The Development of Dunfermline Abbey as a royal cult centre c.1070-c.1420

This thesis examines the development the cult of St Margaret at Dunfermline as a royal cult from 1070, the moment when St Margaret married King Malcolm III at Dunfermline, to 1420, the year of the burial of Robert duke of Albany who was the last royal member to be buried at Dunfermline. Scholars have focused on the life of St Margaret and her reputation or achievement from the biographical, institutional and hagiographical point of view. Although recent historians have considered St Margaret as a royal saint and Dunfermline as a royal mausoleum, they have approached this subject with relatively simple patterns, compared to the studies of the cults of European royal saints and their centres, in particular, those of English and French Kingdoms which influenced Scottish royalty. Just as other European royal cults such as the cults at Westminster and St-Denis have been researched from the point of view of several aspects, so the royal cult at Dunfermline can be approached in many ways. Therefore, this thesis will examine the development of Dunfermline Abbey as a royal cult centre through studying the abbey and the cult of St Margaret from the point of view of miracles and pilgrimage, lay patronage, and liturgical and devotional space. The examination of St Margaret’s miracles stories and pilgrimage to Dunfermline contribute to understanding these stories in the context of the development of the cult. The study of lay patronage explains the significance of royal favour and non-royal patrons in relation to the development of the cult, and how and why the royal cult developed and declined, and how the monks of Dunfermline promoted or sustained the cult of the saint. Lastly, the research of the liturgical and devotional space provides an explanation of the change of liturgical space from the point of view of the development of the cult

Cooperative Membership and Community Engagement: Findings from a Latin American Survey

Cooperatives as organization have mainly been explored in the field of business and management due to their operation in the business sector, and studies of nonprofit organizations have given little attention to them. Consequently, cooperatives studies have tended to examine economic outcomes, such as productivity and job security, comparing them to conventional business firms. Nevertheless, cooperatives are membership associations and have organizational characteristics in common with other types of voluntary associations. Furthermore, one explicit organizational principle of cooperatives is concern for community, and their contributions to the community have been covered frequently by media. Therefore, it is imperative to examine cooperative members’ community engagement, and compare it to other types of association members. Using a national sample of Venezuelans, the relationships between association memberships and community involvement were compared across different types of associations. The results showed that cooperative members had a higher likelihood of being involved in community matters than those from other types of associations. Although the Venezuelan cooperatives have received vast support from the Chavez government for community development, this result can have an implication on the cooperatives’ organizational identity as those who provide members with resources necessary for civic engagement beyond the organizations

Characteristics of Non-Residential (Commuter) Colleges and Factors Affecting Bachelor’s Degree Completion in a Non-Residential College

Despite the abundant amount of studies about bachelor’s degree completion in higher education, little research paid attention to the characteristics of students attending non-residential institutions, given that this type of college accounts for approximately half of all the higher education institutions in the United States. Using student records and survey data, this study compares the student characteristics between residential and non-residential colleges at the institutional level. In addition, using a primarily non-residential college’s survey and student record data, this research explores diverse factors that affect students’ academic and social integration and their graduation at the individual level. Findings include that non-residential colleges tend to have a high proportion of first-generation and transfer students working off campus, and students attending this type of school are more likely to receive financial aid and less likely to participate in student organizations, compared to their counterparts attending residential colleges. At the individual level, academic integration in college, high school GPA, and financial aid are strong predictors for time to graduation of students in a non-residential college. Moreover, having a child, responsibility for siblings, housing issues, and a lack of direction in academic journey are found to be obstacles to degree completion through narratives. Directions for future studies are suggested to bring more attention to non-residential institutions

Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning

Recently, Doppler radar‐based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar‐based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of various foot gestures based on Doppler radar and a deep learning model. In this paper, we propose a method of foot gesture recognition using a new high‐compression radar signature image and deep learning. By means of a deep learning AlexNet model, a new high‐compression radar signature is created by extracting dominant features via Singular Value Decomposition (SVD) processing; four different foot gestures including kicking, swinging, sliding, and tapping are recognized. Instead of using an original radar signature, the proposed method improves the memory efficiency required for deep learning training by using a high-compression radar signature. Original and reconstructed radar images with high compression values of 90%, 95%, and 99% were applied for the deep learning AlexNet model. As experimental results, movements of all four different foot gestures and of a rolling baseball were recognized with an accuracy of approximately 98.64%. In the future, due to the radar’s inherent robustness to the surrounding environment, this foot gesture recognition sensor using Doppler radar and deep learning will be widely useful in future automotive and smart home industry fields. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).1

Extrapolation-RELAX Estimator Based on Spectrum Partitioning for DOA Estimation of FMCW Radar

This paper proposes an extrapolation-RELAX estimator based on spectrum partitioning (SP) for the direction of arrival (DOA) estimation of frequency-modulated continuous-wave (FMCW) radar. The FMCW radar employs fast Fourier transform (FFT)-based digital beamforming (DBF) for the DOA estimation owing to its low complexity and easy implementation. However, the DBF algorithm has a disadvantage of low angle resolution. To improve the angle resolution, super-resolution algorithms such as multiple signal classification (MUSIC) and estimation of signal parameters via rotational invariance techniques (ESPRIT) are proposed. However, these algorithms require the high signal-to-noise ratio (SNR) to meet the required performance. To overcome this drawback of super-resolution algorithms, the SP-based extrapolation method has been proposed. However, this algorithm still has the problem that the resolution performance degrades owing to the insufficient number of actual antenna arrays. To solve this problem, we propose the SP-based extrapolation-RELAX algorithm for DOA estimation of FMCW radar. Through extrapolation, the proposed structure solves the problem of insufficient number of arrays, resulting in high reliability of SP results. When the extrapolation algorithm is used to generate the input signal of the RELAX algorithm, the RELAX method improves the performance of the DOA estimation. To confirm the effectiveness of the proposed estimation, we compare the Monte Carlo simulation and root-mean-square error results of the proposed and conventional algorithms. To verify the performance of the proposed algorithm in practical conditions, experiments were performed using the FMCW radar module within a chamber and in an indoor environment.1

Low-Complexity MUSIC-Based Direction-of-Arrival Detection Algorithm for Frequency-Modulated Continuous-Wave Vital Radar

This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30◦, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.1

An iteration free backward semi-Lagrangian scheme for guiding center problems

In this paper, we develop an iteration free backward semi-Lagrangian method for nonlinear guiding center models. We apply the fourth-order central difference scheme for the Poisson equation and employ the local cubic interpolation for the spatial discretization. A key problem in the time discretization is to find the characteristic curve arriving at each grid point which is the solution of a system of highly nonlinear ODEs with a self-consistency imposed by the Poisson equation. The proposed method is based on the error correction method recently developed by the authors. For the error correction method, we introduce a modified Euler's polygon and solve the induced asymptotically linear differential equation with the midpoint quadrature rule to get the error correction term. We prove that the proposed iteration free method has convergence order at least 3 in space and 2 in time in the sense of the L2-norm. In particular, it is shown that the proposed method has a good performance in computational cost together with better conservation properties in mass, the total kinetic energy, and the enstrophy compared to the conventional second-order methods. Numerical test results are presented to support the theoretical analysis and discuss the properties of the newly proposed scheme.close0

Low-complexity joint range and Doppler FMCW radar algorithm based on number of targets

A low-complexity joint range and Doppler frequency-modulated continuous wave (FMCW) radar algorithm based on the number of targets is proposed in this paper. This paper introduces two low-complexity FMCW radar algorithms, that is, region of interest (ROI)-based and partial discrete Fourier transform (DFT)-based algorithms. We find the low-complexity condition of each algorithm by analyzing the complexity of these algorithms. From this analysis, it is found that the number of targets is an important factor in determining complexity. Based on this result, the proposed algorithm selects a low-complexity algorithm between two algorithms depending the estimated number of targets and thus achieves lower complexity compared two low-complexity algorithms introduced. The experimental results using real FMCW radar systems show that the proposed algorithm works well in a real environment. Moreover, central process unit time and count of float pointing are shown as a measure of complexity. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.1

A Low Complexity Based Spectrum Partitioning - ESPRIT for Noncontact Vital Radar

This paper proposes a low complexity based spectrum partitioning (SP)-ESPRIT for noncontact vital radar as a diagnostic tool for sleep apnea and other respiratory disorders. In the vital radar, the high precision and accuracy of the Doppler frequency is needed for the heart and respiration rates of the human body. However, because of smearing problems caused by limited data length and low SNR environments of the heartbeat signal, conventional fast Fourier transform (FFT) suffers from decreased performance of the Doppler frequency. To improve the parameters of radar measurement data such as the precision and accuracy, many super-resolution based algorithms, e.g., the SP method, have been proposed. Nevertheless, in order to apply the SP based super resolution algorithm into vital radar systems, a number of practical issues related to increased computational load should be addressed. Especially, compared with the conventional super-resolution algorithm such as estimation of signal parameters via rotational invariance techniques (ESPRIT), the complexity of the SP-ESPRIT is increased dramatically by performing multiple algorithms. Therefore, in this paper, we propose a scheme that is modified from the conventional SP-ESPRIT technique with the aim of reducing the computational load for vital detection. From Monte-Carlo simulation results with a SNR of 6 dB, the root mean square error (RMSE) of the proposed method is about 11 times lower than that of the conventional ESPRIT method.1

A new Transmitted-Rererence Automotive UWB Radar using Unequaled Amplitude

This paper analyzes the detection performance of new Transmitted-Reference (TR) automotive UWB radar using unequaled amplitude for vehicles. To improve the detection performance of a traditional TR-UWB system, the amplitude of a reference pulse can be changed to increase the energy-to-noise ratio. Finally, the characteristics of the proposed TR-UWB radar are evaluated by simulation. And the performances of the proposed radar are compared with a coherent matched filter and a traditional TR-UWB system. For special case when SNR=3dB and =6, we can assert that the detection probability of the proposed TR receiver is approximately a 19% increase compared with that of the conventional TR receiver when the probability of false alarm is 0.5.1