Unstructured tree search on SIMD parallel computers

We present new methods for load balancing of unstructured tree computations on large-scale SIMD machines, and analyze the scalability of these and other existing schemes. An efficient formulation of tree search on an SIMD machine consists of two major components: a triggering mechanism, which determines when the search space redistribution must occur to balance the search space over processors, and a scheme to redistribute the search space. We have devised a new redistribution mechanism and a new triggering mechanism. Either of these can be used in conjunction with triggering and redistribution mechanisms developed by other researchers. We analyze the scalability of these mechanisms and verify the results experimentally. The analysis and experiments show that our new load-balancing methods are highly scalable on SIMD architectures. Their scalability is shown to he no worse than that of the best load-balancing schemes on MIMD architectures. We verify our theoretical results by implementing the 15-puzzle problem on a CM-2 SIMD parallel computer     

Replacement of beef fat in Frankfurters by interesterified palm,cottonseed and olive oils

Three interesterified vegetable oils (IVOs) prepared from palm, cottonseed, and olive oil, respectively, have been studied for application to Frankfurters. Beef fat (10%) was replaced by one of the IVOs at 20, 60 or 100%. Fatty acid composition of the lipid fraction in the Frankfurters and saturated/unsaturated ratios were established for all batches. We found that total or partial replacement of beef fat by IVOs did not lead to significant changes in appearance, colour, texture, flavour or sensory score. We conclude that IVOs may be successfully applied as beef fat substitutes in Frankfurters.     

The organisational learning effects of management accounting information under advanced manufacturing technology

This study empirically examined the organisational learning effects of the nonfinancial performance information provided by management accounting information systems (MAISs) under advanced manufacturing technology (AMT). In this study, a target costing system and the frequent and quick reporting of information were considered the facilitators of learning. First, we examined the relationships between AMT level and the amount of nonfinancial performance information produced by MAISs. The empirical results showed that there are significant positive relationships between the level of AMT and nonfinancial performance information. With a systems approach, we also proved the impact of the relationships among AMT levels, nonfinancial performance information and learning facilitators on the organisational performance of a firm. The results of our research suggest that under a high level of AMT, for the provision of information to result in an increase of performance through organisational learning, a target costing system must be introduced and a large amount of information should be provided frequently and quickly. The results of this study also showed that although AMT level may be low, fairly well-arranged facilitators and a moderately large amount of information may be necessary for the improvement of performance. In conclusion, effective organisational learning depends on the provision of relevant information as well as efficient learning support mechanisms.     

General formalism for the study of nonlinear pulse propagation in optical fibres

A general formalism for the study of nonlinear pulse propagation in optical fibres is presented. It is then applied to study the time evolution of a Gaussian laser pulse in a fibre with cubic and fifth-order nonlinearity in the index of refraction. The results are presented and discussed.     

Automatic conversion from lexical words to prosodic words for mandarin text-to-speech system

In real speech, not like lexical words (LWs), prosodic words (PWs) are basic rhythmic units. The naturalness of a Text-to-Speech (TTS) system is directly influenced by the segmentation of the PWs. Most of the PWs are the combination of several LWs. In this paper, three Lexical Combination Models are proposed to combine LWs into PWs, including a Directed Acyclic Graph Model, a Segmentation Model and a Markov Model (MM). To cope with the situation where some long LWs should be segmented into two or more PWs, a Lexical Split Model (LSM) is applied to the long LWs. Experimental results prove that relatively constant results with various training data can be obtained from a MM. The Transformation-Based Error Driven Learning (TBED) algorithm, for its high performance of individual property, is applied in combination with the MM to improve the precision of PW segmentation. Experiments show that among the three proposed models, the MM combined with TBED and LSM, leads to the best performance, in which a precision of 93.00% and a recall of 93.23% are achieved. The perception test indicates that by using PWs as the lowest prosodic units a speech sounds more natural and acceptable than by using LWs. This paper is supported by NSFC Project (60503071); 973 Natural Basic Research Program of China (2004CB318102); Postdoctor Science Foundation of P. R. China (20070420275).