BOBLME Mergui Archipelago Stakeholder Workshop, Yangon, Myanmar, 11-12 October, 2010

Updating environmental baselines and information; identification of major gaps; promotion of environmental services; promotion of livelihood interests; systematic monitoring practices; and increasing public awareness

Report on the current state of the fishery of the Ugandan sector of Lake Albert

Following a general outcry by the population riparian to the Ugandan portion of lake Albert about dwindling fish catches, there was concern both from the FAO Country representative in Uganda and the government of Uganda on the state of the fisheries of this lake. The FAO representative accompanied by an official from the Uganda Fisheries and Fish Conservation Association (UFFCA) visited the lake in July 1999 (Appendix I). The Ugandan minister of state in charge of the Fisheries sector also visited the lake in November 1999 (Appendix II). The two were in common agreement that the lake was in a stocks crisis and there was need for remedial measures. It was therefore deemed necessary to initiate a technical report updating the present state of the fisheries resources of this lake. An agreement was thus signed between the author and the Food and Agricultural Organization of the United Nations - Sub-Regional Office for Southern Africa in Harare, to undertake this exercise.

Bayesian inference for multidimensional NMR image reconstruction

Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans.

Theories of instrumental learning are centred on understanding how success and failure are used to improve future decisions. These theories highlight a central role for reward prediction errors in updating the values associated with available actions. In animals, substantial evidence indicates that the neurotransmitter dopamine might have a key function in this type of learning, through its ability to modulate cortico-striatal synaptic efficacy. However, no direct evidence links dopamine, striatal activity and behavioural choice in humans. Here we show that, during instrumental learning, the magnitude of reward prediction error expressed in the striatum is modulated by the administration of drugs enhancing (3,4-dihydroxy-L-phenylalanine; L-DOPA) or reducing (haloperidol) dopaminergic function. Accordingly, subjects treated with L-DOPA have a greater propensity to choose the most rewarding action relative to subjects treated with haloperidol. Furthermore, incorporating the magnitude of the prediction errors into a standard action-value learning algorithm accurately reproduced subjects' behavioural choices under the different drug conditions. We conclude that dopamine-dependent modulation of striatal activity can account for how the human brain uses reward prediction errors to improve future decisions.

A Bayesian framework to predict deformations during supported excavations based on a semi-empirical method

The ground movements induced by the construction of supported excavation systems are generally predicted by empirical/semi-empirical methods in the design stage. However, these methods cannot account for the site-specific conditions and for information that becomes available as an excavation proceeds. A Bayesian updating methodology is proposed to update the predictions of ground movements in the later stages of excavation based on recorded deformation measurements. As an application, the proposed framework is used to predict the three-dimensional deformation shapes at four incremental excavation stages of an actual supported excavation project. © 2011 Taylor & Francis Group, London.

A Bayesian framework to predict deformations during supported excavations based on a semi-empirical method

The ground movements induced by the construction of supported excavation systems are generally predicted in the design stage by empirical/semi-empirical methods. However, these methods cannot account for the site-specific conditions and for information that become available as an excavation proceeds. A Bayesian updating methodology is proposed to update the predictions of ground movements in the later stages of excavation based on recorded deformation measurements. As an application, the proposed framework is used to predict the three-dimensional deformation shapes at four incremental excavation stages of an actual supported excavation project. Copyright © ASCE 2011.

Enhanced integrated modelling approach to reconfiguring manufacturing enterprises

Dynamism and uncertainty are real challenges for present day manufacturing enterprises (MEs). Reasons include: an increasing demand for customisation, reduced time to market, shortened product life cycles and globalisation. MEs can reduce competitive pressure by becoming reconfigurable and change-capable. However, modern manufacturing philosophies, including agile and lean, must complement the application of reconfigurable manufacturing paradigms. Choosing and applying the best philosophies and techniques is very difficult as most MEs deploy complex and unique configurations of processes and resource systems, and seek economies of scope and scale in respect of changing and distinctive product flows. It follows that systematic methods of achieving model driven reconfiguration and interoperation of component based manufacturing systems are required to design, engineer and change future MEs. This thesis, titled Enhanced Integrated Modelling Approach to Reconfiguring Manufacturing Enterprises , introduces the development and prototyping a model-driven environment for the design, engineering, optimisation and control of the reconfiguration of MEs with an embedded capability to handle various types of change. The thesis describes a novel systematic approach, namely enhanced integrated modelling approach (EIMA), in which coherent sets of integrated models are created that facilitates the engineering of MEs especially their production planning and control (PPC) systems. The developed environment supports the engineering of common types of strategic, tactical and operational processes found in many MEs. The EIMA is centred on the ISO standardised CIMOSA process modelling approach. Early study led to the development of simulation models during which various CIMOSA shortcomings were observed, especially in its support for aspects of ME dynamism. A need was raised to structure and create semantically enriched models hence forming an enhanced integrated modelling environment. The thesis also presents three industrial case examples: (1) Ford Motor Company; (2) Bradgate Furniture Manufacturing Company; and (3) ACM Bearings Company. In order to understand the system prior to realisation of any PPC strategy, multiple process segments of any target organisation need to be modelled. Coherent multi-perspective case study models are presented that have facilitated process reengineering and associated resource system configuration. Such models have a capability to enable PPC decision making processes in support of the reconfiguration of MEs. During these case studies, capabilities of a number of software tools were exploited such as Arena®, Simul8®, Plant Simulation®, MS Visio®, and MS Excel®. Case study results demonstrated effectiveness of the concepts related to the EIMA. The research has resulted in new contributions to knowledge in terms of new understandings, concepts and methods in following ways: (1) a structured model driven integrated approach to the design, optimisation and control of future reconfiguration of MEs. The EIMA is an enriched and generic process modelling approach with capability to represent both static and dynamic aspects of an ME; and (2) example application cases showing benefits in terms of reduction in lead time, cost and resource load and in terms of improved responsiveness of processes and resource systems with a special focus on PPC; (3) identification and industrial application of a new key performance indicator (KPI) known as P3C the measuring and monitoring of which can aid in enhancing reconfigurability and responsiveness of MEs; and (4) an enriched modelling concept framework (E-MUNE) to capture requirements of static and dynamic aspects of MEs where the conceptual framework has the capability to be extended and modified according to the requirements. The thesis outlines key areas outlining a need for future research into integrated modelling approaches, interoperation and updating mechanisms of partial models in support of the reconfiguration of MEs.

Preliminary results of the updated LECR2 source-LECR2M

The Latest developed LECR2M (Lanzhou ECR No. 2 Modified) source is the updated one of LECR2 (Lanzhou ECR No. 2) source at IMP. It has been assembled on the low energy ion beam experimental platform to produce MCI beams for atomic physics and material physics experimental research. In our updating program, the structure of injection and extraction components has been modified to make the source structure more simple and effective. The hexapole magnet has also been replaced by a new hexapole magnet with higher radial field and larger inner diameter. With this updating, stronger magnetic field confinement of the ECR plasma is possible and better base vacuum condition is also achieved. LECR2M was designed to be operated at 14.5GHz. During the preliminary test, 1.3emA O6+ beam was extracted with the injected rf power of 1.1kW. The source has been used to deliver intense MCI beams for different experiments. After some discussion of the main features of this newly updated source, some of the typical commissioning test results of LECR2M will be presented.

软件发布机制体系结构研究

针对现有软件发布方式主要以开发者的角度进行软件开发后生命周期管理所存在的问题,提出了更为合理的以用户的角度进行软件开发后生命周期管理的思想,建立了一种新的软件发布机制体系结构。该发布机制试图解决如下问题:让用户透明地使用软件,即用户不需要显式地进行软件的安装、更新和卸载;支持软件的即点即用和使用态发布,使用态发布指安装了某软件的计算机可以作为该软件的发布源;使得系统重装后能够以较小的代价恢复到指定的状态点。最后,分析了软件动态更新和分布式软件系统发布所应解决的问题。

双模式相关技术研究与实现

文中研究的相关跟踪技术主要应用于飞航导弹的末制导。现阶段，激光制导技术、GPS制导技术、合成孔径雷达（SAR）制导技术在我国的实际应用还不成熟，传统的电视、红外制导技术仍然具有很强的生命力，因而，基于可见光的视频相关跟踪技术具有重要的研究价值。本文主要论述的两种相关算法是：多灰度点相关（MPC）、区域模板相关（RTC）。其中多点相关（MPC）算法的跟踪灵敏度高，定位精度好，硬件实现比较方便，实时性能好；区域模板相关算法（RTC），在图像的匹配过程中，不仅考虑了目标区域的灰度特征，而且兼顾了区域里多灰度层次的位置特征、面积特征，算法具有很好的鲁棒性。文中深入研究了两种相关跟踪算法，并针对它们在实际应用中的不足，提出了有效的改善措施。最后，本文对两种相关跟踪算法进行了初步融合，一是：通过粗匹配、精匹配过程来选取目标跟踪点；二是：提出了一种度量模板更新的能量准则函数。大量的仿真实验结果表明：改进后的两种相关跟踪技术可以较好地完成一些复杂背景下的目标跟踪任务，两种算法的有效结合又进一步提高了目标跟踪的稳定性能和可靠性能。本文研究的一些相关跟踪技术已经运用到实际工程项目中。

一种面向无线传感器网络协同任务分配的动态联盟更新机制

在面向目标追踪等应用的无线传感器网络研究中,协同任务分配机制的研究是很重要的。基于动态联盟机制的协同任务分配方法是事件触发的,适用于任务出现频率相对较低的大规模无线传感器网络。本文在基于动态联盟机制研究的基础上,首先引入了联盟覆盖范围和休眠盟员的概念,进一步消除针对同一任务的检测传感器节点的冗余,降低系统的能量消耗;而后又给出了一种动态联盟的更新机制,以保证动态联盟执行任务时的连续性,在一定程度上保证网络的检测性能。最后通过仿真,从系统总能耗、目标捕获率和检测误差标准差等方面检验了算法的性能,并给出了缓冲带宽度等参数对能耗和网络检测性能的影响。

模型无关的无定标视觉伺服控制

本文首先介绍了视觉伺服的一般原理 .然后提出了一种模型无关的无定标视觉伺服控制方法 ,在这种方法中不需要机器人模型和摄像机模型 ,应用方差最小化的原理推导出了模型无关的无定标视觉伺服控制律 .此外还给出了图像雅可比矩阵的递推公式 .文章最后通过一个轨线跟踪的仿真实验验证了算法的正确性和有效性

基于Vega Prime的多水下机器人视景仿真系统的设计与实现

介绍了一套多水下机器人三维视景仿真系统。该系统采用虚拟现实技术，利用虚拟仿真软件VegaPrime 与Visual C++.NET 2003 混合编程实现三维视景仿真。它主要用于海洋环境的模拟和多水下机器人运行时的位姿更新、碰撞检测、环境效果及各种特效的实时显示。此外，它还具有响应各种输入/输出设备的功能和通过人性化图形界面接口与用户进行交互的功能。

基于关系模型的含空值关系数据库的数据更新

本文以空值的完全语义为基础，以空值环境下基于５值（５ＶＬ）的选择运算为工具，深入研究了基于关于模型的含空值关系数据库的数据更新策略和实现算法

空值环境下含不确定及可能信息关系数据库的更新

本文在［１］扩展关系模型中引入属性级的不完全信息空值。为适应此环境下更新操作的需要，本文对［１］中的扩展关系模型进行了进一步的扩展，并以此模型为基础讨论了空值环境下含不确定及可能信息关系数据库的更新操作的策略，给出了相应的处理算法。