scholarly journals A large-scale multi-rider matching problem with reneging passengers: single source case

2021 ◽  
Keyword(s):  
Large Scale ◽  
Single Source ◽  
Matching Problem ◽  
Source Case

scholarly journals Large-scale Semantic Parsing without Question-Answer Pairs

2014 ◽  
Vol 2 ◽  
pp. 377-392 ◽  
Author(s):  
Siva Reddy ◽  
Mirella Lapata ◽  
Mark Steedman
Keyword(s):  
Natural Language ◽  
Large Scale ◽  
Graph Matching ◽  
State Of The Art ◽  
The State ◽  
Semantic Parsing ◽  
Matching Problem ◽  
Weak Supervision ◽  
Benchmark Datasets

In this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via semantic graphs whose topology shares many commonalities with Freebase. Given this representation, we conceptualize semantic parsing as a graph matching problem. Our model converts sentences to semantic graphs using CCG and subsequently grounds them to Freebase guided by denotations as a form of weak supervision. Evaluation experiments on a subset of the Free917 and WebQuestions benchmark datasets show our semantic parser improves over the state of the art.

scholarly journals Space-time clustering-based method to optimize shareability in real-time ride-sharing

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262499
Author(s):  
Negin Alisoltani ◽  
Mostafa Ameli ◽  
Mahdi Zargayouna ◽  
Ludovic Leclercq
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Computation Time ◽  
Clustering Method ◽  
Matching Problem ◽  
Solution Quality ◽  
Mobility Service ◽  
Ride Sharing ◽  
Large Scale Problems ◽  
Spatio Temporal

Real-time ride-sharing has become popular in recent years. However, the underlying optimization problem for this service is highly complex. One of the most critical challenges when solving the problem is solution quality and computation time, especially in large-scale problems where the number of received requests is huge. In this paper, we rely on an exact solving method to ensure the quality of the solution, while using AI-based techniques to limit the number of requests that we feed to the solver. More precisely, we propose a clustering method based on a new shareability function to put the most shareable trips inside separate clusters. Previous studies only consider Spatio-temporal dependencies to do clustering on the mobility service requests, which is not efficient in finding the shareable trips. Here, we define the shareability function to consider all the different sharing states for each pair of trips. Each cluster is then managed with a proposed heuristic framework in order to solve the matching problem inside each cluster. As the method favors sharing, we present the number of sharing constraints to allow the service to choose the number of shared trips. To validate our proposal, we employ the proposed method on the network of Lyon city in France, with half-million requests in the morning peak from 6 to 10 AM. The results demonstrate that the algorithm can provide high-quality solutions in a short time for large-scale problems. The proposed clustering method can also be used for different mobility service problems such as car-sharing, bike-sharing, etc.

scholarly journals Prospects of testing an UHECR single source class model with the K-EUSO orbital telescope

2019 ◽  
Vol 210 ◽  
pp. 06011
Author(s):  
Oleg Kalashev ◽  
Maxim Pshirkov ◽  
Mikhail Zotov
Keyword(s):  
Cosmic Rays ◽  
Active Galactic Nuclei ◽  
Large Scale ◽  
Space Station ◽  
Galactic Nuclei ◽  
High Energy ◽  
Single Source ◽  
Class Model ◽  
High Energy Cosmic Rays ◽  
Celestial Sphere

KLYPVE-EUSO (K-EUSO) is a planned orbital detector of ultra-high energy cosmic rays (UHECRs), which is to be deployed on board the International Space Station. K-EUSO is expected to have a uniform exposure over the celestial sphere and register from 120 to 500 UHECRs at energies above 57 EeV in a 2-year mission. We employed the TransportCR and CRPropa 3 packages to estimate prospects of testing a minimal single source class model for extragalactic cosmic rays and neutrinos by Kachelrieß, Kalashev, Ostapchenko and Semikoz (2017) with K-EUSO in terms of the large-scale anisotropy. Nearby active galactic nuclei Centaurus A, M82, NGC 253, M87 and Fornax A were considered as possible sources of UHECRs. We demonstrate that an observation of more than 200 events will allow testing predictions of the model with a high confidence level providing the fraction of events arriving from any of the sources is ^10-15%, with a smaller contribution for larger samples. These numbers agree with theoretical expectations of a possible contribution of a single source in the UHECR flux. Thus, K-EUSO can provide good opportunities for verifying the minimal model basing on an analysis of the large-scale anisotropy of arrival directions of UHECRs.

scholarly journals A facile synthetic route to tungsten diselenide using a new precursor containing a long alkyl chain cation for multifunctional electronic and optoelectronic applications

RSC Advances ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 6169-6176
Author(s):  
Jahee Kim ◽  
Yi Rang Lim ◽  
Yeoheung Yoon ◽  
Wooseok Song ◽  
Bo Keun Park ◽  
...  
Keyword(s):  
Large Scale ◽  
Alkyl Chain ◽  
Low Cost ◽  
Transition Metal Dichalcogenides ◽  
Two Dimensional ◽  
Single Source ◽  
Synthetic Route ◽  
Decomposition Processes ◽  
Metal Dichalcogenides ◽  
Long Alkyl Chain

Single source precursors for coating and subsequent thermal decomposition processes enable a large-scale, low-cost synthesis of two-dimensional transition metal dichalcogenides (TMDs).

Approximate weighted matching on emerging manycore and multithreaded architectures

2012 ◽  
Vol 26 (4) ◽  
pp. 413-430 ◽  
Author(s):  
Mahantesh Halappanavar ◽  
John Feo ◽  
Oreste Villa ◽  
Antonino Tumeo ◽  
Alex Pothen
Keyword(s):  
Approximation Algorithms ◽  
Large Scale ◽  
Scientific Computing ◽  
Graph Matching ◽  
Combinatorial Problem ◽  
Fine Tuning ◽  
Matching Problem ◽  
Weighted Matching ◽  
Wide Range ◽  
The Impact

Graph matching is a prototypical combinatorial problem with many applications in high-performance scientific computing. Optimal algorithms for computing matchings are challenging to parallelize. Approximation algorithms are amenable to parallelization and are therefore important to compute matchings for large-scale problems. Approximation algorithms also generate nearly optimal solutions that are sufficient for many applications. In this paper we present multithreaded algorithms for computing half-approximate weighted matching on state-of-the-art multicore (Intel Nehalem and AMD Magny-Cours), manycore (Nvidia Tesla and Nvidia Fermi), and massively multithreaded (Cray XMT) platforms. We provide two implementations: the first uses shared work queues and is suited for all platforms; and the second implementation, based on dataflow principles, exploits special features available on the Cray XMT. Using a carefully chosen dataset that exhibits characteristics from a wide range of applications, we show scalable performance across different platforms. In particular, for one instance of the input, an R-MAT graph (RMAT-G), we show speedups of about [Formula: see text] on [Formula: see text] cores of an AMD Magny-Cours, [Formula: see text] on [Formula: see text] cores of Intel Nehalem, [Formula: see text] on Nvidia Tesla and [Formula: see text] on Nvidia Fermi relative to one core of Intel Nehalem, and [Formula: see text] on [Formula: see text] processors of Cray XMT. We demonstrate strong as well as weak scaling for graphs with up to a billion edges using up to 12,800 threads. We avoid excessive fine-tuning for each platform and retain the basic structure of the algorithm uniformly across platforms. An exception is the dataflow algorithm designed specifically for the Cray XMT. To the best of the authors' knowledge, this is the first such large-scale study of the half-approximate weighted matching problem on multithreaded platforms. Driven by the critical enabling role of combinatorial algorithms such as matching in scientific computing and the emergence of informatics applications, there is a growing demand to support irregular computations on current and future computing platforms. In this context, we evaluate the capability of emerging multithreaded platforms to tolerate latency induced by irregular memory access patterns, and to support fine-grained parallelism via light-weight synchronization mechanisms. By contrasting the architectural features of these platforms against the Cray XMT, which is specifically designed to support irregular memory-intensive applications, we delineate the impact of these choices on performance.

Performance analysis of G-MUSIC based DOA estimator with random linear array: A single source case

2018 ◽  
Vol 142 ◽  
pp. 513-521 ◽  
Author(s):  
Han-Fei Zhou ◽  
Lei Huang ◽  
Hing Cheung So ◽  
Jian Li
Keyword(s):  
Performance Analysis ◽  
Linear Array ◽  
Single Source ◽  
Source Case

scholarly journals Hydrothermal Synthesis of Bi2S3Nanorods from a Single-Source Precursor and Their Promotional Effect on the Photocatalysis of TiO2

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Juan Lu ◽  
Zuoshan Wang ◽  
Ying Zhang ◽  
Xiufeng Zhou
Keyword(s):  
Large Scale ◽  
Energy Gap ◽  
Catalytic Efficiency ◽  
Orthorhombic Phase ◽  
Catalytic Performance ◽  
Single Source ◽  
Promotional Effect ◽  
Single Source Precursor ◽  
Ca 50 ◽  
Visible Irradiation

As a direct bandgap semiconductor, Bi2S3has the potential ability to improve the photocatalytic activity of nano-TiO2due to its low energy gap (Eg=1.3 eV). In this study, large-scale uniform Bi2S3nanorods were synthesized by a hydrothermal treatment, using Bi[S2P(OC4H9)2]3as the single-source precursor. Characterization results show that as-prepared samples belong to an orthorhombic phase of Bi2S3, and the products mainly crystallize in the form of nanorods which measure ca. 200 nm in length and ca. 50 nm in diameter. The photo-catalytic experiments for the degradation of methyl orange under visible irradiation revealed that a small amount of as-prepared Bi2S3in our study would significantly improve the photo-catalytic activity of nano-TiO2, whether Bi2S3is introduced by a physical way or a chemical way. However, excess Bi2S3will lead to a decrease in the catalytic efficiency of TiO2when Bi2S3was introduced by a chemical way; it never happened when Bi2S3was introduced by a physical way. Even so, among all as-prepared samples, the TiO2-based photo-catalyst with 3 wt.% Bi2S3introduced by a chemical way exhibits the best catalytic performance under visible irradiation.

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