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Adjacency list

About: Adjacency list is a research topic. Over the lifetime, 4419 publications have been published within this topic receiving 78449 citations.


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Journal ArticleDOI
TL;DR: In this paper, the influence of aerosol vertical distributions on the adjacency effect was evaluated by calculating the single-scattering light intensity which, after the reflection at the ground surface, reaches the satellite sensor via a single scattering with a molecule or an aerosol particle.
Abstract: In the atmospheric correction of satellite data in the visible and near-infrared bands, it is necessary to remove the adjacency effect due to the reflection from contiguous pixels. Evaluation of the influence of aerosol vertical distributions on the adjacency effect is done by calculating the single-scattering light intensity which, after the reflection at the ground surface, reaches the satellite sensor via a single scattering with a molecule or an aerosol particle. In the simulation, we assume aerosol vertical profiles similar to those used in the MODTRAN radiation transfer code, and those having a mixed layer with a uniform value of the aerosol extinction coefficient. We assume for the ground surface a simple model representing a border of land/sea surfaces. In spite of the single scattering approximation, it is confirmed that even if the optical thickness is the same, we have a larger adjacency effect when the extinction coefficient is large at higher altitudes. We also discuss the dependence of the adjacency effect on the aerosol optical thickness and that on the difference in the reflectances of the land and sea surfaces along the border.

32 citations

Journal ArticleDOI
TL;DR: The concept of energy of fuzzy graph is extended to the energy of a vague graph, which has many applications in physics, chemistry, computer science, and other branches of mathematics.
Abstract: The concept of vague graph was introduced by Ramakrishna (Int J Comput Cognit 7:51–58, 2009). Since the vague models give more precision, flexibility, and compatibility to the system as compared to the classical and fuzzy models, in this paper, the concept of energy of fuzzy graph is extended to the energy of a vague graph. It has many applications in physics, chemistry, computer science, and other branches of mathematics. We define adjacency matrix, degree matrix, laplacian matrix, spectrum, and energy of a vague graph in terms of their adjacency matrix. The spectrum of a vague graph appears in physics statistical problems, and combinatorial optimization problems in mathematics. Also, the lower and upper bounds for the energy of a vague graph are also derived. Finally, we give some applications of energy in vague graph and other sciences.

32 citations

Proceedings ArticleDOI
Chunyang Wang1, Yanmin Zhu1, Tianzi Zang1, Haobing Liu1, Jiadi Yu1 
08 Mar 2021
TL;DR: Zhang et al. as discussed by the authors proposed an attentive temporal graph convolutional network (ATGCN) to model diverse inter-station relationships for air quality prediction of citywide stations, which encoded three types of relationships among stations including spatial adjacency, functional similarity, and temporal pattern similarity into graphs.
Abstract: Air pollution is an important environmental issue of increasing concern, which impacts human health. Accurate air quality prediction is crucial for avoiding people suffering from serious air pollution. Most of the prior works focus on capturing the temporal trend of air quality for each monitoring station. Recent deep learning based methods also model spatial dependencies among neighboring stations. However, we observe that besides geospatially adjacent stations, the stations which share similar functionalities or consistent temporal patterns could also have strong dependencies. In this paper, we propose an Attentive Temporal Graph Convolutional Network (ATGCN) to model diverse inter-station relationships for air quality prediction of citywide stations. Specifically, we first encode three types of relationships among stations including spatial adjacency, functional similarity, and temporal pattern similarity into graphs. Then we design parallel encoding modules, which respectively incorporate attentive graph convolution operations into the Gated Recurrent Units (GRUs) to iteratively aggregate features from related stations with different graphs. Furthermore, augmented with an attention-based fusion unit, decoding modules with a similar structure to the encoding modules are designed to generate multi-step predictions for all stations. The experiments on two real-world datasets demonstrate the superior performance of our model beyond state-of-the-art methods.

32 citations

Proceedings ArticleDOI
01 Jan 2008
TL;DR: A new algorithm is proposed that uses the maximum spanning tree of a graph defining potential connectivity and adjacency in recorded stripes to solve the problem of relating projected and recorded stripes.
Abstract: Structured light is a well-known technique for capturing 3D surface measurements but has yet to achieve satisfactory results for applications demanding high resolution models at frame rate. For these requirements a dense set of uniform uncoded white stripes seems attractive. But the problem of relating projected and recorded stripes, here called the Indexing Problem, has proved to be difficult to overcome reliably for uncoded patterns. We propose a new algorithm that uses the maximum spanning tree of a graph defining potential connectivity and adjacency in recorded stripes. Results are significantly more accurate and reliable than previous attempts. We do however also identify an important limitation of uncoded patterns and claim that, in general, additional stripe coding is necessary. Our algorithm adapts easily to accommodate a minimal coding scheme that increases neither sample size nor acquisition time.

32 citations

Journal ArticleDOI
TL;DR: Almost all finite graphs have the $n$-e.c. c.\ adjacency property, although until recently few explicit examples of such graphs were known.
Abstract: Almost all finite graphs have the $n$-e.c.\ adjacency property, although until recently few explicit examples of such graphs were known. We survey some recently discovered families of explicit finite $n$-e.c.\ graphs, and present a new construction of strongly regular $n$-e.c.\ arising from affine planes.

31 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023209
2022439
2021283
2020280
2019296
2018232