An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Optimizing storage and memory systems for energy and performance

Electrical energy is an essential resource for the modern world. Unfortunately, its price has almost doubled in the last decade. Furthermore, energy production is also currently one of the primary sources of pollution. These concerns are becoming more important in data-centers. As more computational power is required to serve hundreds of millions of users, bigger data-centers are becoming necessary. This results in higher electrical energy consumption. Of all the energy used in data-centers, including power distribution units, lights, and cooling, computer hardware consumes as much as 80%. Consequently, there is opportunity to make data-centers more energy efficient by designing systems with lower energy footprint. Consuming less energy is critical not only in data-centers. It is also important in mobile devices where battery-based energy is a scarce resource. Reducing the energy consumption of these devices will allow them to last longer and re-charge less frequently. Saving energy in computer systems is a challenging problem. Improving a system's energy efficiency usually comes at the cost of compromises in other areas such as performance or reliability. In the case of secondary storage, for example, spinning-down the disks to save energy can incur high latencies if they are accessed while in this state. The challenge is to be able to increase the energy efficiency while keeping the system as reliable and responsive as before. This thesis tackles the problem of improving energy efficiency in existing systems while reducing the impact on performance. First, we propose a new technique to achieve fine grained energy proportionality in multi-disk systems; Second, we design and implement an energy-efficient cache system using flash memory that increases disk idleness to save energy; Finally, we identify and explore solutions for the page fetch-before-update problem in caching systems that can: (a) control better I/O traffic to secondary storage and (b) provide critical performance improvement for energy efficient systems.

Universal Design for Learning and Differentiated Instruction: Resolving Competing Mandates of the Individuals with Disabilities Education Act and No Child Left Behind

Recent federal mandates require accountability for providing students with disabilities access to the general education curriculum. In this paper, the authors recommend that principles of Universal Design for Learning and Differentiated Instruction can help school personnel tailor their teaching to meet the various strengths and needs of individual students.

Scaffolding in Second Language Learning and Instruction

In a study of the triadic interaction among pairs of advanced second language learners engaged in a complex language task, it was found that the scaffolding provided by the researcher was determinant in keeping the participants on task and encouraging language production, thus facilitating both language development and comprehension.

The Role of Forgiveness in Adult Learning and Education

Adverse experiences can initiate angry and negative emotions and if not addressed and resolved have the ability to impede learning. Forgiveness counseling gives learners and educators a way to extinguish the power of these hindering emotions and thereby enhance learning.

Revisiting Entrepreneurship Education Literature: Implications for Learning and Teaching Entrepreneurship

Courses and programs about entrepreneurship show so much variation that it is hard to identify typical teaching strategies. Although diversity is good, consistency is needed because the value of entrepreneurship education has not been established. A literature review on teaching and learning in entrepreneurship was conducted; three challenges were identified.

Global Learning and the Human Capability Approach: Florida International University Case Study

This case study traced the process in which Florida International University engaged to determine what students want and need from their undergraduate education. Using grounded theory, the authors discovered that the process was reflective of the human capability approach in the development of its global learning student learning outcomes.

Estrogen and Lithium: Facilitating Factors Involved in Brain Cell Signaling Pathways

Learning and memory in adult females decline during menopause and estrogen replacement therapy is commonly prescribed during menopause. Post-menopausal women tend to suffer from depression and are prescribed antidepressants – in addition to hormone therapy. Estrogen replacement therapy is a topic that engenders debate since several studies contradict its efficacy as a palliative therapy for cognitive decline and neurodegenerative diseases. Signaling transduction pathways can alter brain cell activity, survival, and morphology by facilitating transcription factor DNA binding and protein production. The steroidal hormone estrogen and the anti-depressant drug lithium interact through these signaling transduction pathways facilitating transcription factor activation. The paucity of data on how combined hormones and antidepressants interact in regulating gene expression led me to hypothesize that in primary mixed brain cell cultures, combined 17beta-estradiol (E2) and lithium chloride (LiCl) (E2/LiCl) will alter genetic expression of markers involved in synaptic plasticity and neuroprotection. Results from these studies indicated that a 48 h treatment of E2/LiCl reduced glutamate receptor subunit genetic expression, but increased neurotrophic factor and estrogen receptor genetic expression. Combined treatment also failed to protect brain cell cultures from glutamate excitotoxicity. If lithium facilitates protein signaling pathways mediated by estrogen, can lithium alone serve as a palliative treatment for post-menopause? This question led me to hypothesize that in estrogen-deficient mice, lithium alone will increase episodic memory (tested via object recognition), and enhance expression in the brain of factors involved in anti-apoptosis, learning and memory. I used bilaterally ovariectomized (bOVX) C57BL/6J mice treated with LiCl for one month. Results indicated that LiCl-treated bOVX mice increased performance in object recognition compared with non-treated bOVX. Increased performance in LiCl-treated bOVX mice coincided with augmented genetic and protein expression in the brain. Understanding the molecular pathways of estrogen will assist in identifying a palliative therapy for menopause-related dementia, and lithium may serve this purpose by acting as a selective estrogen-mediated signaling modulator.

Learning and accepting quantum physics. Re-analysis of a teaching proposal

Nella tesi è analizzata nel dettaglio una proposta didattica sulla Fisica Quantistica elaborata dal gruppo di ricerca in Didattica della Fisica dell’Università di Bologna, in collaborazione con il gruppo di ricerca in Fisica Teorica e con ricercatori del CNR di Bologna. La proposta è stata sperimentata in diverse classi V di Liceo scientifico e dalle sperimentazioni sono emersi casi significativi di studenti che non sono riusciti ad accettare la teoria quantistica come descrizione convincente ad affidabile della realtà fisica (casi di non accettazione), nonostante sembrassero aver capito la maggior parte degli argomenti e essersi ‘appropriati’ del percorso per come gli era stato proposto. Da questa evidenza sono state formulate due domande di ricerca: (1) qual è la natura di questa non accettazione? Rispecchia una presa di posizione epistemologica o è espressione di una mancanza di comprensione profonda? (2) Nel secondo caso, è possibile individuare precisi meccanismi cognitivi che possono ostacolare o facilitare l’accettazione della fisica quantistica? L’analisi di interviste individuali degli studenti ha permesso di mettere in luce tre principali esigenze cognitive (cognitive needs) che sembrano essere coinvolte nell’accettazione e nell’apprendimento della fisica quantistica: le esigenze di visualizzabilità, comparabilità e di ‘realtà’. I ‘cognitive needs’ sono stati quindi utilizzati come strumenti di analisi delle diverse proposte didattiche in letteratura e del percorso di Bologna, al fine di metterne in luce le criticità. Sono state infine avanzate alcune proposte per un suo miglioramento.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Convergence and translation: attitudes to inter-professional learning and teaching of creative problem-solving among medical and engineering students and staff

Background: Healthcare worldwide needs translation of basic ideas from engineering into the clinic. Consequently, there is increasing demand for graduates equipped with the knowledge and skills to apply interdisciplinary medicine/engineering approaches to the development of novel solutions for healthcare. The literature provides little guidance regarding barriers to, and facilitators of, effective interdisciplinary learning for engineering and medical students in a team-based project context. Methods: A quantitative survey was distributed to engineering and medical students and staff in two universities, one in Ireland and one in Belgium, to chart knowledge and practice in interdisciplinary learning and teaching, and of the teaching of innovation. Results: We report important differences for staff and students between the disciplines regarding attitudes towards, and perceptions of, the relevance of interdisciplinary learning opportunities, and the role of creativity and innovation. There was agreement across groups concerning preferred learning, instructional styles, and module content. Medical students showed greater resistance to the use of structured creativity tools and interdisciplinary teams. Conclusions: The results of this international survey will help to define the optimal learning conditions under which undergraduate engineering and medicine students can learn to consider the diverse factors which determine the success or failure of a healthcare engineering solution.

Investigative Interviewing and Memory: How Accurate Are Interviewers’ Recollections of Investigative Interviews?

Contrary to interviewing guidelines, a considerable portion of witness interviews are not recorded. Investigators’ memory, their interview notes, and any subsequent interview reports therefore become important pieces of evidence; the accuracy of interviewers’ memory or such reports is therefore of crucial importance when interviewers testify in court regarding witness interviews. A detailed recollection of the actual exchange during such interviews and how information was elicited from the witness will allow for a better assessment of statement veracity in court. Two studies were designed to examine interviewers’ memory for a prior witness interview. Study One varied interviewer note-taking and type of subsequent interview report written by interviewers by including a sample of undergraduates and implementing a two-week delay between interview and recall. Study Two varied levels of interviewing experience in addition to report type and note-taking by comparing experienced police interviewers to a student sample. Participants interviewed a mock witness about a crime, while taking notes or not, and wrote an interview report two weeks later (Study One) or immediately after (Study Two). Interview reports were written either in a summarized format, which asked interviewers for a summary of everything that occurred during the interview, or verbatim format, which asked interviewers to record in transcript format the questions they asked and the witness’s responses. Interviews were videotaped and transcribed. Transcriptions were compared to interview reports to score for accuracy and omission of interview content. Results from both studies indicate that much interview information is lost between interview and report especially after a two-week delay. The majority of information reported by interviewers is accurate, although even interviewers who recalled information immediately after still reported a troubling amount of inaccurate information. Note-taking was found to increase accuracy and completeness of interviewer reports especially after a two week delay. Report type only influenced recall of interviewer questions. Experienced police interviewers were not any better at recalling a prior witness interview than student interviewers. Results emphasize the need to record witness interviews to allow for more accurate and complete interview reconstruction by interviewers, even if interview notes are available.