Flipping a Hardware Design Class: An Encouragement of Active Learning. Should It Continue?

In this paper we aim to present the lessons learned from flipping the classroom of an entry-level graduate course on digital hardware design. This digital hardware design course uses hardware description languages (HDLs) for programming and requires students to learn relevant concepts and methodologies to successfully design, simulate, synthesize, and verify digital circuits created using hands-on projects and in-class activities. In addition, students in the digital hardware design class get exposure and gain familiarity with an industrial design suite to enhance their knowledge of real-life design cycles. Typically, students struggle with provided in-class activities, assignments, and projects in any digital hardware design class; even those with prior experience in the field may still struggle due to the complex nature of HDLs. The effort required for large digital designs is often overwhelming and leads to time commitments of several hours outside of the classroom to debug design issues without help from the instructor or teaching assistant(s). This extra time spent shows that help through office hours and recitation sessions is definitely needed to help prepare students. This work summarizes our explored implications of taking a previously all-lecture-based classroom environment, with traditional teaching methods, and changing to an active-learning environment using multi-modal teaching techniques. In this new teaching environment, students were directed to watch and follow along with short videos produced with the goal of providing instructional and pre-programmed digital hardware design exercises before coming into class. The pre-programmed exercises help change the classroom environment into a center for active-learning through means of creative activities. Students in the active-learning environment are further urged to work in teams on the provided activities to reinforce key concepts and operational ideologies. From the students’ perspectives, our preliminary results show that less time was spent working alone on assignments and projects due to the new active-learning environment, pre-class preparation, and in-class group-work activities. The new active-learning environment included online preview of lecture notes, constant interaction between the instructor, teaching assistant(s), and students, and an increased number of in-class hands-on activities. From an instructional perspective, regardless of drawbacks, the new active-learning environment and teaching techniques allowed for the instructor to reinforce and delve deeper into course content while allowing students to work efficiently with new material. The results from the change to an active learning environment on students’ work on assignments and projects during non class-times is: adequate preparation, easy reference to related materials, and an overall wealth of knowledge in the field of digital hardware design

Teaching the Hardware Implementation of Cybesecurity Encryption Algorithms on FPGA Using Hands-On Projects

Cybersecurity is an important concept in today’s age of information and is of major interest to keep information secure, helping to protect sensitive information in the presence of untrusted third-parties. This has presented the need for an implemented hardware variant of secure algorithms with small footprint to help add protection while reducing processing time/overhead on a standard processor. In this work we present two hands-on projects that are designed specifically to teach these two concepts using project-based learning techniques in an innovative cooperative learning environment. The learning environment served to combine both student-peer learning and jigsaw strategies. The technical contents of the first project teach students the process and methodologies of designing and testing the hardware implementation of a block cipher encryption, the Advanced Encryption Standard, on a field-programmable gate array. The second project builds on the first by introducing the hardware implementation of hash message authentication codes through the Whirlpool hash function in three different operating modes. The objective of this work is to present an innovative teaching environment for these hands-on encryption algorithm-based projects using cooperative learning rather than a traditional mode of lecturing with given homework assignments. This environment encouraged students to think thoroughly, out-of-the-box, gain problem-solving skills, and improve their communication of technical concepts to peers through the delivery of student-led lectures. The assessment of student learning is accomplished by a mixture of presentations with peer evaluations, instructor evaluations, and thorough grading of project reports. End-of-course evaluations were positive regarding the learning environment and technical skills gained by students. For this work one assigned hands-on project for students working in groups resulted in unique per-group implementations, where in the second project, this led to different project perspectives and additions beyond a standard assigned project, enhanced by student-peer teaching. Students effectively learned and comprehended many different implementations of a widely used encryption and authentication algorithm via our modified teaching techniques

Negativity vs Entropy in Entanglement Witnessing

In this work, we prove that while all measures of mixedness can be used to witness entanglement, no measure of mixedness is more sensitive than the negativity of the partial transpose. However, computing either the negativity or differences between von Neumann entropies to witness entanglement requires complete knowledge of the joint density matrix (and is therefore not practical at high dimension). In light of this, we examine joint vs marginal purities as a witness of entanglement, (which can be obtained directly through interference measurements) and find that comparing purities is actually more sensitive at witnessing entanglement than using von Neumann entropies while also providing tight upper and lower bounds to it in the high-entanglement limit.Comment: 4 pages, 1 figur

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Towards Hybrid Quantum-Classical Ciphersuite Primitives

With the dawn of quantum computing in scale, current secure classical primitives are at risk. Protocols with immediate risk of breach are those built on the advanced encryption standard (AES) and Rivest-Shamir-Adleman (RSA) algorithms. To secure classical data against a quantum adversary, a secure communications ciphersuite must be developed. The ciphersuite developed in this work contains components that do not necessarily rely on quantum key distribution (QKD), due to recent insecurities found when a QKD-based protocol is faced with a quantum eavesdropper. A set of quantum-classical ciphersuite primitives were developed using less common mathematical methods where a quantum adversary will take a non-deterministic polynomial-time to find a solution, but still easy enough for communicating classical computers to evaluate. The methods utilized for this work were created from random walks, lattices, symplectic mappings, combinatorics, and others. The hardware methods developed in this work rely on either classical laser-light, or entangled quantum states, with matching optimization developed from global optimization theories. The result of this work is the creation of non-QKD hybrid quantum-classical set of secure ciphersuite primitives, built and expanded from existing classical and post-quantum security schemes, for both classical and quantum information. In the tight integration between quantum and classical computers, the security of classical systems with quantum interaction is essential

Utilizing a Fully Optical and Reconfigurable PUF as a Quantum Authentication Mechanism

In this work, the novel usage of a physically unclonable function composed of a network of Mach-Zehnder interferometers for authentication tasks is described. The physically unclonable function hardware is completely reconfigurable, allowing for a large number of seemingly independent devices to be utilized, thus imitating a large array of single-response physically unclonable functions. It is proposed that any reconfigurable array of Mach-Zehnder interferometers can be used as an authentication mechanism, not only for physical objects, but for information transmitted both classically and quantumly. The proposed use-case for a fully-optical physically unclonable function, designed with reconfigurable hardware, is to authenticate messages between a trusted and possibly untrusted party; verifying that the messages received are generated by the holder of the authentic device