Numerical estimation of quantum channel capacity is an important problem both theoretically and practically. Oto et al. showed an effective approximation algorithm to compute a capacity of a one-qubit quantum channel....
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Numerical estimation of quantum channel capacity is an important problem both theoretically and practically. Oto et al. showed an effective approximation algorithm to compute a capacity of a one-qubit quantum channel. In this paper, we show an explicit upper bound for the error of their algorithm. The algorithm might be repeatedly used in the verification of a certain equation or inequality. The bound of the error we give is a criterion to decide when to stop that iteration, and eventually it can improve the performance of the whole process of the calculation.
This paper describes real chip implementation issues of network-on-chip (NoC) and their solutions along with series of chip design examples. The solutions described in this paper cover both architectural aspects and c...
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This paper describes real chip implementation issues of network-on-chip (NoC) and their solutions along with series of chip design examples. The solutions described in this paper cover both architectural aspects and circuit level techniques for practical chip implementation of NoC. As for architecture level solutions, topology selection, chip-aware protocol design, and on-chip serialization (OCS) for link area reduction are explained. For circuit level techniques, SERDES and synchronizer design, crossbar switch partial activation, and low-voltage link are presented as the foundations for power and area efficient NoC implementation. Regarding presented solutions for NoC implementation, this paper proposes memory centric NoC (MC-NoC) for homogeneous multi processor SoC (MPSoC). Flexibility and feasibility of task mapping on homogeneous SoC is the key feature of the MC-NoC. 8 dual port SRAMs connected to crossbar switches in hierarchical star topology network facilitate data communication between processors, regardless of task mapping into the MC-NoC. Experimental result obtained by mapping edge detection tasks on the MC-NoC in various configurations shows almost constant performance. This result proves the effectiveness of the proposed architecture. The MC-NoC based SoC is also implemented on TSMC 0.18 um process technology
An 81.6 GOPS object recognition processor is developed by using NoC and Visual Image Processing (VIP) memory. SIFT (Scale Invariant Feature Transform) object recognition requires huge computing power and data transact...
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An 81.6 GOPS object recognition processor is developed by using NoC and Visual Image Processing (VIP) memory. SIFT (Scale Invariant Feature Transform) object recognition requires huge computing power and data transactions among tasks. The chip integrates 10 SIMD PEs for data/task level parallelism while the NoC facilitates inter-PE communications. The VIP memory searches local maximum pixel inside a 3×3 window in a single cycle providing 65.6 GOPS. The proposed processor achieves 15.9fps SIFT feature extraction at 200MHz.
An 81.6 GOPS object recognition processor based on memory-centric NoC (MC-NoC) is implemented in a 0.18-mum CMOS technology. The MC-NoC facilitates data transactions among 10 SIMD processing elements (PEs) by exploiti...
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An 81.6 GOPS object recognition processor based on memory-centric NoC (MC-NoC) is implemented in a 0.18-mum CMOS technology. The MC-NoC facilitates data transactions among 10 SIMD processing elements (PEs) by exploiting 8 visual image processing (VIP) memories. The 10 PEs implement special SIMD instructions to perform Gaussian filtering at 16 GOPS. The 8 VIP memories provide one cycle local maximum pixels search operation performing 65.6 GOPS. The chip dissipates 1.4 W at 200 MHz operating frequency.
This paper presents an online semi-supervised clustering algorithm based on a self-organizing incremental neural network (SOINN). Using labeled data and a large amount of unlabeled data, the proposed semi-supervised S...
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This paper presents an online semi-supervised clustering algorithm based on a self-organizing incremental neural network (SOINN). Using labeled data and a large amount of unlabeled data, the proposed semi-supervised SOINN (ssSOINN) can automatically learn the topology of input data distribution without any prior knowledge such as the number of nodes or a good network structure; it can subsequently divide the structure into sub-structures as the need arises. Experimental results we obtained for artificial data and real-world data show that the ssSOINN has superior performance for separating data distributions with high-density overlap and that ssSOINN Classifier (S3C) is an efficient classifier.
Bolted joints are widely used in mechanical structures since the disassembly for maintenance is easy without high cost. However, vibration induced loosing due to dynamic loading has been unsolved subject for a long ti...
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Bolted joints are widely used in mechanical structures since the disassembly for maintenance is easy without high cost. However, vibration induced loosing due to dynamic loading has been unsolved subject for a long time. We have developed a new type of nut named 'hyper lock nut (HLN), which realizes anti-loosening performance without complicated tightening process and tool. In this study, we have investigated the mechanisms of bolted joint with HLN, and tightening behavior are analyzed by mean of three-dimensional finite element method. Results are compared with the experimental results for HLN. Good qualitative agreement is observed between analytical results and experiments with respect to displacement, tightening force and tightening torque. We found some new aspects and superior points for bolted-joint with HLN than that of standard nuts. It is found that tightening torque of HLN is higher than that of standard. It is also found that the anti-loosening performance can be realized by the thread contact force at the slit region and angular facing on bearing surface. Moreover, by mean of tensile and fatigue experiments, it is concluded that HLN involves sufficient strength in practical use.
We have examined the effect of spatial structures on the evolution of iterated prisoner's dilemma (IPD) game strategies. In our former study, we used two neighborhood structures, which follow the concept of struct...
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We have examined the effect of spatial structures on the evolution of iterated prisoner's dilemma (IPD) game strategies. In our former study, we used two neighborhood structures, which follow the concept of structured demes. One is for the interaction among players through the IPD game. A player in each cell in a grid-world plays against its neighbors defined by this neighborhood structure. The other is for the mating of strategies by genetic operations. A new strategy for a player is generated by genetic operations from a pair of parent strings, which are selected from its neighbors defined by the second neighborhood structure. In this paper, we extend our IPD game simulation to a more realistic problem while keeping the simplicity of the original IPD game. We employ a stochastic strategy represented by a string of real numbers between 0 and 1. Each real number in the string denotes the probability of cooperation. We examine the effects of spatial structures on the evolution of IPD game strategies with probabilistic decision making in various payoff matrices. From simulation results, it is shown that cooperative behavior is evolved only when the interaction neighborhood is small and the mating neighborhood is also small for some payoff matrices.
Information security and assurance is a rapidly developing area therefore government and industry have high demand for information security professionals. This paper reports collaboration activities between North Caro...
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Agent-based models are widely used for the simulation of systems from several domains (biology, economics, meteorology, etc). In biology agent-based models are very useful for predicting the social behaviour of system...
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Agent-based models are widely used for the simulation of systems from several domains (biology, economics, meteorology, etc). In biology agent-based models are very useful for predicting the social behaviour of systems; in particular they seem well adapted to model the behaviour of a cell population. In this paper an agent-based model, developed to study normal human keratinocytes (tissue cells), will be investigated. This kind of model exhibits probabilistic behaviour and the validation of simulation results is often done with a qualitative analysis by the experts (biologists). The main objective of this paper is to propose new variables and metrics that allow the comparison and a possible quantitative validation using numerical results from simulations.
Services in the ubiquitous computing are heterogeneous in nature. To be pervasive, these services should be defined in terms of their functionality and capabilities rather than the meaningless UUIDs or types of servic...
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Services in the ubiquitous computing are heterogeneous in nature. To be pervasive, these services should be defined in terms of their functionality and capabilities rather than the meaningless UUIDs or types of services. Thus, clients can access the proper service based on semantic requests. In this paper, we study the demand of semantic query in service discovery processes. Current discovery protocols and the concept of semantics are bringing together to construct a framework to realize the semantic service discovery for ubiquitous computing. Many issues are discussed in relation to service discovery topologies, ontology languages, and semantic query languages.
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