Intifada 3.0? Cyber colonialism and Palestinian resistance

Palestine “exists” on Google and increasingly in various other “virtual” ways. But are “Palestine” on Google or the acquisition of the google.ps domain name in 2009 examples of political resistance on the internet? For Palestinian politicians, virtual presence has historical significance. Consider, for example, the Ministry of Telecommunications and Information Technology’s (MTIT) suggestion that “ICTs information and communications technology] contribute directly to the national goal of establishing and building an independent state.”3 Within that context, Sabri Saydam, adviser to Palestinian Authority (PA) president Mahmoud Abbas and a former MTIT minister himself, posited Google’s 2013 move as “a step towards...liberation.” 4 For Israeli politicians, as quoted above, the emergence of (a virtual) “Palestine” poses ideological and practical dangers. Both camps ascribe power to the internet. Their only disagreement is over the ends to which the internet is a means: The internet is a threat to the existence of the state of Israel or a step toward a future state. At heart, however, both views are a form of technological determinism. They remove the internet from human, historical, and geopolitical contexts, and posit it as agent of political, social, or economic change. We contend that neither position is valid

Pairwise Confusion for Fine-Grained Visual Classification

Fine-Grained Visual Classification (FGVC) datasets contain small sample sizes, along with significant intra-class variation and inter-class similarity. While prior work has addressed intra-class variation using localization and segmentation techniques, inter-class similarity may also affect feature learning and reduce classification performance. In this work, we address this problem using a novel optimization procedure for the end-to-end neural network training on FGVC tasks. Our procedure, called Pairwise Confusion (PC) reduces overfitting by intentionally {introducing confusion} in the activations. With PC regularization, we obtain state-of-the-art performance on six of the most widely-used FGVC datasets and demonstrate improved localization ability. {PC} is easy to implement, does not need excessive hyperparameter tuning during training, and does not add significant overhead during test time.Comment: Camera-Ready version for ECCV 201

An analysis of design for manufacturing requirements for managing aerospace manufacturing knowledge

In the manufacturing lifecycle of aerospace products, large amounts of data are generated throughout the activities involved. Much of this data contains useful knowledge for engineers to improve various aspects of Design for Manufacturing (DFM) of new or existing products that may help reduce defects in future manufacturing activities. An investigation is carried out at a large UK based manufacturer of aerospace products that aims to introduce an improved approach that supports design engineering activities to make use of the ‘data’ generated to drive the number of re-occurring defects down. This paper particularly focuses on analyzing the requirements for introducing a solution identified from questionnaires, observations and stakeholder reviews and proposes a framework of the components to enable its implementation. The research discussed the requirements and concludes the main findings toward implementing a fully integrated solution at the collaborating company in order to improve data usefulness and effectiveness