GPU-driven recombination and transformation of YCoCg-R video samples

Common programmable Graphics Processing Units (GPU) are capable of more than just rendering real-time effects for games. They can also be used for image processing and the acceleration of video decoding. This paper describes an extended implementation of the H.264/AVC YCoCg-R to RGB color space transformation on the GPU. Both the color space transformation and recombination of the color samples from a nontrivial data layout are performed by the GPU. Using mid- to high-range GPUs, this extended implementation offers a significant gain in processing speed compared to an existing basic GPU version and an optimized CPU implementation. An ATI X1900 GPU was capable of processing more than 73 high-resolution 1080p YCoCg-R frames per second, which is over twice the speed of the CPU-only transformation using a Pentium D 820

Protecting the environment for self-interested reasons. Altruism is not the only pathway to sustainability

Concerns for environmental issues are important drivers of sustainable and pro-environmental behaviors, and can be differentiated between those with a self-enhancing (egoistic) vs. self-transcendent (biospheric) psychological foundation. Yet to date, the dominant approach for promoting pro-environmental behavior has focused on highlighting the benefits to others or nature, rather than appealing to self-interest. Building on the Inclusion Model for Environmental Concern, we argue that egoistic and biospheric environmental concerns, respectively, conceptualized as self-interest and altruism, are hierarchically structured, such that altruism is inclusive of self-interest. Three studies show that self-interested individuals will behave more pro-environmentally when the behavior results in a personal benefit (but not when there is exclusively an environmental benefit), while altruistic individuals will engage in pro-environmental behaviors when there are environmental benefits, and critically, also when there are personal benefits. The reported findings have implications for programs and policies designed to promote pro-environmental behavior, and for social science research aimed at understanding human responses to a changing environmen

Not all adversarial examples require a complex defense : identifying over-optimized adversarial examples with IQR-based logit thresholding

Detecting adversarial examples currently stands as one of the biggest challenges in the field of deep learning. Adversarial attacks, which produce adversarial examples, increase the prediction likelihood of a target class for a particular data point. During this process, the adversarial example can be further optimized, even when it has already been wrongly classified with 100% confidence, thus making the adversarial example even more difficult to detect. For this kind of adversarial examples, which we refer to as over-optimized adversarial examples, we discovered that the logits of the model provide solid clues on whether the data point at hand is adversarial or genuine. In this context, we first discuss the masking effect of the softmax function for the prediction made and explain why the logits of the model are more useful in detecting over-optimized adversarial examples. To identify this type of adversarial examples in practice, we propose a non-parametric and computationally efficient method which relies on interquartile range, with this method becoming more effective as the image resolution increases. We support our observations throughout the paper with detailed experiments for different datasets (MNIST, CIFAR-10, and ImageNet) and several architectures

Slime mould imitation of Belgian transport networks: redundancy, bio-essential motorways, and dissolution

Belgium is amongst few artificial countries, established on purpose, when Dutch and French speaking parts were joined in a single unit. This makes Belgium a particularly interesting testbed for studying bio-inspired techniques for simulation and analysis of vehicular transport networks. We imitate growth and formation of a transport network between major urban areas in Belgium using the acellular slime mould Physarum polycephalum. We represent the urban areas with the sources of nutrients. The slime mould spans the sources of nutrients with a network of protoplasmic tubes. The protoplasmic tubes represent the motorways. In an experimental laboratory analysis we compare the motorway network approximated by P. polycephalum and the man-made motorway network of Belgium. We evaluate the efficiency of the slime mould network and the motorway network using proximity graphs