We consider the problem of routing in an asynchronous dynamically changing ring of processors using schemes that minimize the storage space for the routing information. In general, applying static techniques to a dyna...
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We consider the problem of routing in an asynchronous dynamically changing ring of processors using schemes that minimize the storage space for the routing information. In general, applying static techniques to a dynamic network would require significant re-computation. Moreover, the known dynamic techniques applied to the ring lead to inefficient schemes. In this paper we introduce a new technique, Dynamic Interval Routing, and we show tradeoffs between the stretch factor, the adaptation cost, and the size of the update messages used by routing schemes based upon it. We give three algorithms for rings of maximum size N: the first two are deterministic, one with adaptation cost zero but worst case stretch factor [N/2], the other with worst case adaptation cost O (N) update messages of 0 (log N) bits and stretch factor 1. The third algorithm is randomized, uses update messages of size O (k log N), has adaptation cost O (k), and expected stretch factor 1+1/k, for any integer kgreater than or equal to3. All schemes require O (log N) bits per node for the routing information and all messages headers are of O (log N) bits.
The paper presents an improved version of the region-growing algorithm for the interferometric phase unwrapping of the radar images. A method for packing/unpacking indices of points in a photograph that is based on bi...
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The paper presents an improved version of the region-growing algorithm for the interferometric phase unwrapping of the radar images. A method for packing/unpacking indices of points in a photograph that is based on bitwise operations is developed. A fast algorithm for generating a growth ring of target pixels and an algorithm for merging regions are created. Software implementation of the algorithm can be run on platforms using graphics devices that support the NVIDIA CUDA technology.
Navigation with the specific objective can be defined by specifying desired timed trajectory. The concept of desired direction field is proposed to deal with such navigation problem. To lay down a principled discussio...
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Navigation with the specific objective can be defined by specifying desired timed trajectory. The concept of desired direction field is proposed to deal with such navigation problem. To lay down a principled discussion of the accuracy and efficiency of navigation algorithms, strictly quantitative definitions of tracking error, actuator effect, and time efficiency are established. In this paper, one vision navigation control method based on desired direction field is proposed. This proposed method uses discrete image sequences to form discrete state space, which is especially suitable for bipedal walking robots with single camera walking on a free-barrier plane surface to track the specific objective without overshoot. The shortest path method (SPM) is proposed to design such direction field with the highest time efficiency. However, one improved control method called canonical piecewise-linear function (PLF) is proposed. In order to restrain the noise disturbance from the camera sensor, the band width control method is presented to significantly decrease the error influence. The robustness and efficiency of the proposed algorithm are illustrated through a number of computer simulations considering the error from camera sensor. Simulation results show that the robustness and efficiency can be balanced by choosing the proper controlling value of band width.
Random sequences and random numbers constitute a necessary part of cryptography. Many cryptographic protocols depend on random values. Randomness is measured by statistical tests and hence security evaluation of a cry...
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Random sequences and random numbers constitute a necessary part of cryptography. Many cryptographic protocols depend on random values. Randomness is measured by statistical tests and hence security evaluation of a cryptographic algorithm deeply depends on statistical randomness tests. In this work we focus on statistical distributions of runs of lengths one, two, and three. Using these distributions we state three new statistical randomness tests. New tests use chi(2) distribution and, therefore, exact values of probabilities are needed. Probabilities associated runs of lengths one, two, and three are stated. Corresponding probabilities are divided into five subintervals of equal probabilities. Accordingly, three new statistical tests are defined and pseudocodes for these new statistical tests are given. New statistical tests are designed to detect the deviations in the number of runs of various lengths from a random sequence. Together with some other statistical tests, we analyse our tests' results on outputs of well-known encryption algorithms and on binary expansions of e, pi, and root 2. Experimental results show the performance and sensitivity of our tests.
The web resources in the World Wide Web are rising, to large extent due to the services and applications provided by it. Because web traffic is large, gaining access to these resources incurs user-perceived latency. A...
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The web resources in the World Wide Web are rising, to large extent due to the services and applications provided by it. Because web traffic is large, gaining access to these resources incurs user-perceived latency. Although the latency can never be avoided, it can be minimized to a larger extent. Web prefetching is identified as a technique that anticipates the user's future requests and fetches them into the cache prior to an explicit request made. Because web objects are of various types, a new algorithm is proposed that concentrates on prefetching embedded objects, including audio and video files. Further, clustering is employed using adaptive resonance theory (ART) 2 in order to prefetch embedded objects as clusters. For comparative study, the web objects are clustered using ART2, ART1, and other statistical techniques. The clustering results confirm the supremacy of ART2 and, thereby, prefetching web objects in clusters is observed to produce a high hit rate.
The ten-year anniversary of TOPLAP presents a unique opportunity for reflection and introspection. In this essay we ask the question, what is the meaning of live coding? Our goal is not to answer this question, in abs...
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The ten-year anniversary of TOPLAP presents a unique opportunity for reflection and introspection. In this essay we ask the question, what is the meaning of live coding? Our goal is not to answer this question, in absolute terms, but rather to attempt to unpack some of live coding's many meanings. Our hope is that by exploring some of the formal, embodied, and cultural meanings surrounding live-coding practice, we may help to stimulate a conversation that will resonate within the live-coding community for the next ten years.
Context-aware applications aim at providing personalized services to end users. Sensors and context sources are able to provide enormous amounts of valuable information about individuals that can be used to drive the ...
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Context-aware applications aim at providing personalized services to end users. Sensors and context sources are able to provide enormous amounts of valuable information about individuals that can be used to drive the behavior of services and applications, and adapt them to the specific conditions and preferences of each user. Thanks to advances in mobility, convergence and integration, increasingly larger amounts of these data are available in the Internet. However, this context information is usually fragmented, and traditionally applications have had to take care of context management themselves. This work presents a solution for a converged context management framework and how it can be employed in a future Internet to integrate data from all context sources and serve it to client applications in a seamless and transparent manner. This framework takes advantage of the intelligent and convergent features of next-generation networks, allowing seamless integration, monitoring, and control of heterogeneous sensors and devices under a single context-aware service layer. This layer is centered on a context intelligence module, capable of combining clustering algorithms and semantics to learn from user usage history and take advantage of that information to infer missing or high-level context data.
Particle swarm optimization (PSO) algorithm has been developing rapidly and many results have been reported. PSO algorithm has shown some important advantages by providing high speed of convergence in specific problem...
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Particle swarm optimization (PSO) algorithm has been developing rapidly and many results have been reported. PSO algorithm has shown some important advantages by providing high speed of convergence in specific problems. but it has a tendency to get stuck in a near optimal solution and one may find it difficult to improve solution accuracy by fine tuning. This paper presents a dynamic global and local combined particle swarm optimization (DGLCPSO) algorithm to improve the performance of original PSO, in which all particles dynamically share the best information of the local particle, global particle and group particles. It is tested with a set of eight benchmark functions with different dimensions and compared with original PSO. Experimental results indicate that the DGLCPSO algorithm improves the search performance on the benchmark functions significantly, and shows the effectiveness of the algorithm to solve optimization problems. (C) 2009 Elsevier Ltd. All rights reserved.
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better tools for estimat...
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Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better tools for estimating disease progression are needed. Here, we report results from the DREAM-Phil Bowen ALS Prediction Prize4Life challenge. In this crowdsourcing competition, competitors developed algorithms for the prediction of disease progression of 1,822 ALS patients from standardized, anonymized phase 2/3 clinical trials. The two best algorithms outperformed a method designed by the challenge organizers as well as predictions by ALS clinicians. We estimate that using both winning algorithms in future trial designs could reduce the required number of patients by at least 20%. The DREAM-Phil Bowen ALS Prediction Prize4Life challenge also identified several potential nonstandard predictors of disease progression including uric acid, creatinine and surprisingly, blood pressure, shedding light on ALS pathobiology. This analysis reveals the potential of a crowdsourcing competition that uses clinical trial data for accelerating ALS research and development.
As voice over IP gains popularity, it is easy to imagine that Internet hacking and other security problems we currently face with email spam will attack the VoIP environment. In contrast to email protocols represented...
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As voice over IP gains popularity, it is easy to imagine that Internet hacking and other security problems we currently face with email spam will attack the VoIP environment. In contrast to email protocols represented by SMTP, VoIP does not tolerate any negotiation in its signaling steps or screening content due to the delay limitation. Thus, it is difficult to implement voice spam protection or control algorithms by just mimicking popular email spam protection algorithms. This article proposes a voice spam control algorithm called Progressive Multi Gray-Leveling (PMG) that fits in VoIP settings. PMG progressively calculates the "gray level" of a caller and determines whether the call will be connected or blocked based on previous call patterns. Based on experiments, it turns out that PMG can learn a spammer's calling pattern and block massive spam attacks from them effectively.
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