5569010
A Fast Efficient Parallel Hough Transform Algorithm on LARPBS
A parallel algorithm for Hough transform on a linear array with reconfigurable pipeline bus system (LARPBS) is presented. Suppose the number of θ-values to be considered is m, for an image with n × n pixels, the algorithm can complete Hough transform in O(1) time using mn2 processors and achieve optimal speed and efficiency. We also illustrate how to partition data and perform the algorithm on a LARPBS with fewer than mn2 processors, and hence show that the algorithm is highly scalable.
60542101
A novel ant clustering algorithm based on cellular automata
Based on the principle of cellular automata in artificial life, an artificial ant sleeping model (ASM) and an ant algorithm for cluster analysis (A4C) are presented. Inspired by the behaviors of gregarious ant colonies, we use the ant agent to represent a data object. In ASM, each ant has two states: a sleeping state and an active state. The ant's state is controlled by a function of the ant's fitness to the environment it locates and a probability for the ants becoming active. The state of an ant is determined only by its local information. By moving dynamically, the ants form different subgroups adaptively, and hence the data objects they represent are clustered. Experimental results show that the A4C algorithm on ASM is significantly better than other clustering methods in terms of both speed and quality. It is adaptive, robust and efficient, achieving high autonomy, simplicity and efficiency.
441449
A novel ant clustering algorithm based on cellular automata
Based on the principle of cellular automata in artificial life, an artificial ant sleeping model (ASM) and an ant algorithm for cluster analysis (A4C) are presented. Inspired by the behaviors of gregarious ant colonies, we use the ant agent to represent a data object. In ASM, each ant has two states: a sleeping state and an active state. The ant's state is controlled by a function of the ant's fitness to the environment it locates and a probability for the ants becoming active. The state of an ant is determined only by its local information. By moving dynamically, the ants form different subgroups adaptively, and hence the data objects they represent are clustered. Experimental results show that the A4C algorithm on ASM is significantly better than other clustering methods in terms of both speed and quality. It is adaptive, robust and efficient, achieving high autonomy, simplicity and efficiency.
6316461
Partitioned optimization algorithms for multiple sequence alignment
Multiple sequence alignment is an important and difficult problem in molecular biology and bioinformatics. In this paper, we propose a partitioning approach that significantly improves the solution time and quality by utilizing the locality structure of the problem. The algorithm solves the multiple sequence alignment in three stages. First, an automated and suboptimal partitioning strategy is used to divide the set of sequences into several subsections. Then a multiple sequence alignment algorithm based on ant colony optimization is used to align the sequences of each subsection. Finally, the alignment of original sequences can be obtained by assembling the result of each subsection. The ant colony algorithm is highly optimized in order to avoid local optimal traps and converge to global optimal efficiently. Experimental results show that the algorithm can significantly reduce the running time and improve the solution quality on large-scale multiple sequence alignment benchmarks.
2673173
State Aware Data Dissemination over Structured Overlays
We describe the problem of data dissemination in stream-oriented applications where the required filter is a function of the current state. We call such functions dynamic filters. A state aware data dissemination network (SA-DDN) is proposed to support dynamic filters. Two approaches single-level filtering (SF) and multilevel filter decomposition (MFD) are proposed to facilitate the data dissemination. We show how MFD improves performance over SF. We then describe a realization of SA-DDN on top of an improved bi-directional Chord overlay with a built-in multicast mechanism. An application of stock price monitoring is implemented based on SA-DDN and real life stock quotes are collected to demonstrate the feasibility of our system. Extensive simulations are performed to compare the performance of both approaches and provide insight into the advantages of MFD
16535706
An efficient architecture for two-dimensional discrete wavelet transform
This paper proposes an efficient architecture for the two-dimensional discrete wavelet transform (2-D DWT). The proposed architecture includes a transform module, a RAM module, and a multiplexer. In the transform module, we employ the polyphase decomposition technique and the coefficient folding technique to the decimation filters of stages 1 and 2, respectively. In comparison with other 2-D DWT architectures, the advantages of the proposed architecture are 100% hardware utilization, fast computing time (0.5-0.67 times of the parallel filters'), regular data flow, and low control complexity, making this architecture suitable for next generation image compression systems, e.g., JPEG-2000.
6076707
Bridging Nonliving and Living Matter
Assembling non-biological materials (geomaterials) into a proto-organism constitutes a bridge between nonliving and living matter. In this article we present a simple step-by-step route to assemble a proto-organism. Many pictures have been proposed to describe this transition within the origins-of-life and artificial life communities, and more recently alternative pictures have been emerging from advances in nanoscience and biotechnology. The proposed proto-organism lends itself to both traditions and defines a new picture based on a simple idea: Given a set of required functionalities, minimize the physicochemical structures that support these functionalities, and make sure that all structures self-assemble and mutually enhance each other's existence. The result is the first concrete, rational design of a simple physicochemical system that integrates the key functionalities in a thermodynamically favorable manner as a lipid aggregate integrates proto-genes and a proto-metabolism. Under external pumping of free energy, the metabolic processes produce the required building blocks, and only specific gene sequences enhance the metabolic kinetics sufficiently for the whole system to survive. We propose an experimental implementation of the proto-organism with a discussion of our experimental results, together with relevant results produced by other experimental groups, and we specify what is still missing experimentally. Identifying the missing steps is just as important as providing the road map for the transition. We derive the kinetic and thermodynamic conditions of each of the proto-organism subsystems together with relevant theoretical and computational results about these subsystems. We present and discuss detailed 3D simulations of the lipid aggregation processes. From the reaction kinetics we derive analytical aggregate size distributions, and derive key properties of the metabolic efficiency and stability. Thermodynamics and kinetics of the ligation directed self-replication of the proto-genes is discussed, and we summarize the full life cycle of the proto-organism by comparing size, replication time, and energy with the biomass efficiency of contemporary unicells. Finally, we also compare our proto-organism picture with existing origins-of-life and protocell pictures. By assembling one possible bridge between nonliving and living matter we hope to provide a piece in the ancient puzzle about who we are and where we come from.
10353520
Finding Self-Similarities in Opportunistic People Networks
Opportunistic network is a type of delay tolerant networks (DTN) where network communication opportunities appear opportunistic. In this study, we investigate opportunistic network scenarios based on public network traces, and our contributions are the following: First, we identify the censorship issue in network traces that usually leads to strongly skewed distribution of the measurements. Based on this knowledge, we then apply the Kaplan-Meier Estimator to calculate the survivorship of network measurements, which is used in designing our proposed censorship removal algorithm (CRA) that is used to recover censored data. Second, we perform a rich set of analysis illustrating that UCSD and Dartmouth network traces show strong self-similarity, and can be modeled as such. Third, we pointed out the importance of these newly revealed characteristics in future development and evaluation of opportunistic networks.
206952974
High throughput CORDIC-based systolic array design for the discrete cosine transform
In this paper, we propose a modified Malvar algorithm that can transfer the Discrete Hartley Transform (DHT) results to the Discrete Cosine Transform (DCT) by using a one additional CORDIC computing stage. A fast CORDIC-based systolic array is designed with four attractive features the single/double data folding feature; the constructive feature; the co-computing feature; and redundant path computation. Due to the existence of the redundant path, the proposed design also has the capability of error detection.<<ETX>>