On‐Chip Bus Serialization Method for Low‐Power Communications

One of the critical issues in on‐chip serial communications is increased power consumption. In general, serial communications tend to dissipate more energy than parallel communications due to bit multiplexing. This paper proposes a low‐power bus serialization method. This encodes bus signals prior to serialization so that they are converted into signals that do not greatly increase in transition frequency when serialized. It significantly reduces the frequency by making the best use of word‐to‐word and bit‐by‐bit correlations presented in original parallel signals. The method is applied to the revision of an MPEG‐4 processor, and the simulation results show that the proposed method surpasses the existing one. In addition, it is cost‐effective when implemented as a hardware circuit since its algorithm is very simple.     

Compact feature subset-based multi-label music categorization for mobile devices

Music categorization based on acoustic features extracted from music clips and user-defined tags forms the basis of recent music recommendation applications, because relevant tags can be automatically assigned based on the feature values and their relation to tags. In practice, especially for handheld lightweight mobile devices, there is a certain limitation on the computational capacity, owing to consumers’ usage behavior or battery consumption. This also limits the maximum number of acoustic features to be extracted, and results in the necessity of identifying a compact feature subset that is used for the music categorization process. In this study, we propose an approach to compact feature subset-based multi-label music categorization for mobile music recommendation services. Experimental results using various multi-labeled music datasets reveal that the proposed approach yields better performance when compared to conventional approach.

     

A multiscale model for modulus of elasticity of concrete at high temperatures

In this paper, the thermal degradation of modulus of elasticity of concrete is modeled by composite mechanics at three scales of observation: (a) at the level of concrete, (b) at the level of mortar, and (c) the cement paste level. At the latter, the change of volume fractions of the constituents are evaluated based on phase transformations which take place in different temperature ranges. Stoichiometric models are used to determine the volume changes of the constituents. At the mortar and concrete levels, the temperature dependence of fine and coarse aggregates is considered based on available test data. The multiscale chemo-mechanical model can be used to predict the temperature dependence and thermal degradation of the elastic concrete modulus. The model predictions are compared with test data in the literature as well as in-house test data.