Ecosystem Approach to Fisheries Management (Essential EAFM) training and TOT in Sri Lanka

This report presents presentations from representatives of 12 countries, key outcomes and recommendations for the future.

Training aspects for a trawling fishery

Trawling experiments carried out by the United Nations Development Programme Project and the Uganda Department of Fisheries, strongly suggest that the trawling method of fishing, if introduced on Lake Victoria, would bring about a tremendous increase in fish production from the lake. It is recognised, however, that before trawling is introduced, its economic, social, technical, biological and manpower implications must be carefully analysed. I now propose to discuss the training aspects of a trawl fishery on Lake Victoria.

Gaussian Process training with input noise

In standard Gaussian Process regression input locations are assumed to be noise free. We present a simple yet effective GP model for training on input points corrupted by i.i.d. Gaussian noise. To make computations tractable we use a local linear expansion about each input point. This allows the input noise to be recast as output noise proportional to the squared gradient of the GP posterior mean. The input noise variances are inferred from the data as extra hyperparameters. They are trained alongside other hyperparameters by the usual method of maximisation of the marginal likelihood. Training uses an iterative scheme, which alternates between optimising the hyperparameters and calculating the posterior gradient. Analytic predictive moments can then be found for Gaussian distributed test points. We compare our model to others over a range of different regression problems and show that it improves over current methods.

Factor analysis based VTS discriminative adaptive training

Vector Taylor Series (VTS) model based compensation is a powerful approach for noise robust speech recognition. An important extension to this approach is VTS adaptive training (VAT), which allows canonical models to be estimated on diverse noise-degraded training data. These canonical model can be estimated using EM-based approaches, allowing simple extensions to discriminative VAT (DVAT). However to ensure a diagonal corrupted speech covariance matrix the Jacobian (loading matrix) relating the noise and clean speech is diagonalised. In this work an approach for yielding optimal diagonal loading matrices based on minimising the expected KL-divergence between the diagonal loading matrix and "correct" distributions is proposed. The performance of DVAT using the standard and optimal diagonalisation was evaluated on both in-car collected data and the Aurora4 task. © 2012 IEEE.

N-best error simulation for training spoken dialogue systems

A recent trend in spoken dialogue research is the use of reinforcement learning to train dialogue systems in a simulated environment. Past researchers have shown that the types of errors that are simulated can have a significant effect on simulated dialogue performance. Since modern systems typically receive an N-best list of possible user utterances, it is important to be able to simulate a full N-best list of hypotheses. This paper presents a new method for simulating such errors based on logistic regression, as well as a new method for simulating the structure of N-best lists of semantics and their probabilities, based on the Dirichlet distribution. Off-line evaluations show that the new Dirichlet model results in a much closer match to the receiver operating characteristics (ROC) of the live data. Experiments also show that the logistic model gives confusions that are closer to the type of confusions observed in live situations. The hope is that these new error models will be able to improve the resulting performance of trained dialogue systems. © 2012 IEEE.

Complementary Phone Error training

This paper introduces a novel method for the training of a complementary acoustic model with respect to set of given acoustic models. The method is based upon an extension of the Minimum Phone Error (MPE) criterion and aims at producing a model that makes complementary phone errors to those already trained. The technique is therefore called Complementary Phone Error (CPE) training. The method is evaluated using an Arabic large vocabulary continuous speech recognition task. Reductions in word error rate (WER) after combination with a CPE-trained system were obtained with up to 0.7% absolute for a system trained on 172 hours of acoustic data and up to 0.2% absolute for the final system trained on nearly 2000 hours of Arabic data.

Training and assignment of multi-skilled workers for implementing seru production systems

Confronted with high variety and low volume market demands, many companies, especially the Japanese electronics manufacturing companies, have reconfigured their conveyor assembly lines and adopted seru production systems. Seru production system is a new type of work-cell-based manufacturing system. A lot of successful practices and experience show that seru production system can gain considerable flexibility of job shop and high efficiency of conveyor assembly line. In implementing seru production, the multi-skilled worker is the most important precondition, and some issues about multi-skilled workers are central and foremost. In this paper, we investigate the training and assignment problem of workers when a conveyor assembly line is entirely reconfigured into several serus. We formulate a mathematical model with double objectives which aim to minimize the total training cost and to balance the total processing times among multi-skilled workers in each seru. To obtain the satisfied task-to-worker training plan and worker-to-seru assignment plan, a three-stage heuristic algorithm with nine steps is developed to solve this mathematical model. Then, several computational cases are taken and computed by MATLAB programming. The computation and analysis results validate the performances of the proposed mathematical model and heuristic algorithm. © 2013 Springer-Verlag London.

Impact of Brunswick river mouth training walls on adjacent beaches, Brunswick heads, New South Wales, Australia

River training walls have been built at scores of locations along the NSW coast and their impacts on shoreline change are still not fully understood. In this study, the Brunswick River entrance and adjacent beaches are selected for examination of the impact of the construction of major training walls. Thirteen sets of aerial photographs taken between 1947 and 1994 are used in a CIS approach to accurately determine tire shoreline Position, beach contours and sand volumes, and their changes in both time and space, and then to assess the contribution of both tire structures and natural hydrodynamic conditions to large scale (years-decades and kilometres) beach changes. The impact of the training walls can be divided into four stages: natural conditions prior to their construction (pre 1959), major downdrift erosion and updrift accretion during and. following the construction of the walls in 1959 similar to 1962 and 1966. diminishing impact of the walls between 1966 and 1987, and finally no apparent impact between 1987 similar to 1994. The impact extends horizontally about 8 km updrift and 17 km downdrift, and temporally up to 25 years..

New method for analysis of Chinese herbal complex prescription and its application

Traditional Chinese medicine (TCM) is a great treasure of China, the analysis of which is an arduous task. The viewpoint that all chemical constituents of Chinese herbal complex prescription should be analyzed as a black box is elucidated for the first time. Intelligent multi-mode multi-column chromatographic system (IMMCC) with its hybrids is the basic method and HPLC Unified Method is the breakthrough for the black box analysis. Dang-Gui-Bu-Xue-Tang was selected as a typical TCM and a systematic separation method from non-aqueous mobile phase to pure water mobile phase was put forward in order to convert unknown sample to known sample. The a, c values and UV spectra of 66 components of Astragalus, 78 components of Angelica and 71 components of Dang-Gui-Bu-Xue-Tang were obtained. Intelligent optimization and peak identification method and software for complex samples were developed and the optimum multi-step multi-binary gradient curve of mobile phase for Astragalus was ascertained. The maximum error and minimum error of predicted retention time for all components of Astragalus are 8.62% and 0.05% respectively. All components of Astragalus were compared with those of Angelica and it is found that many components of Astragalus are the same as those of Angelica, while the contents of these components are different. Many components of Dang-Gui-Bu-Xue-Tang are also the same as those of Astragalus and Angelica with different contents.