus placebo and 26% to 46% versus ezetimibe. There were significant treatment differences for evolocumab 140 mg every 2 weeks at the mean of weeks 10 and 12 versus placebo (â74.1%; 95% credible interval â79.81% to â68.58%), alirocumab 75 mg (â20.03%; 95% credible interval â27.32% to â12.96%), and alirocumab 150 mg (â13.63%; 95% credible interval â22.43% to â5.33%) at â„12 weeks. Treatment differences were similar in direction and magnitude for PCSK9 inhibitor monthly dosing. Adverse events were similar between PCSK9 inhibitors and control. Rates of adverse events were similar between PCSK9 inhibitors versus placebo or ezetimibe.
Conclusions: PCSK9 inhibitors added to mediumâ to highâintensity statin therapy significantly reduce LDLâC in patients requiring further LDLâC reduction. The network metaâanalysis showed a significant treatment difference in LDLâC reduction for evolocumab versus alirocumab
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