Investigating combinations of feature extraction and classification for improved image-based multimodal biometric systems at the feature level

Multimodal biometrics has become a popular means of overcoming the limitations of unimodal biometric systems. However, the rich information particular to the feature level is of a complex nature and leveraging its potential without overfitting a classifier is not well studied. This research investigates feature-classifier combinations on the fingerprint, face, palmprint, and iris modalities to effectively fuse their feature vectors for a complementary result. The effects of different feature-classifier combinations are thus isolated to identify novel or improved algorithms. A new face segmentation algorithm is shown to increase consistency in nominal and extreme scenarios. Moreover, two novel feature extraction techniques demonstrate better adaptation to dynamic lighting conditions, while reducing feature dimensionality to the benefit of classifiers. A comprehensive set of unimodal experiments are carried out to evaluate both verification and identification performance on a variety of datasets using four classifiers, namely Eigen, Fisher, Local Binary Pattern Histogram and linear Support Vector Machine on various feature extraction methods. The recognition performance of the proposed algorithms are shown to outperform the vast majority of related studies, when using the same dataset under the same test conditions. In the unimodal comparisons presented, the proposed approaches outperform existing systems even when given a handicap such as fewer training samples or data with a greater number of classes. A separate comprehensive set of experiments on feature fusion show that combining modality data provides a substantial increase in accuracy, with only a few exceptions that occur when differences in the image data quality of two modalities are substantial. However, when two poor quality datasets are fused, noticeable gains in recognition performance are realized when using the novel feature extraction approach. Finally, feature-fusion guidelines are proposed to provide the necessary insight to leverage the rich information effectively when fusing multiple biometric modalities at the feature level. These guidelines serve as the foundation to better understand and construct biometric systems that are effective in a variety of applications

Faster upper body pose recognition and estimation using compute unified device architecture

>Magister Scientiae - MScThe SASL project is in the process of developing a machine translation system that can translate fully-fledged phrases between SASL and English in real-time. To-date, several systems have been developed by the project focusing on facial expression, hand shape, hand motion, hand orientation and hand location recognition and estimation. Achmed developed a highly accurate upper body pose recognition and estimation system. The system is capable of recognizing and estimating the location of the arms from a twodimensional video captured from a monocular view at an accuracy of 88%. The system operates at well below real-time speeds. This research aims to investigate the use of optimizations and parallel processing techniques using the CUDA framework on Achmed’s algorithm to achieve real-time upper body pose recognition and estimation. A detailed analysis of Achmed’s algorithm identified potential improvements to the algorithm. Are- implementation of Achmed’s algorithm on the CUDA framework, coupled with these improvements culminated in an enhanced upper body pose recognition and estimation system that operates in real-time with an increased accuracy

Compete to Learn: Toward Cybersecurity as a Sport

To support the workforce gap of skilled cybersecurity professionals, gamified pedagogical approaches for teaching cybersecurity have exponentially grown over the last two decades. During this same period, e-sports developed into a multi-billion dollar industry and became a staple on college campuses. In this work, we explore the opportunity to integrate e-sports and gamified cybersecurity approaches into the inaugural US Cyber Games Team. During this tenure, we learned many lessons about recruiting, assessing, and training cybersecurity teams. We share our approach, materials, and lessons learned to serve as a model for fielding amateur cybersecurity teams for future competition

Tall Buildings and Their Foundations: Three Examples

The influence of foundations on the design and behavior of tall buildings is explored by examining two built towers: Burj Khalifa, Trump International Hotel and Tower, and the partially built Plaza Rakyat, a 77 story tower in Malaysia. The paper reviews how foundation conditions were considered in the design of the buildings, and how the foundations were anticipated to influence the behavior of the towers

Additive Manufacturing of Metal Bandpass Filters for Future Radar Receivers

Selective laser melting (SLM) is a powder-bed fusion (PBF) process that bonds successive layers of powder with a laser to create components directly from computer-aided design (CAD) files. The additive nature of the SLM process in addition to the use of fine powders facilitates the construction of complex geometries, which has captured the attention of those involved in the design of bandpass filters for radar applications. However, a significant drawback of SLM is its difficulty in fabricating parts with overhangs necessitating the use of support structures, which, if not removed, can greatly impact the performance of bandpass filters. Therefore, in this study bandpass filters are manufactured in two stages with 304L stainless steel where each builds only a portion of the part to improve the reliability in manufacturing the overhangs present. The results show that the versatility of SLM can produce difficult-to-manufacture bandpass filters with high dimensional accuracy

Structural invariance of General Behavior Inventory (GBI) scores in Black and White young adults.

In the United States, Black and White individuals show discrepant rates of diagnosis of bipolar disorder versus schizophrenia and antisocial personality disorder, as well as disparate access to and utilization of treatment for these disorders (e.g., Alegria, Chatterji et al., 2008; Chrishon et al., 2012). Such diagnostic discrepancies might stem from racially-related cognitive biases in clinical judgment or from racial biases in measurements of bipolar disorder. The General Behavior Inventory (GBI) is among the most well-validated and widely used measures of bipolar mood symptoms, but the psychometric properties of the GBI have been examined primarily in predominantly White samples. This study used multi-group confirmatory factor analyses (CFA) to examine the invariance of GBI scores across racial groups with a non-clinical sample. Fit was acceptable for tests of configural invariance, equal factor loadings, and equal intercepts, but not invariance of residuals. Findings indicate that GBI scores provide functionally invariant measurement of mood symptoms in both Black and White samples. The use of GBI scores may contribute consistent information to clinical assessments and could potentially reduce diagnostic discrepancies and associated differences in access to and utilization of mental health services

Dietary intakes differ by body composition goals: An observational study of professional rugby union players in New Zealand

Preseason in rugby union is a period of intensive training where players undergo conditioning to prepare for the competitive season. In some cases, this includes modifying body composition through weight gain or fat loss. This study aimed to describe the macronutrient intakes of professional rugby union players during pre-season training. It was hypothesized that players required to gain weight would have a higher energy, carbohydrate and protein intake compared to those needing to lose weight. Twenty-three professional rugby players completed 3 days of dietary assessment and their sum of eight skinfolds were assessed. Players were divided into three groups by the team coaches and medical staff: weight gain, weight maintain and weight loss. Mean energy intakes were 3,875 ± 907 kcal·d⁻¹ (15,965 ± 3,737 kJ·d⁻¹) (weight gain 4,532 ± 804 kcal·d⁻¹; weight maintain 3,825 ± 803 kcal·d⁻¹; weight loss 3,066 ± 407 kcal·d⁻¹) and carbohydrate intakes were 3.7 ± 1.2 g·kg⁻¹·d⁻¹ (weight gain 4.8 ± 0.9 g.kg⁻¹·d⁻¹; weight maintain 2.8 ± 0.7 g·kg⁻¹·d⁻¹; weight loss 2. 6 ± 0.7 g·kg⁻¹·d⁻¹). The energy and carbohydrate intakes are similar to published intakes among rugby union players. There were significant differences in energy intake and the percent of energy from protein between the weight gain and the weight loss group

Body image amongst elite rugby union players.

There is limited information on the risk of eating disorders and body image of elite male athletes. However, research suggests there are some athletes who have poor body image and they may be at increased risk of developing eating disorders. Therefore, the current study investigated risk of eating disorders, body image, and the relationship with age, in elite rugby union players during their pre-season training period. This cross-sectional study was undertaken at the start of the pre-season amongst elite rugby union players in New Zealand. Twenty-six professional rugby union players completed a 49-item questionnaire on body image and disordered eating. A ‘body image score’ was calculated from questionnaire subscales including ‘drive for thinness’, ‘bulimia’ and ‘body dissatisfaction’, with total scores above twenty indicative of poor body image. Body image scores varied from 8-39 out of a possible 0-100. Disordered eating behaviours were reported, including binge eating at least once a week (15%, n=4/26), pathogenic weight control use (4%, n=1/26) and avoidance of certain foods (77%, n=20/26). There was a statistically significant inverse association between the bulimia subscale and age (P = 0.034). At the start of the pre-season training period, many elite rugby union players experience disturbances in body image. The prevalence of disordered eating behaviours is of concern, and needs to be minimised due to the negative impact on health and performance. A focus on assessment and education of younger male rugby players may be required in order to reduce disordered eating patterns

Collective intuition : implications for improved decision making and organizational learning

This article establishes the foundation for research on collective intuition through a study of decision making and organizational learning processes in police senior management teams. We conceptualize collective intuition as independently formed judgement based on domain-specific knowledge, experience and cognitive ability, shared and interpreted collectively. We contribute to intuition research, which has tended to focus its attention at the individual level, by studying intuition collectively in team settings. From a dual-process perspective, we investigate how expert intuition and deliberation affect decision making and learning at various levels of the organization. Furthermore, we contribute to organizational learning research by offering an empirically derived elaboration of the foundational 4I framework, identifying additional ‘feed-forward’ and ‘feedback’ loop processes, and thereby providing a more complete account of this organizational learning model. Bridging a variety of relevant but previously unconnected literatures via our focal concept of collective intuition, our research provides a foundation for future studies of this vitally important but under-researched organizational phenomenon. We offer theoretical and practical implications whereby expert intuitions can be developed and leveraged collectively as valuable sources of organizational knowledge and learning, and contribute to improved decision making in organizations.PostprintPeer reviewe