By means of the limit and jump relations of classical potential theory with respect to the Helmholtz equation a wavelet approach is established on a regular surface. The multiscale procedure is constructed in such a w...
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By means of the limit and jump relations of classical potential theory with respect to the Helmholtz equation a wavelet approach is established on a regular surface. The multiscale procedure is constructed in such a way that the emerging potential kernels act as scaling functions, wavelets are defined via a canonical refinement equation. A tree algorithm for fast computation of a function discretely given on a regular surface is developed based on numerical integration rules. By virtue of the tree algorithm, an efficient numerical method for the solution of Fredholm integral equations involving boundary-value problems of the Helmholtz equation corresponding to (general) regular (boundary) surfaces is discussed in more detail.
Recently, tree algorithms have been combined with successive interference cancellation to achieve a substantially higher maximum stable throughput (MST). All previous work assumed either a single or an unbounded numbe...
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Recently, tree algorithms have been combined with successive interference cancellation to achieve a substantially higher maximum stable throughput (MST). All previous work assumed either a single or an unbounded number of signal memory locations, with MSTs of 0.662 and 0.693, respectively. In this paper, we address the gap between these two algorithms by designing and analyzing two novel general k-signal memory location algorithms.
This paper presents a branching process approach to determine the main performance measures of a variety of conflict resolution algorithms known as tree algorithms with free access. In particular we present an efficie...
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This paper presents a branching process approach to determine the main performance measures of a variety of conflict resolution algorithms known as tree algorithms with free access. In particular we present an efficient approach to calculate the mean delay, number of transmission attempts, collision resolution interval length and energy usage with arbitrary precision. (C) 2013 Elsevier B.V. All rights reserved.
The empirical performance of the algorithms of Kruskal, Prim, and Sollin for determining a minimum spanning tree is examined and found to be considerably better than suggested by worst case analysis. Kruskal's alg...
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The empirical performance of the algorithms of Kruskal, Prim, and Sollin for determining a minimum spanning tree is examined and found to be considerably better than suggested by worst case analysis. Kruskal's algorithm is generally slowest, with the Prim algorithm being preferred for dense networks and the Sollin algorithm for sparse networks. A simple criterion in terms of the number of vertices and edges of a network is given which indicates which of the Prim or Sollin algorithms as implemented is faster for a particular problem.
Pattern matching, acceptance, and parsing algorithms on node-labeled, ordered, ranked trees (live algorithms') are important for applications such as instruction selection and tree transformation/term rewriting. M...
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ISBN:
(纸本)9781586039752
Pattern matching, acceptance, and parsing algorithms on node-labeled, ordered, ranked trees (live algorithms') are important for applications such as instruction selection and tree transformation/term rewriting. Many such algorithms have been developed. They often are based on results from such algorithms on words or generalizations thereof using finite (tree) automata. Regrettably no coherent, extensive toolkit of such algorithms and automata existed, complicating their use. Our toolkit FOREST FIRE contains many such algorithms and automata constructions. It is accompanied by the graphical user interface (GUI) FIRE WOOD. The toolkit and GUI provide a useful environment for experimenting with and comparing the algorithms. In this tool paper we give an overview of the toolkit and GUI, their context and design rationale, and mention some results obtained with them.
Nowadays, multiprocessing is mainstream with exponentially increasing number of processors. Load balancing is, therefore, a critical operation for the efficient execution of parallel algorithms. In this paper we consi...
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ISBN:
(纸本)9781509027712
Nowadays, multiprocessing is mainstream with exponentially increasing number of processors. Load balancing is, therefore, a critical operation for the efficient execution of parallel algorithms. In this paper we consider the fundamental class of tree-based algorithms that are notoriously irregular, and hard to load-balance with existing static techniques. We propose a hybrid load balancing method using the utility of statistical random sampling in estimating the tree depth and node count distributions to uniformly partition an input tree. To conduct an initial performance study, we implemented the method on an Intel Xeon Phi accelerator system. We considered the tree traversal operation on both regular and irregular unbalanced trees manifested by Fibonacci and unbalanced (biased) randomly generated trees, respectively. The results show scalable performance for up to the 60 physical processors of the accelerator, as well as an extrapolated 128 processors case.
In this paper, we study binary tree-algorithms that exploit a combination of multi-packet reception (MPR) and successive interference cancellation (SIC), which so far has not been considered in the literature. Specifi...
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In this paper, we study binary tree-algorithms that exploit a combination of multi-packet reception (MPR) and successive interference cancellation (SIC), which so far has not been considered in the literature. Specifically, we assume that the receiver is capable of successfully decoding any collision of up to and including K concurrent packet transmissions and can perform SIC along the tree. We show a number of novel results for this type of tree algorithms. We first derive the basic performance parameters, which are the expected length of the collision resolution interval and the throughput normalized with K, conditioned on the number of contending users. We then analyze their asymptotic behaviour, identifying an oscillatory component that amplifies as K increases. In the next step, we derive the maximum stable throughput (MST) for the gated and windowed access assuming Poisson arrivals. We show that for windowed access, the bound on MST normalized with K increases with K. Finally, we discuss practical issues related to implementation of such scheme, as well as compare it to slotted ALOHA-based schemes that exploit both K-MPR and SIC.
Adversarial search of a network for an immobile Hider (or target) was introduced and solved for rooted trees by Shmuel Gal in 1979. In this zero-sum game, a Hider picks a point to hide on the tree and a Searcher picks...
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Adversarial search of a network for an immobile Hider (or target) was introduced and solved for rooted trees by Shmuel Gal in 1979. In this zero-sum game, a Hider picks a point to hide on the tree and a Searcher picks a unit speed trajectory starting at the root. The payoff (to the Hider) is the search time. In Gal's model (and many subsequent investigations), the Searcher receives no additional information after the Hider chooses his location. In reality, the Searcher will often receive such locational information. For homeland security, mobile sensors on vehicles have been used to locate radioactive material stashed in an urban environment. In a military setting, mobile sensors can detect chemical signatures from land mines. In predator-prey search, the predator often has specially attuned senses (hearing for wolves, vision for eagles, smell for dogs, sonar for bats, pressure sensors for sharks) that may help it locate the prey. How can such noisy locational information be used by the Searcher to modify her route? We model such information as signals which indicate which of two branches of a binary tree should be searched first, where all signals have a known accuracy p < 1. Our solution calculates which branch (at every branch node) is favored, meaning it should always be searched first when the signal is in that direction. When the signal is in the other direction, we calculate the probability the signal should be followed. Compared with the optimal Hider strategy in the classic search game of Gal, the Hider's optimal distribution for this model is more skewed toward leaf nodes that are further from the root.
We present methods to estimate systematic uncertainties in unbinned large hadron collider (LHC) data analyses, focusing on constraining Wilson coefficients in the standard model effective field theory (SMEFT). Our app...
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We present methods to estimate systematic uncertainties in unbinned large hadron collider (LHC) data analyses, focusing on constraining Wilson coefficients in the standard model effective field theory (SMEFT). Our approach also applies to broader parametric models of non-resonant phenomena beyond the standard model. By using machine-learned surrogates of the likelihood ratio, we extend well-established procedures from binned Poisson counting experiments to the unbinned case. This framework handles various theoretical, modeling, and experimental uncertainties, laying the foundation for future unbinned analyses at the LHC. We also introduce a tree-boosting algorithm that learns precise parametrizations of systematic effects, providing a robust, flexible alternative to neural networks for modeling systematics. We demonstrate this approach with an SMEFT analysis of highly energetic top quark pair production in proton-proton collisions.
This study investigates the influence of various printing parameters on the impact toughness of PLA products, utilizing small sample data and machine learning algorithms to expedite the identification of optimal tough...
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This study investigates the influence of various printing parameters on the impact toughness of PLA products, utilizing small sample data and machine learning algorithms to expedite the identification of optimal toughness. We propose a 3D printing tree algorithm model that focuses on the temporal distribution of impact toughness. The relationships between printing parameters and impact toughness are explored and predicted using three algorithms: Random Forest(RF),Light Gradient Boosting Machine(LightGBM) and Adaptive Boosting(AdaBoost). Experimental results indicate that the LightGBM algorithm yields the highest predictive accuracy, with the optimal parameter combination being a layer height of 0.3 mm, an infill density of 100 %, a printing speed of 60 mm/s, and a nozzle temperature of 200-210 degrees C.
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