The Policy Dynamics of the Trans-Alaska Pipeline System
Since 1977, oil produced in northern Alaska has posed a major environmental threat across large areas of Alaska while simultaneously playing a dominant role in the economy of Alaska. This enduring dilemma was created by the building of the Trans-Alaska Pipeline System to transport oil produced on the North Slope of Alaska, a region containing the largest oil field ever developed in North America. The Trans-Alaska Pipeline System transports oil through an 800-mile pipeline and ocean-going oil tankers. This complex technological system poses an enduring risk of environmentally damaging oil spills in Alaska. This study applies the punctuated equilibrium theory of policy change to examine the processes and enduring consequences of the national policy reforms that allowed the building of the Trans-Alaska Pipeline System.
Interest Group Competition and the Alaska Native Land Claims Settlement Act
This article examines the competition among three main sets of interest groups during the struggle to resolve the Native land claims issue: the Natives, the development interests (oil companies and ...
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.