H4VDM: H.264 Video Device Matching

Methods that can determine if two given video sequences are captured by the same device (e.g., mobile telephone or digital camera) can be used in many forensics tasks. In this paper we refer to this as "video device matching". In open-set video forensics scenarios it is easier to determine if two video sequences were captured with the same device than identifying the specific device. In this paper, we propose a technique for open-set video device matching. Given two H.264 compressed video sequences, our method can determine if they are captured by the same device, even if our method has never encountered the device in training. We denote our proposed technique as H.264 Video Device Matching (H4VDM). H4VDM uses H.264 compression information extracted from video sequences to make decisions. It is more robust against artifacts that alter camera sensor fingerprints, and it can be used to analyze relatively small fragments of the H.264 sequence. We trained and tested our method on a publicly available video forensics dataset consisting of 35 devices, where our proposed method demonstrated good performance

Detecting cow behaviours associated with parturition using computer vision

Monitoring of dairy cows and their calf during parturition is essential in determining if there are any associated problems for mother and offspring. This is a critical period in the productive life of the mother and offspring. A difficult and assisted calving can impact on the subsequent milk production, health and fertility of a cow, and its potential survival. Furthermore, an alert to the need for any assistance would enhance animal and stockperson wellbeing. Manual monitoring of animal behaviour from images has been used for decades, but is very labour intensive. Recent technological advances in the field of Computer Vision based on the technique of Deep Learning have emerged, which now makes automated monitoring of surveillance video feeds feasible. The benefits of using image analysis compared to other monitoring systems is that image analysis relies upon neither transponder attachments, nor invasive tools and may provide more information at a relatively low cost. Image analysis can also detect and track the calf, which is not possible using other monitoring methods. Using cameras to monitor animals is commonly used, however, automated detection of behaviours is new especially for livestock. Using the latest state-of-the-art techniques in Computer Vision, and in particular the ground-breaking technique of Deep Learning, this thesis develops a vision-based model to detect the progress of parturition in dairy cows. A large-scale dataset of cow behaviour annotations was created, which included over 46 individual cow calvings and is approximately 690 hours of video footage with over 2.5k of video clips, each between 3-10 seconds. The model was trained on seven different behaviours, which included standing, walking, shuffle, lying, eating, drinking, and contractions while lying. The developed network correctly classified the seven behaviours with an accuracy of between 80 to 95%. The accuracy in predicting contractions while lying down was 83%, which in itself can be an early warning calving alert, as all cows start contractions one to two hours before giving birth. The performance of the model developed was also comparable to methods for human action classification using the Kinetics dataset

Micro/Nano Devices for Blood Analysis, Volume II

The development of micro- and nanodevices for blood analysis continues to be a growing interdisciplinary subject that demands the careful integration of different research fields. Following the success of the book “Micro/Nano Devices for Blood Analysis”, we invited more authors from the scientific community to participate in and submit their research for a second volume. Researchers from different areas and backgrounds cooperated actively and submitted high-quality research, focusing on the latest advances and challenges in micro- and nanodevices for diagnostics and blood analysis; micro- and nanofluidics; technologies for flow visualization and diagnosis; biochips, organ-on-a-chip and lab-on-a-chip devices; and their applications to research and industry

Measuring Behavior 2018 Conference Proceedings

These proceedings contain the papers presented at Measuring Behavior 2018, the 11th International Conference on Methods and Techniques in Behavioral Research. The conference was organised by Manchester Metropolitan University, in collaboration with Noldus Information Technology. The conference was held during June 5th – 8th, 2018 in Manchester, UK. Building on the format that has emerged from previous meetings, we hosted a fascinating program about a wide variety of methodological aspects of the behavioral sciences. We had scientific presentations scheduled into seven general oral sessions and fifteen symposia, which covered a topical spread from rodent to human behavior. We had fourteen demonstrations, in which academics and companies demonstrated their latest prototypes. The scientific program also contained three workshops, one tutorial and a number of scientific discussion sessions. We also had scientific tours of our facilities at Manchester Metropolitan Univeristy, and the nearby British Cycling Velodrome. We hope this proceedings caters for many of your interests and we look forward to seeing and hearing more of your contributions

Disrupting the Symbolic Hamlet: A Semiotic Reading

Even though the eruption of Shakespeare’s Hamlet in everyday performative situations, Verities, and the Variable theatrical performative world is common, understood, and accepted over the centuries, the reasons for its return are not fully explored. Deciphering the mechanisms through which it has survived provide a good model for sprouting the contemporary theater of Pakistan. An overview or ‘thinking’ of its semiotic renditions into variegated forms, without analysis based on discrimination, helps in focusing upon some of the essentials that enable the performance text to survive through times. My work involves one such analysis. The objective of this study was to examine two questions: first, why does Hamlet constantly return in the contemporary performance? Second, is there a similar text, character or situation, in Pakistan through which we can structure the performance art of the country? To examine these questions, I explored the literary and performance texts of Hamlet as well as the literary theory, especially Affect Theory and Performance Philosophy. This study displayed a connection between history, culture, affect, and audience. In fact, I could link the Traditional Punjabi Performers of ‘Vaar’ or folk ballads with the performers affected by the strong history and culture based affective field of Hamlet. However, I found Vaari performers relied upon their voice and history based oral narrative and not on the text. This recognition suggests that Pakistan can build upon the historically popular oral narratives to frame its theater. I found that writers steeped in history and cultures of the country have already made such attempts. In future, theater of Pakistan may focus on developing, disrupting and re-performing these narratives. This dissertation highlighted the re-birth of the ‘Vaari’ as the means of reviving performance art in Pakistan.Obwohl der Ausbruch von Shakespeares Hamlet in alltäglichen performativen Situationen, Verities und der variablen theatralisch-performativen Welt im Laufe der Jahrhunderte weit verbreitet ist, verstanden und akzeptiert wird, sind die Gründe für seine Rückkehr nicht vollständig erforscht. Die Entschlüsselung der Mechanismen, durch die es überlebt hat, bieten ein gutes Modell für die Entfaltung des zeitgenössischen pakistanischen Theaters. Eine Übersicht oder ein „Denken“ der semiotischen Darstellungen in verschiedenen Formen, ohne diskriminierende Analyse, hilft dabei sich auf einige der wesentlichen Aspekte zu konzentrieren, die dem Performance-Text das Überleben in den Zeiten ermöglichen. Meine Arbeit beinhaltet eine solche Analyse. Ziel dieser Studie war es, zwei Fragen zu untersuchen: Erstens, warum kehrt Hamlet ständig in die zeitgenössische Performance zurück? Und zweitens, gibt es in Pakistan einen ähnlichen Text, Charakter oder eine ähnliche Situation, durch die wir die Performance-Kunst des Landes strukturieren können? Um diese Fragen zu untersuchen, habe ich die literarischen und Performance-Texte von Hamlet sowie die literarische Theorie, insbesondere die Affekttheorie und die Performance-Philosophie, untersucht. Diese Studie zeigte einen Zusammenhang zwischen Geschichte, Kultur, Einfluss und Publikum. In der Tat könnte ich die traditionellen Punjabi-Darsteller von 'Vaar' mit den Darstellern aus Hamlet in verbindung bringen, die von der starken Geschichte und Kultur des affektiven Feldes von Hamlet betroffen sind. Ich fand jedoch, dass Vaari-Darsteller sich auf ihre Stimme und Geschichte stützten, basierend auf mündlichen Erzählungs und nicht auf den Text. Diese Erkenntis legt nahe, dass Pakistan auf den historisch populären mündlichen Erzählungen aufbauen kann, um sein Theater zu gestalten. Ich fand heraus, dass Schriftsteller, die mit der Geschichte und Kultur des Landes vertraut sind, bereits solche Versuche unternommen haben. In Zukunft kann sich das Theater in Pakistan darauf konzentrieren, diese Erzählungen weiter zu entwickeln, zu variieren und wiederzugeben. In dieser Dissertation wurde die Wiedergeburt des "Vaari" als Mittel zur Aktivierung der Performance-Kunst in Pakistan thematisiert

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings

A functional cortical network for sensorimotor sequence generation

The brain generates complex sequences of movements that can be flexibly reconfigured in real-time based on sensory feedback, but how this occurs is not fully understood. We developed a novel ‘sequence licking’ task in which mice directed their tongue to a target that moved through a series of locations. Mice could rapidly reconfigure the sequence online based on tactile feedback. Closed-loop optogenetics and electrophysiology revealed that tongue/jaw regions of somatosensory (S1TJ) and motor (M1TJ) cortex encoded and controlled tongue kinematics at the level of individual licks. Tongue premotor (anterolateral motor, ALM) cortex encoded intended tongue angle in a smooth manner that spanned individual licks and even whole sequences, and progress toward the reward that marked successful sequence execution. ALM activity regulated sequence initiation, but multiple cortical areas collectively controlled termination of licking. Our results define a functional cortical network for hierarchical control of sensory- and reward-guided orofacial sequence generation