Narrow Results

This study aims to detect objects quickly and accurately and then start the necessary obstacle avoidance procedure when the uncrewed vessel is at sea. This study uses a multivariate convolutional neural network (CNN) to perform automatic object detection and direction prediction for uncrewed vessels. This study is divided into three parts for processing. The first part of this process uses camera calibration technology to correct the image. Discrete cosine transform (DCT) is then used to detect sea level. Finally, this study uses Kalman filtering and affine transformation to stabilize images taken by uncrewed vessels at sea. The second part of the processing system uses a CNN to detect sea objects automatically. The third part of the process uses the dual-lens camera installed on the vessel to detect the distance and direction of objects at sea. In the experiment, the detection rate can reach more than 91% in this study method. In the experiment on image stabilization, this study’s method can also effectively improve video instability. In the experiment involving the distance and direction of the object, the experimental results show that the distance and direction of the object obtained by this study method have a distance error value of less than 10%, and the prediction results have a good effect no matter whether the object is at a short or long distance. It is hoped that this paper’s method can be applied to the automatic obstacle avoidance of unmanned vessels.

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A network of acoustic tide gauges was installed in 1992/93 to monitor long term relative sea level change and contribute to understanding of the tropical Pacific oceanography at shorter time scales. This study analyses the tide gauge data in conjunction with other sources of sea level information, weather and other oceanographic phenomena, over a range of time scales. For simplicity, the study is divided into two Parts. In Part 1, the data from the new network is verified by comparison with data from pre-existing, conventional tide gauges at seven sites where older technology had previously been installed. The accuracy of the acoustic data is found to improve on that of the pre-existing tide gauges, but an error analysis shows that the reduction in random error is not sufficient to reduce the time required to establish a linear trend by more than about one half year. In Part 2 attention is turned to observations of seasonal cycles and planetary waves. Two sites are selected for analysis: Rarotonga and Nuku'alofa. The tide gauge results are compared to sea levels from satellite altimeter and numerical model output. However, the intent is simply to present a preliminary statistical description as a basis for more exhaustive analyses which will be justified as more data comes available.

In 1990, scientists agreed that increasing atmospheric concentrations of greenhouse gases (GHG) will enhance the earth's average temperature in the coming decades. Later, the same group from Intergovernmental Panel on Climate Change (IPCC) 1995 reported that there is now a discernible effect of human activity. There continues to be substantial scientific uncertainty as to the magnitude of this impact on population, economic, environment and other sectors of the ecosystems, at global, regional and national levels. These uncertainties do not mean that GHG emissions can be safely ignored, rather they call for urgent response strategies to be developed.

This paper discusses the outputs from a number of scientific monitoring and research activities currently being implemented in the Pacific region, including the “South Pacific Sea Level and Climate Monitoring Project” in the Forum Island countries. These aim to reduce the uncertainties in order to formulate national response strategies to mitigate or reduce the impacts of climate change and sea level rise in the region.

The response options developed in the Pacific region will be discussed, emphasising especially the development of adaptation option-Integrated Coastal Management (ICM) and Planning.

Coastal areas have become more exposed to natural hazards. Therefore, the management of coastal hazards is becoming more essential. Unfortunately, coastal hazards are often overlooked until their occurrence brings severe damage to the coastal areas. As more people develop their assets and properties in coastal areas, the impact from coastal hazard phenomena increases, such as the risk of potential hazards against coastal communities and properties as a result of sea level rise. The objectives of this paper are to evaluate and review the quality of the coastal hazard management plans that have been implemented in several countries. Developing advanced setbacks based on the need to avoid or reduce risk and accepting uncertainties can be established and translated into planning and management system in a pragmatic and effective way. An organization can learn from the success and failures, proving to be an effective approach that crosses functional boundaries. Best practices, new technologies and knowledge are to be transferred through this approach. The approach proposed in this study is the preparation of coastal hazard management for coastal communities through informed, coordinated and timely actions over long term. It is necessary to avoid an uncoordinated sectoral approach and locally incoherent mitigation countermeasures. From the lessons learned, it is important to follow appropriate and effective coastal hazard management cycle chart as a guidance for protecting the coastal area and the community.