Suspension force and mechanism of debris flows

The paper discusses the postulated suspension force, by which it is possible to explain some enigmatic phenomena observed in different types of mass movements. This force is generated in thick suspensions as a result of friction between sinking solid particles and static water. The suspension force is related to the seepage force but they have opposite directions. Both forces form flow networks. Having explained the suspension force, the paper describes how this influences the movement of material, particularly in debris flows. Enigmatic features and the mechanism of debris flows and lahars are explained by virtue of the suspension force. Electronic Publication     

Scheduling railway traffic at a construction site

We consider the problem of rescheduling trains in the case where one track of a railway section consisting of two tracks in opposing directions is closed due to construction activities. After presenting an appropriate model for this situation we derive a polynomial algorithm for the subproblem of finding an optimal schedule with minimal latenesss if the subsequences of trains for both directions outside the construction site are fixed. Based on this algorithm we propose a local search procedure for the general problem of finding good schedules and report test results for some real world instances. Received: December 8, 1999 / Accepted: May 2, 2001     

Sequential tripping strategy for a transmission network back-upprotection expert system

This paper describes a sequential tripping strategy used in a wide area back-up protection expert system (BPES) to combat situations in which protection relays have maloperated or information is missing. The BPES is an innovative back-up protection scheme designed to prevent the occurrence of widespread blackouts. The BPES evaluates the certainty that transmission lines are likely to be affected by the fault and uses a sequential tripping strategy to isolate the fault if a firm decision is not available due to maloperated relays and/or missing information. The mode of analysis and the sequential tripping strategy ensures that the BPES will clear a fault at minimum risk to the network. An example is included to demonstrate how the certainty factor based sequential tripping strategy is employed by the BPES to clear a fault which occurred on the South Western part of the UK National Grid System     

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.     

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).