Efficient computation of map algebra over raster data stored in the k2-acc compact data structure

2021 ◽  
Author(s):  
Mónica Caniupán ◽  
Rodrigo Torres-Avilés ◽  
Tatiana Gutiérrez-Bunster ◽  
Manuel Lepe
Keyword(s):  
Data Structure ◽  
Efficient Computation ◽  
Map Algebra ◽  
Raster Data

scholarly journals A Head/Tail Breaks-Based Method for Efficiently Estimating the Absolute Boltzmann Entropy of Numerical Raster Data

2020 ◽  
Vol 9 (2) ◽  
pp. 103 ◽  
Author(s):  
Hong Zhang ◽  
Zhiwei Wu
Keyword(s):  
Shannon Entropy ◽  
Spatial Data ◽  
Computation Time ◽  
Original Method ◽  
Efficient Computation ◽  
Boltzmann Entropy ◽  
Raster Data ◽  
Digital Elevation ◽  
The Absolute ◽  
Heavy Tailed

Shannon entropy is the most popular method for quantifying information in a system. However, Shannon entropy is considered incapable of quantifying spatial data, such as raster data, hence it has not been applied to such datasets. Recently, a method for calculating the Boltzmann entropy of numerical raster data was proposed, but it is not efficient as it involves a series of numerical processes. We aimed to improve the computational efficiency of this method by borrowing the idea of head and tail breaks. This paper relaxed the condition of head and tail breaks and classified data with a heavy-tailed distribution. The average of the data values in a given class was regarded as its representative value, and this was substituted into a linear function to obtain the full expression of the relationship between classification level and Boltzmann entropy. The function was used to estimate the absolute Boltzmann entropy of the data. Our experimental results show that the proposed method is both practical and efficient; computation time was reduced to about 1% of the original method when dealing with eight 600 × 600 pixel digital elevation models.

Efficient computation of the convex hull on sets of points stored in a k-tree compact data structure

2020 ◽  
Vol 62 (10) ◽  
pp. 4091-4111
Author(s):  
Juan Felipe Castro ◽  
Miguel Romero ◽  
Gilberto Gutiérrez ◽  
Mónica Caniupán ◽  
Carlos Quijada-Fuentes
Keyword(s):  
Data Structure ◽  
Convex Hull ◽  
Efficient Computation

Distributed Modeling Of Building Systems Through Cyber-Physical Integration

2019 ◽  
pp. 12-17
Keyword(s):  
Data Structure ◽  
Operating Conditions ◽  
Physical Models ◽  
Distributed Model ◽  
Physical Processes ◽  
Distributed Modeling ◽  
Distributed Models ◽  
Operating Modes ◽  
Building Systems ◽  
Important Practical Application

This article describes the proposed approaches to creating distributed models that can, with given accuracy under given restrictions, replace classical physical models for construction objects. The ability to implement the proposed approaches is a consequence of the cyber-physical integration of building systems. The principles of forming the data structure of designed objects and distributed models, which make it possible to uniquely identify the elements and increase the level of detail of such a model, are presented. The data structure diagram of distributed modeling includes, among other things, the level of formation and transmission of signals about physical processes inside cyber-physical building systems. An enlarged algorithm for creating the structure of the distributed model which describes the process of developing a data structure, formalizing requirements for the parameters of a design object and its operating modes (including normal operating conditions and extreme conditions, including natural disasters) and selecting objects for a complete group that provides distributed modeling is presented. The article formulates the main approaches to the implementation of an important practical application of the cyber-physical integration of building systems - the possibility of forming distributed physical models of designed construction objects and the directions of further research are outlined.

No fear of George Kingsley Zipf

10.1558/37291 ◽  
2018 ◽  
Vol 2 (2) ◽  
pp. 242-263
Author(s):  
Stefano Rastelli ◽  
Kook-Hee Gil
Keyword(s):  
Minimalist Program ◽  
Classroom Research ◽  
Language Design ◽  
Efficient Computation ◽  
Generative Linguistics ◽  
The Third ◽  
Factor Effect ◽  
Language Classroom ◽  
Recent Developments ◽  
Insight Into

This paper offers a new insight into GenSLA classroom research in light of recent developments in the Minimalist Program (MP). Recent research in GenSLA has shown how generative linguistics and acquisition studies can inform the language classroom, mostly focusing on what linguistic aspects of target properties should be integrated as a part of the classroom input. Based on insights from Chomsky’s ‘three factors for language design’ – which bring together the Faculty of Language, input and general principles of economy and efficient computation (the third factor effect) for language development – we put forward a theoretical rationale for how classroom research can offer a unique environment to test the learnability in L2 through the statistical enhancement of the input to which learners are exposed.

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