A model and framework for reliable build systems

Reliable and fast builds are essential for rapid turnaround during development and testing. Popular existing build systems rely on correct manual specification of build dependencies, which can lead to invalid build outputs and nondeterminism. We outline the challenges of developing reliable build systems and explore the design space for their implementation, with a focus on non-distributed, incremental, parallel build systems. We define a general model for resources accessed by build tasks and show its correspondence to the implementation technique of minimum information libraries, APIs that return no information that the application doesn't plan to use. We also summarize preliminary experimental results from several prototype build managers

The Living Body of the Lord: E.B. Pusey’s ‘Types and Prophecies of the Old Testament’

In his ‘Lectures on Types and Prophecy’ (1836-7), E. B. Pusey urges the recovery of a patristic and ‘Apostolic’ approach to the interpretation of the Old Testament. This thesis will argue that for Pusey finding types and ‘typical’ prophecies of Christ and his Church in the whole of the Old Testament is not an exegetical curiosity or option, but rather a necessary expression of doctrine and spiritual discipline. For Pusey, the unwillingness of interpreters guided by the apologetic and evidentialist approach to theology in his day to follow the Fathers’ example manifests important theological differences. He advocates both the recovery of patristic exegesis and the theological vision in which it makes sense. ‘Every thing is a type’, in the books of God’s works and words, because all created things bear the impress of their creator. Moreover, all types or images, in Scripture, in nature, and in the human soul, seek a fulfilment in a salvific return to the Trinity in Unity. Drawing on both patristic and Romantic sources, Pusey describes knowledge as a form of participation in the divine life in opposition to the rationalistic and procedural presuppositions he finds implicit in the apologetic approach. For Pusey, epistemology must be treated alongside sanctification and typology reflects Christology; a sacramental or ‘typical’ reading of prophecy transforms people made in the image of God to become more like God and hence able to know God and to read with understanding. Articulating these ideas was a project which occupied Pusey and his Tractarian colleagues during the most creative years of the Oxford Movement. While in many ways they gave voice to important High Church ideals, the puzzled response which greeted this part of their work reveals its radicalism and suggests possibilities for the contemporary search for the re-integration of theology and spirituality

A magnetically isolated gate driver for high-speed voltage sharing in series-connected MOSFETs

A scalable resonant gate drive circuit is described, suitable for driving series-connected MOSFETs in high-voltage, high-speed inverter applications for resistive and capacitive loads. Galvanic isolation is provided by a loop of high voltage wire, which also serves as the resonant inductor in the circuit. Fast dynamic voltage sharing is achieved by delivering equal current to each gate. A prototype is built and tested, demonstrating a 75ns switching time at 5kV using 900V MOSFETs

Video Camera Identification from Sensor Pattern Noise with a Constrained ConvNet

The identification of source cameras from videos, though it is a highly relevant forensic analysis topic, has been studied much less than its counterpart that uses images. In this work we propose a method to identify the source camera of a video based on camera specific noise patterns that we extract from video frames. For the extraction of noise pattern features, we propose an extended version of a constrained convolutional layer capable of processing color inputs. Our system is designed to classify individual video frames which are in turn combined by a majority vote to identify the source camera. We evaluated this approach on the benchmark VISION data set consisting of 1539 videos from 28 different cameras. To the best of our knowledge, this is the first work that addresses the challenge of video camera identification on a device level. The experiments show that our approach is very promising, achieving up to 93.1% accuracy while being robust to the WhatsApp and YouTube compression techniques. This work is part of the EU-funded project 4NSEEK focused on forensics against child sexual abuse.Comment: Paper Accepted in - 10th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2021

Source Camera Device Identification from Videos

Source camera identification is an important and challenging problem in digital image forensics. The clues of the device used to capture the digital media are very useful for Law Enforcement Agencies (LEAs), especially to help them collect more intelligence in digital forensics. In our work, we focus on identifying the source camera device based on digital videos using deep learning methods. In particular, we evaluate deep learning models with increasing levels of complexity for source camera identification and show that with such sophistication the scene-suppression techniques do not aid in model performance. In addition, we mention several common machine learning strategies that are counter-productive in achieving a high accuracy for camera identification. We conduct systematic experiments using 28 devices from the VISION data set and evaluate the model performance on various video scenarios—flat (i.e., homogeneous), indoor, and outdoor and evaluate the impact on classification accuracy when the videos are shared via social media platforms such as YouTube and WhatsApp. Unlike traditional PRNU-noise (Photo Response Non-Uniform)-based methods which require flat frames to estimate camera reference pattern noise, the proposed method has no such constraint and we achieve an accuracy of $$72.75 \pm 1.1 \%$$on the benchmark VISION data set. Furthermore, we also achieve state-of-the-art accuracy of $$71.75\%$$on the QUFVD data set in identifying 20 camera devices. These two results are the best ever reported on the VISION and QUFVD data sets. Finally, we demonstrate the runtime efficiency of the proposed approach and its advantages to LEAs

The Dark Internet: Without Darkness There is No Light

What is the Bright Internet? One way to define ‘bright’ is to explore darkness. The purpose of this panel is to clarify what is meant by the ‘Bright Internet’ by presenting the contrast of the ‘Dark Internet’ and the dark web. The panelists, all of whom have expertise in the dark side of Internet and information technology use, will discuss deception, fraud, phishing, terrorism, and the dark web