scholarly journals A Large-scale Benchmark and an Inclusion-based Algorithm for Continuous Collision Detection

2021 ◽  
Vol 40 (5) ◽  
pp. 1-16
Author(s):  
Bolun Wang ◽  
Zachary Ferguson ◽  
Teseo Schneider ◽  
Xin Jiang ◽  
Marco Attene ◽  
...  
Keyword(s):  
Collision Detection ◽  
Large Scale ◽  
State Of The Art ◽  
False Positives ◽  
False Negatives ◽  
Detection Algorithms ◽  
Root Finding ◽  
Continuous Collision Detection ◽  
Degenerate Cases ◽  
Design Techniques

We introduce a large-scale benchmark for continuous collision detection (CCD) algorithms, composed of queries manually constructed to highlight challenging degenerate cases and automatically generated using existing simulators to cover common cases. We use the benchmark to evaluate the accuracy, correctness, and efficiency of state-of-the-art continuous collision detection algorithms, both with and without minimal separation. We discover that, despite the widespread use of CCD algorithms, existing algorithms are (1) correct but impractically slow; (2) efficient but incorrect, introducing false negatives that will lead to interpenetration; or (3) correct but over conservative, reporting a large number of false positives that might lead to inaccuracies when integrated in a simulator. By combining the seminal interval root finding algorithm introduced by Snyder in 1992 with modern predicate design techniques, we propose a simple and efficient CCD algorithm. This algorithm is competitive with state-of-the-art methods in terms of runtime while conservatively reporting the time of impact and allowing explicit tradeoff between runtime efficiency and number of false positives reported.

scholarly journals Systematic Review and Quantitative Comparison of Cyberattack Scenario Detection and Projection

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1722
Author(s):  
Ivan Kovačević ◽  
Stjepan Groš ◽  
Karlo Slovenec
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Knowledge Bases ◽  
Intrusion Detection Systems ◽  
False Negatives ◽  
Detection Systems ◽  
Malicious Activity ◽  
Event Logs ◽  
Manual Analysis

Intrusion Detection Systems (IDSs) automatically analyze event logs and network traffic in order to detect malicious activity and policy violations. Because IDSs have a large number of false positives and false negatives and the technical nature of their alerts requires a lot of manual analysis, the researchers proposed approaches that automate the analysis of alerts to detect large-scale attacks and predict the attacker’s next steps. Unfortunately, many such approaches use unique datasets and success metrics, making comparison difficult. This survey provides an overview of the state of the art in detecting and projecting cyberattack scenarios, with a focus on evaluation and the corresponding metrics. Representative papers are collected while using Google Scholar and Scopus searches. Mutually comparable success metrics are calculated and several comparison tables are provided. Our results show that commonly used metrics are saturated on popular datasets and cannot assess the practical usability of the approaches. In addition, approaches with knowledge bases require constant maintenance, while data mining and ML approaches depend on the quality of available datasets, which, at the time of writing, are not representative enough to provide general knowledge regarding attack scenarios, so more emphasis needs to be placed on researching the behavior of attackers.

Collision Detection between Rigid Bodies Based on Adaptive Test Lines

2013 ◽  
Vol 756-759 ◽  
pp. 3189-3193
Author(s):  
Xiao Dong Shao ◽  
Wei Gao ◽  
Huan Lling Liu
Keyword(s):  
Collision Detection ◽  
Detection Efficiency ◽  
Rigid Bodies ◽  
Collision Point ◽  
Detection Algorithms ◽  
Adaptive Test ◽  
Rigid Objects ◽  
Continuous Collision Detection ◽  
Volume Algorithm ◽  
Swept Volume

A novel algorithm, which can check the collision point of rigid objects continuously and solve the problem of penetration and crossing in collision detection effectively, is presented in this paper. At each simulation moment, the adaptive test lines (ATLs) are first constructed based on the velocity vector of the moving object and then the intersection between the ATLs and the environment is calculated. The collision happens when the intersection is not empty and the collision point is obtained through crossing-frame processing. By checking the interference between body and ATLs instead of bodies, we greatly improve the detection efficiency. It avoids missing collisions for an object with arbitrary shape or in any motion states. Simulation results show that our algorithm runs faster than the general continuous collision detection algorithms and has similar detection effects to the swept volume algorithm.

Collision Detection Using the GJK Algorithm

2012 ◽  
pp. 253-288 ◽  
Author(s):  
William N. Bittle
Keyword(s):  
Collision Detection ◽  
Detection Algorithm ◽  
Ray Casting ◽  
Detection Algorithms ◽  
Continuous Collision Detection

GJK is a fast and elegant collision detection algorithm. Originally designed to determine the distance between two convex shapes, it has been adapted to collision detection, continuous collision detection, and ray casting. Its versatility, speed, and compactness have allowed GJK to be one of the top choices of collision detection algorithms in a number of fields.

scholarly journals MapReduce Based Personalized Locality Sensitive Hashing for Similarity Joins on Large Scale Data

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Jingjing Wang ◽  
Chen Lin
Keyword(s):  
Large Scale ◽  
False Negative ◽  
Experimental Studies ◽  
Simulated Data ◽  
False Positives ◽  
Locality Sensitive Hashing ◽  
False Negatives ◽  
Large Scale Data ◽  
Similarity Joins ◽  
Scale Data

Locality Sensitive Hashing (LSH) has been proposed as an efficient technique for similarity joins for high dimensional data. The efficiency and approximation rate of LSH depend on the number of generated false positive instances and false negative instances. In many domains, reducing the number of false positives is crucial. Furthermore, in some application scenarios, balancing false positives and false negatives is favored. To address these problems, in this paper we propose Personalized Locality Sensitive Hashing (PLSH), where a new banding scheme is embedded to tailor the number of false positives, false negatives, and the sum of both. PLSH is implemented in parallel using MapReduce framework to deal with similarity joins on large scale data. Experimental studies on real and simulated data verify the efficiency and effectiveness of our proposed PLSH technique, compared with state-of-the-art methods.

Sky Segmentation for Enhanced Depth Reconstruction and Bokeh Rendering with Efficient Architectures

2020 ◽  
Vol 2020 (14) ◽  
pp. 378-1-378-7
Author(s):  
Tyler Nuanes ◽  
Matt Elsey ◽  
Radek Grzeszczuk ◽  
John Paul Shen
Keyword(s):  
Real Time ◽  
Mobile Device ◽  
Computational Cost ◽  
False Positives ◽  
Compact Model ◽  
High Quality ◽  
False Negatives ◽  
Trade Off ◽  
Depth Reconstruction ◽  
Binary Classifiers

We present a high-quality sky segmentation model for depth refinement and investigate residual architecture performance to inform optimally shrinking the network. We describe a model that runs in near real-time on mobile device, present a new, highquality dataset, and detail a unique weighing to trade off false positives and false negatives in binary classifiers. We show how the optimizations improve bokeh rendering by correcting stereo depth misprediction in sky regions. We detail techniques used to preserve edges, reject false positives, and ensure generalization to the diversity of sky scenes. Finally, we present a compact model and compare performance of four popular residual architectures (ShuffleNet, MobileNetV2, Resnet-101, and Resnet-34-like) at constant computational cost.

Automatic Extraction of Acronyms from Text

2020 ◽  
Author(s):  
Stuart Yeates
Keyword(s):  
Digital Library ◽  
False Positives ◽  
Automatic Extraction ◽  
False Negatives ◽  
Library Research ◽  
Communications Theory ◽  
Textual Content

A brief introduction to acronyms is given and motivation for extracting them in a digital library environment is discussed. A technique for extracting acronyms is given with an analysis of the results. The technique is found to have a low number of false negatives and a high number of false positives. Introduction Digital library research seeks to build tools to enable access of content, while making as few as possible assumptions about the content, since assumptions limit the range of applicability of the tools. Generally, the broader the assumptions the more widely applicable the tools. For example, keyword based indexing [5] is based on communications theory and applies to all natural human textual languages (allowances for differences in character sets and similar localisation issues not withstanding) . The algorithm described in this paper makes much stronger assumptions about the content. It assumes textual content that contains acronyms, an assumption which is known to hold for...

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

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