Model Checking Based Approach for Compliance Checking

Process mining is the set of techniques to retrieve a process model starting from available logging data. The discovered process model has to be analyzed to verify it respects the defined properties, i.e., the so-called compliance checking. Our aim is to use a model checking based approach to verify compliance. First, we propose an integrated-tool approach using existing tools as ProM (a framework supporting process mining techniques) and CADP (a formal verification environment). More precisely, the execution traces from a software system are extracted. Then, using the "Mine Transition System" plugin in ProM, we obtain a labelled transition system, that can be easily used to verify formal properties trough CADP. However, this choice presents the "state explosion" problem, i.e., models discovered through the classical process mining techniques tend to be large and complex. In order to solve this problem, another custom-made approach is shown, which accomplishes a pre- processing on the traces to obtain abstract traces, where abstraction is based on the set of temporal logic formulae specifying the system properties. Then, from the set of abstracted traces, we discover a system described in Lotos, a process algebra specification language; in this way we do not build an operational model for the system, but we produce only a language description from which a model checking environment will automatically obtain the reduced corresponding transition system. Real systems have been used as case studies to evaluate the proposed methodologies

Wind Tunnel Designs and Their Diverse Engineering Applications

This book is intended to be a valuable addition to students, engineers, scientists, industrialists, consultants and others providing greater insight into wind tunnel designs and their enormous research potential. It is a compilation of works from world experts on subsonic and supersonic wind tunnel designs, applicable to a diverse range of disciplines. The book is organised in two sections. The first section comprises of three chapters on various aspects of stationary and portable subsonic wind tunnel designs, followed by one chapter on supersonic wind tunnel and the final chapter discusses a method to address unsteadiness effects of fan blade rotation. The second section contains four chapters regarding wind tunnel applications across a multitude of engineering fields including civil, mechanical, chemical and environmental engineering

Fundamental Awareness: A Framework for Integrating Science, Philosophy and Metaphysics

The ontologic framework of Fundamental Awareness proposed here assumes that non-dual Awareness is foundational to the universe, not arising from the interactions or structures of higher level phenomena. The framework allows comparison and integration of views from the three investigative domains concerned with understanding the nature of consciousness: science, philosophy, and metaphysics. In this framework, Awareness is the underlying reality, not reducible to anything else. Awareness and existence are the same. As such, the universe is non-material, self-organizing throughout, a holarchy of complementary, process driven, recursive interactions. The universe is both its own first observer and subject. Considering the world to be non-material and comprised, a priori, of Awareness is to privilege information over materiality, action over agency and to understand that qualia are not a “hard problem,” but the foundational elements of all existence. These views fully reflect main stream Western philosophical traditions, insights from culturally diverse contemplative and mystical traditions, and are in keeping with current scientific thinking, expressible mathematically

Jewish messianism culminating in the rise and dissemination of Sabbatianism - an excursion into messianic Kabbalah and its theological enterprises

Dissertation (MTh (Old Testament Studies))--University of Pretoria 2022.An examination of Jewish messianism and mysticism from 500 BCE up to and including the seventeenth-century advent of Shabbatai Tzvi and the Sabbatian movement. The study shows that outbreaks of messianic fervour are usually preceded by some form of mysticism, and the more intense the mysticism the more intense the messianism. This is juxtaposed against the rationalist approach of Maimonides who developed the idea of a natural progression of humankind towards a messianic era without an apocalyptic or supernatural component.Old Testament StudiesMTh (Old Testament Studies)Unrestricte

Daily Eastern News: August 05, 1986

https://thekeep.eiu.edu/den_1986_aug/1000/thumbnail.jp

Daily Eastern News: August 05, 1986

https://thekeep.eiu.edu/den_1986_aug/1000/thumbnail.jp

Constructing networks of quantum channels for state preparation

Entangled possibly mixed states are an essential resource for quantum computation, communication, metrology, and the simulation of many-body systems. It is important to develop and improve preparation protocols for such states. One possible way to prepare states of interest is to design an open system that evolves only towards the desired states. A Markovian evolution of a quantum system can be generally described by a Lindbladian. Tensor networks provide a framework to construct physically relevant entangled states. In particular, matrix product density operators (MPDOs) form an important variational class of states. MPDOs generalize matrix product states to mixed states, can represent thermal states of local one-dimensional Hamiltonians at sufficiently large temperatures, describe systems that satisfy the area law of entanglement, and form the basis of powerful numerical methods. In this work we develop an algorithm that determines for a given linear subspace of MPDOs whether this subspace can be the stable space of some frustration free k-local Lindbladian and, if so, outputs an appropriate Lindbladian. We proceed by using machine learning with networks of quantum channels, also known as quantum neural networks (QNNs), to train denoising post-processing devices for quantum sources. First, we show that QNNs can be trained on imperfect devices even when part of the training data is corrupted. Second, we show that QNNs can be trained to extrapolate quantum states to, e.g., lower temperatures. Third, we show how to denoise quantum states in an unsupervised manner. We develop a novel quantum autoencoder that successfully denoises Greenberger-Horne-Zeilinger, W, Dicke, and cluster states subject to spin-flip, dephasing errors, and random unitary noise. Finally, we develop recurrent QNNs (RQNNs) for denoising that requires memory, such as combating drifts. RQNNs can be thought of as matrix product quantum channels with a quantum algorithm for training and are closely related to MPDOs. The proposed preparation and denoising protocols can be beneficial for various emergent quantum technologies and are within reach of present-day experiments