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Smoke is a useful method to visualize flows from scientific experiments or physical simulations in many applications of science, engineering, graphics, and virtual reality. In visualizing flows, smoke evolution inside a flow field...
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Smoke is a useful method to visualize flows from scientific experiments or physical simulations in many applications of science, engineering, graphics, and virtual reality. In visualizing flows, smoke evolution inside a flow field creates 3D, high-resolution, and time-varying data sets. The large data size imposes challenge on storing and transmitting the smoke animation results where good compression techniques are demanded. Furthermore, small-scale smoke details play important roles in visualizing and conveying realistic flow behavior. They should be well preserved in compression and reconstructed to create smooth animation effect in decompression. This requirement impairs the direct adaptation of existing techniques in video and volume compression. In this paper, we design new techniques to enable effective smoke visualization compression with smooth detail preservation. The motion estimation between key frames of density fields is implemented by a special bidirectional advection. The intermediate frames are built from advected key frames with specific blending. The advection is driven by motion vectors over nonuniform blocks, which are created with an adaptive simplification of velocity field to reflect the heterogeneous velocity variations. Moreover, pertinent intra-frame compression techniques are integrated. Our approach eventually achieves good compression performance and quality with easy control.
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Nowadays, efficient and effective stream processing has become increasingly important in many real-world applications such as sensor data monitoring, network intrusion detection, IP network traffic analysis, and so on. In practice...
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Nowadays, efficient and effective stream processing has become increasingly important in many real-world applications such as sensor data monitoring, network intrusion detection, IP network traffic analysis, and so on. In practice, stream data often encounter the problem of having some data attributes missing, due to reasons such as packet losses, network congestion/failure, and so on. In such a scenario, it is rather important, yet challenging, to accurately and efficiently monitor top-k objects over incomplete data stream, which may potentially indicate some dangerous and critical security events (e.g., fire, network intrusion, or denial-of-service attack). In this paper, we formally define the problem of top-k query over incomplete data stream (Topk-iDS), which continuously detects top-k objects with the highest ranking scores over an incomplete data stream. Due to unique characteristics such as incompleteness and stream processing, we propose a cost-model-based data imputation approach, design effective pruning strategies to reduce the Topk-iDS search space, and carefully devise dynamically updated data synopses to facilitate Topk-iDS query processing. We also propose an efficient algorithm to perform the data imputation and incremental Topk-iDS computation at the same time. Finally, through extensive experiments, we evaluate the efficiency and effectiveness of our proposed Topk-iDS query answering approach over both real and synthetic data sets.. (C) 2020 Elsevier Inc. All rights reserved.
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We consider the distributed setting of N autonomous mobile robots that operate in Look-Compute-Move (LCM) cycles and communicate with other robots using colored lights following the robots with lights model. We assume obstructed v...
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We consider the distributed setting of N autonomous mobile robots that operate in Look-Compute-Move (LCM) cycles and communicate with other robots using colored lights following the robots with lights model. We assume obstructed visibility under which a robot cannot see another robot if a third robot is positioned between them on the straight line connecting them. We study the fundamental COMPLETE VISIBILITY problem of repositioning N robots, starting from N distinct points, on a plane so that each robot is visible to all others. We are interested in fault-tolerant algorithms. We study fault-tolerance with respect to failures on the mobility of robots. Therefore, any algorithm for COMPLETE VISIBILITY is required to provide visibility between all non-faulty robots (i.e., no three non-faulty robots are collinear and no faulty robot is between two non-faulty robots on the straight line connecting them), independently of the behavior of the faulty ones. We model mobility failures as crash faults in which each faulty robot may stop its movement at any time and, once it stopped moving, it will remain stationary indefinitely thereafter. There exists an algorithm for this problem that tolerates a single faulty robot in the semi-synchronous setting under both-axis agreement. In that algorithm, the light of the faulty robot does not need to work correctly after the robot experiences fault. In this article, we assume the model in which, even after a robot experiences fault, its light still operates correctly and provide the first algorithm for COMPLETE VISIBILITY that tolerates f 收起
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A set of restructurings to systematically normalize selective syntax in C++ is presented. The objective is to convert variations in syntax of specific portions of code into a single form to simplify the construction of large, comp...
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A set of restructurings to systematically normalize selective syntax in C++ is presented. The objective is to convert variations in syntax of specific portions of code into a single form to simplify the construction of large, complex program transformation rules. Current approaches to constructing transformations require developers to account for a large number of syntactic cases, many of which are syntactically different but semantically equivalent. The work identifies classes of such syntactic variations and presents normalizing restructurings to simplify each variation to a single, consistent syntactic form. The normalizing restructurings for C++ are presented and applied to two open source systems for evaluation. The evaluation uses the system's test cases to validate that the normalizing restructurings do not affect the systems' tested behavior. In addition, a set of example transformations that benefit from the prior application of normalizing restructurings are presented along with a small survey to assess the effect of the readability of the resultant code.
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This study focuses on VR as a form of therapy for individuals with intellectual and developmental disabilities (IDDs). The research aim is to develop an immersive and interactive VR system that is tailored for IDD individuals, for...
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This study focuses on VR as a form of therapy for individuals with intellectual and developmental disabilities (IDDs). The research aim is to develop an immersive and interactive VR system that is tailored for IDD individuals, for which most currently available VR experience systems are not optimized. Being intimately familiar with a place through an interactive VR tour will help alleviate social anxiety-very provident to IDD individuals. Accordingly, we create a hotspot-based VR tour system, which can provide an almost lifelike experience of visiting and learning about the location. We have conducted experiments with nondisabled individuals, acting as the control group, and IDD individuals, acting as the experimental group, to evaluate the tour system and compare the results between two groups. Our experiments show that the VR tour has a positive impact on the IDD individuals. In this article, we present the design of our VR tour system and its evaluation results.
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The delta-hyperbolicity of a graph is defined by a simple 4-point condition: for any four vertices u, v, w, and x, the two larger of the distance sums d(u, v) + d(w, x), d(u, w) + d(v, x), and d(u, x) + d(v, w) differ by at most 2...
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The delta-hyperbolicity of a graph is defined by a simple 4-point condition: for any four vertices u, v, w, and x, the two larger of the distance sums d(u, v) + d(w, x), d(u, w) + d(v, x), and d(u, x) + d(v, w) differ by at most 2 delta >= 0. Hyperbolicity can be viewed as a measure of how close a graph is to a tree metrically; the smaller the hyperbolicity of a graph, the closer it is metrically to a tree. A graph G is Helly if its disks satisfy the Helly property, i.e., every family of pairwise intersecting disks in G has a common intersection. It is known that for every graph G there exists the smallest Helly graph H(G) into which G isometrically embeds (H(G) is called the injective hull of H(G) and the hyperbolicity of H(G) is equal to the hyperbolicity of G. Motivated by this, we investigate structural properties of Helly graphs that govern their hyperbolicity and identify three isometric subgraphs of the King-grid as structural obstructions to a small hyperbolicity in Helly graphs. (C) 2018 Elsevier B.V. All rights reserved.
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In this paper, we introduce and investigate the Minimum Eccentricity Shortest Path (MESP) problem in unweighted graphs. It asks for a given graph to find a shortest path with minimum eccentricity. Let n and m denote the number of ...
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In this paper, we introduce and investigate the Minimum Eccentricity Shortest Path (MESP) problem in unweighted graphs. It asks for a given graph to find a shortest path with minimum eccentricity. Let n and m denote the number of vertices and the number of edges of a given graph. We demonstrate that:
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Delay- and Disruption-Tolerant Networks (DTNs) refer to a range of networks with link intermittency that is mainly driven by mobility, predictable or unpredictable network environmental conditions. Examples of DTNs include interpl...
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Delay- and Disruption-Tolerant Networks (DTNs) refer to a range of networks with link intermittency that is mainly driven by mobility, predictable or unpredictable network environmental conditions. Examples of DTNs include interplanetary networks, battlefield networks, smart highways, remote sensing, and animal-movement outposts. There exist a number of mobility models describing the operation of various DTNs. One common characteristic that all mobility models share is the distribution of contact time and inter-contact time between nodes. Predicting an end-to-end delay in networks with disruptive links is more complicated than predicting the delay in connected networks. Disruptive patterns and underlying routing algorithms play a major role in an end-to-end delay modeling. In this article, we introduce a new model that can be used to estimate the end-to-end delay in networks with intermittent links. The model incorporates the two non-deterministic delay distributions, namely link intermittency and tandem queuing delay distributions. The model is based on an open queuing system with exponentially distributed link intermittency. The model gives a close approximation of the average end-to-end delay and the delay variance in closed forms. Simulation results on various networks and under different traffic conditions confirm the accuracy of the model within the conventional bounds of statistical significance.
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In modern cities, service providers want to identify the regions that are hard to reach from multiple fire stations, a citizen wants to meet with friends in a restaurant close to everyone, and administrators want to find whether a...
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In modern cities, service providers want to identify the regions that are hard to reach from multiple fire stations, a citizen wants to meet with friends in a restaurant close to everyone, and administrators want to find whether an area far from two bus stations needs a new one. Such tasks involve studying the dynamic accessibility of the urban structures over multiple geospatial and temporal constraints, which is an important topic in geographical sciences and urban transportation. In this paper, we present a new computational model and a visualization system that help domain users to interactively study the jointly constrained accessible regions, street segments, and Points of Interest (POIs). In particular, Urban Structure Accessibility Visualization system is built upon a new Min-Max Joint Set model, where specifically designed set operations not only represent the accessible regions but also compute the minimum and maximum access times to urban structures from the joint constraints. The computation and visualization are supported by a new graph model that accommodates the real-world dynamic traffic situation and the geographical settings of urban street segments and POIs. The visualization system allows the users to conveniently construct and manage accessible regions and visually explore the urban structures inside them.
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Nowadays, efficient and effective processing over massive stream data has attracted much attention from the database community, which are useful in many real applications such as sensor data monitoring, network intrusion detection...
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Nowadays, efficient and effective processing over massive stream data has attracted much attention from the database community, which are useful in many real applications such as sensor data monitoring, network intrusion detection, and so on. In practice, due to the malfunction of sensing devices or imperfect data collection techniques, real-world stream data may often contain missing or incomplete data attributes. In this paper, we will formalize and tackle a novel and important problem, named skyline query over incomplete data stream (Sky-iDS), which retrieves skyline objects (in the presence of missing attributes) with high confidences from incomplete data stream. In order to tackle the Sky-iDS problem, we will design efficient approaches to impute missing attributes of objects from incomplete data stream via differential dependency (DD) rules. We will propose effective pruning strategies to reduce the search space of the Sky-iDS problem, devise cost-model-based index structures to facilitate the data imputation and skyline computation at the same time, and integrate our proposed techniques into an efficient Sky-iDS query answering algorithm. Extensive experiments have been conducted to confirm the efficiency and effectiveness of our Sky-iDS processing approach over both real and synthetic data sets.
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