scholarly journals Efficient n-to-n Collision Detection for Space Debris using 4D AABB Trees

10.29007/5pl1 ◽  
2019 ◽  
Author(s):  
Stanley Bak ◽  
Kerianne Hobbs
Keyword(s):  
Collision Detection ◽  
Space Debris ◽  
Dynamics Simulation ◽  
Video Gaming ◽  
Time Dimension ◽  
Detection Algorithms ◽  
Space Objects ◽  
Tree Data ◽  
Tree Data Structure ◽  
Three Space

Collision detection algorithms are used in aerospace, swarm robotics, automotive, video gaming, dynamics simulation and other domains. As many applications of collision detection run online, timing requirements are imposed on the algorithm runtime: algorithms must, at a minimum, keep up with the passage of time. Even offline reachability computation can be slowed down by the process of safety checking when n is large and the specification is n-to-n collision avoidance. In practice, this places a limit on the number of objects, n, that can be concurrently tracked or verified. In this paper, we present an improved method for efficient object tracking and collision detection, based on a modified version of the axis-aligned bounding-box (AABB) tree data structure. We consider 4D AABB Trees, where a time dimension is added to the usual three space dimensions, in order to enable per-object time steps when checking for collisions in space-time. We evaluate the approach on a space debris collision benchmark, demonstrating efficient checking beyond the full catalog of n = 16848 space objects made public by the U.S. Strategic Command on www.space-track.org.

Molecular Dynamics Simulation of Nanodroplet Evaporation

2000 ◽  
Vol 123 (4) ◽  
pp. 741-748 ◽  
Author(s):  
J. H. Walther ◽  
P. Koumoutsakos
Keyword(s):  
Molecular Dynamics ◽  
Heat Conduction ◽  
Data Structure ◽  
Dynamics Simulation ◽  
Evaporation Coefficient ◽  
Theoretical Predictions ◽  
Tree Data ◽  
Convergence Study ◽  
Dynamics Simulations ◽  
Tree Data Structure

Molecular dynamics simulations are used to study the sub-critical evaporation of a nanometer-size droplet at 300 K and 3 MPa. Classical molecular dynamics techniques are combined with an adaptive tree data structure for the construction of the neighbor lists, allowing efficient simulations using hundreds of thousands of molecules. We present a systematic convergence study of the method demonstrating its convergence for heat conduction problems in submicron scales. These high resolution simulations compute values of the evaporation coefficient that are in excellent agreement with theoretical predictions.

Logical Structure for User Friendly dynamic Web Page Visualization for Small Screen Terminals Promoting E-Business

2020 ◽  
Vol 14 ◽  
Author(s):  
Shefali Singhal ◽  
Poonam Tanwar
Keyword(s):  
Logical Structure ◽  
Vital Role ◽  
Web Pages ◽  
Main Concern ◽  
Web Page ◽  
Large Screen ◽  
Tree Data ◽  
Tree Data Structure ◽  
User Friendly ◽  
Small Screen

Abstract:: Now-a-days when everything is going digitalized, internet and web plays a vital role in everyone’s life. When one has to ask something or has any online task to perform, one has to use internet to access relevant web-pages throughout. These web-pages are mainly designed for large screen terminals. But due to mobility, handy and economic reasons most of the persons are using small screen terminals (SST) like mobile phone, palmtop, pagers, tablet computers and many more. Reading a web page which is actually designed for large screen terminal on a small screen is time consuming and cumbersome task because there are many irrelevant content parts which are to be scrolled or there are advertisements, etc. Here main concern is e-business users. To overcome such issues the source code of a web page is organized in tree data-structure. In this paper we are arranging each and every main heading as a root node and all the content of this heading as a child node of the logical structure. Using this structure, we regenerate a web-page automatically according to SST size. Background:: DOM and VIPS algorithms are the main background techniques which are supporting the current research. Objective:: To restructure a web page in a more user friendly and content presenting format. Method Backtracking:: Method Backtracking: Results:: web page heading queue generation. Conclusion:: Concept of logical structure supports every SST.

scholarly journals The Ad Hoc Back-End of the BIRALET Radar to Measure Slant-Range and Doppler Shift of Resident Space Objects

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 577
Author(s):  
Luca Schirru ◽  
Tonino Pisanu ◽  
Angelo Podda
Keyword(s):  
Doppler Shift ◽  
Space Debris ◽  
Ad Hoc ◽  
Low Earth Orbit ◽  
Slant Range ◽  
Radar Systems ◽  
The Earth ◽  
Space Objects ◽  
Resident Space Objects ◽  
Potential Issue

Space debris is a term for all human-made objects orbiting the Earth or reentering the atmosphere. The population of space debris is continuously growing and it represents a potential issue for active satellites and spacecraft. New collisions and fragmentation could exponentially increase the amount of debris and so the level of risk represented by these objects. The principal technique used for the debris monitoring, in the Low Earth Orbit (LEO) between 200 km and 2000 km of altitude, is based on radar systems. The BIRALET system represents one of the main Italian radars involved in resident space objects observations. It is a bi-static radar, which operates in the P-band at 410–415 MHz, that uses the Sardinia Radio Telescope as receiver. In this paper, a detailed description of the new ad hoc back-end developed for the BIRALET radar, with the aim to perform slant-range and Doppler shift measurements, is presented. The new system was successfully tested in several validation measurement campaigns, the results of which are reported and discussed.

TABU PROGRAMMING: A NEW PROBLEM SOLVER THROUGH ADAPTIVE MEMORY PROGRAMMING OVER TREE DATA STRUCTURES

2011 ◽  
Vol 10 (02) ◽  
pp. 373-406 ◽  
Author(s):  
ABDEL-RAHMAN HEDAR ◽  
EMAD MABROUK ◽  
MASAO FUKUSHIMA
Keyword(s):  
Search Algorithm ◽  
Benchmark Problems ◽  
Problem Solver ◽  
Learning Tools ◽  
Mutation Operators ◽  
Tree Data ◽  
Tree Data Structure ◽  
Comprehensive Framework ◽  
Rate Of Success ◽  
Crossover And Mutation

Since the first appearance of the Genetic Programming (GP) algorithm, extensive theoretical and application studies on it have been conducted. Nowadays, the GP algorithm is considered one of the most important tools in Artificial Intelligence (AI). Nevertheless, several questions have been raised about the complexity of the GP algorithm and the disruption effect of the crossover and mutation operators. In this paper, the Tabu Programming (TP) algorithm is proposed to employ the search strategy of the classical Tabu Search algorithm with the tree data structure. Moreover, the TP algorithm exploits a set of local search procedures over a tree space in order to mitigate the drawbacks of the crossover and mutation operators. Extensive numerical experiments are performed to study the performance of the proposed algorithm for a set of benchmark problems. The results of those experiments show that the TP algorithm compares favorably to recent versions of the GP algorithm in terms of computational efforts and the rate of success. Finally, we present a comprehensive framework called Meta-Heuristics Programming (MHP) as general machine learning tools.

A Scalable Algorithm for Constructing Frequent Pattern Tree

2014 ◽  
Vol 10 (1) ◽  
pp. 42-56 ◽  
Author(s):  
Zailani Abdullah ◽  
Tutut Herawan ◽  
A. Noraziah ◽  
Mustafa Mat Deris
Keyword(s):  
Data Structure ◽  
Frequent Pattern ◽  
Frequent Patterns ◽  
Scalable Algorithm ◽  
Tree Construction ◽  
Frequent Pattern Tree ◽  
Support Threshold ◽  
Benchmark Datasets ◽  
Tree Data ◽  
Tree Data Structure

Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. In typical FP-Tree construction, besides the prior knowledge on support threshold, it also requires two database scans; first to build and sort the frequent patterns and second to build its prefix paths. Thus, twice database scanning is a key and major limitation in completing the construction of FP-Tree. Therefore, this paper suggests scalable Trie Transformation Technique Algorithm (T3A) to convert our predefined tree data structure, Disorder Support Trie Itemset (DOSTrieIT) into FP-Tree. Experiment results through two UCI benchmark datasets show that the proposed T3A generates FP-Tree up to 3 magnitudes faster than that the benchmarked FP-Growth.

scholarly journals Pengenalan Motif Karawo Menggunakan Ekstraksi Fitur SIFT Dan Approximate Nearest Neighbor

2019 ◽  
Author(s):  
Syahrial
Keyword(s):  
Nearest Neighbor ◽  
Feature Matching ◽  
Recognition Accuracy ◽  
Sift Algorithm ◽  
Approximate Nearest Neighbor ◽  
Single Pattern ◽  
Tree Data ◽  
Threshold Testing ◽  
Root Word ◽  
Tree Data Structure

An art culture from Gorontalo became iconic handcraft is kerawang or karawo. The word “karawo” came from root word of “mokarawo” which means slicing or making holes. It’s created with precision, carefulness, and patience in work using handmade masterpiece. Pattern of karawo itself held four kinds which is flora, fauna, geometric, and nature. From those kinds born vary pattern which come difficult to identify both its names and its kind. Karawo patterns can be form as a single pattern or a pattern that it parts came from several or many pattern combined. Those patterns had its own characteristic from shape and scale perspective. Identifying single pattern on combined pattern are particularly a problem because it’s combined involve scaling and rotation. This research is recognizing single pattern on combined pattern using feature extraction SIFT algorithm which is capable extract feature that invariant from scale and rotation. Feature matching using approximate nearest neighbor (aNN) for similarity of features labor best bin first strategy on kd-tree data structure. Those methods can be a reference to recognize single pattern on combined pattern using from range 5 to 20 match features as a threshold. Testing result indicated recognition accuracy is good which range form 76.36% to 85.45% on recognize the kind of karawo pattern and 76.36% on its name.

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