QoS adaptation in multimedia multicast conference applications for e-learning services

Tolerant real-time applications, such as video conferences, are in the frontline to benefit from QoS adaptation. However, not all include adaptive technology able to provide both end-system and network quality awareness. Adaptation, in these cases, can be achieved by introducing a multiplatform middleware layer responsible for tutoring the applications’ resources (enabling adjudication or limitation) based on the available processing and networking capabilities. Congregating these technological contributions, an adaptive platform has been developed integrating public domain multicast tools, applied to a Web-based distance learning system. The system is user-centered (estudent), aiming at good pedagogical practices and proactive usability for multimedia and networkresources. The services provided, including QoS adapted interactive multimedia multicast conferences (MMC), are fully integrated and transparent to end-users. QoS adaptation, when treated systematically in tolerant real-time applications, denotes advantages in group scalability and QoS sustainability in heterogeneous and unpredictable environments such as the Internet

Securing configuration, management and migration of virtual network functions using blockchain

The current technologies of network functions virtualization and network service function chaining increase service provision agility and add intelligence at the core of the network. However, the network core programmability and the provision of services by multiple providers brings new vulnerabilities to this scenario. The need for secure provisioning of virtual network service functions (VNFs) becomes even more critical, since simple modifications at the network core can affect multiple network users. This work proposes a blockchain-based architecture for secure management, configuration and migration of VNFs. This architecture ensures the immutability, non-repudiation, and auditability of VNF configuration and the management histories. In addition, the proposed architecture preserves the anonymity of VNFs, tenants, and configuration information, to mitigate the possibilities of targeted attack. A prototype designed for the OPNFV (Open Platform for NFV) platform was developed, and the proposed architecture performance was evaluated in terms of parameters trade-offs and bottlenecks.As tecnologias de virtualização de funções de rede e de encadeamento de funções de serviço de rede aumentam a agilidade na provisão de serviços e acrescentam inteligência no núcleo da rede. No entanto, a programabilidade do n´núcleo da rede e a oferta de serviços por múltiplos fornecedores provocam novas vulnerabilidades neste ambiente. A necessidade de provisão de funções virtuais de serviço de rede (VNFs) seguras torna-se ainda mais crítica, uma vez que uma simples modificação no núcleo da rede pode afetar múltiplos usuários. Este trabalho propõe uma arquitetura baseada em correntes de blocos para gerenciamento seguro, configuração emigração de VNFs. Esta arquitetura garante a imutabilidade, não repúdio e auditabilidade da configuração de VNF e do histórico de gerenciamento de VNFs. Além disso, a arquitetura proposta preserva o anonimato das VNFs, dos inquilinos e das informações de configuração, a fim de evitar que estes se tornem alvos de ataques. Foi desenvolvido um protótipo concebido para a plataforma OPNFV (Open Platform for NFV) e foi avaliado o desempenho em relação ao custo benefício de parâmetros e aos gargalos da arquitetura proposta

Hardware Acceleration for Unstructured Big Data and Natural Language Processing.

The confluence of the rapid growth in electronic data in recent years, and the renewed interest in domain-specific hardware accelerators presents exciting technical opportunities. Traditional scale-out solutions for processing the vast amounts of text data have been shown to be energy- and cost-inefficient. In contrast, custom hardware accelerators can provide higher throughputs, lower latencies, and significant energy savings. In this thesis, I present a set of hardware accelerators for unstructured big-data processing and natural language processing. The first accelerator, called HAWK, aims to speed up the processing of ad hoc queries against large in-memory logs. HAWK is motivated by the observation that traditional software-based tools for processing large text corpora use memory bandwidth inefficiently due to software overheads, and, thus, fall far short of peak scan rates possible on modern memory systems. HAWK is designed to process data at a constant rate of 32 GB/s—faster than most extant memory systems. I demonstrate that HAWK outperforms state-of-the-art software solutions for text processing, almost by an order of magnitude in many cases. HAWK occupies an area of 45 sq-mm in its pareto-optimal configuration and consumes 22 W of power, well within the area and power envelopes of modern CPU chips. The second accelerator I propose aims to speed up similarity measurement calculations for semantic search in the natural language processing space. By leveraging the latency hiding concepts of multi-threading and simple scheduling mechanisms, my design maximizes functional unit utilization. This similarity measurement accelerator provides speedups of 36x-42x over optimized software running on server-class cores, while requiring 56x-58x lower energy, and only 1.3% of the area.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116712/1/prateekt_1.pd

The Centers for Disease Control and Prevention's Healthy Days Measures – Population tracking of perceived physical and mental health over time

To promote the health and quality of life of United States residents, the U.S. Department of Health and Human Services' Centers for Disease Control and Prevention (CDC) – with 54 state and territorial health agencies – has supported population surveillance of health-related quality of life (HRQOL). HRQOL was defined as "perceived physical and mental health over time." Commonly-used measures of health status and activity limitation were identified and a set of "Healthy Days" HRQOL measures was developed and validated. A core set of these measures (the CDC HRQOL-4) asks about self-rated general health and the number of recent days when a person was physically unhealthy, mentally unhealthy, or limited in usual activities. A summary measure combines physically and mentally unhealthy days. From 1993 to 2001, more than 1.2 million adults responded to the CDC HRQOL-4 in each state-based Behavioral Risk Factor Surveillance System (BRFSS) telephone interview. More than one fifth of all BRFSS respondents also responded to a set of related questions – including five items that assess the presence, main cause and duration of a current activity limitation, and the need for activity-related personal and routine care; as well as five items that ask about recent days of pain, depression, anxiety, sleeplessness, and vitality. The Healthy Days surveillance data are particularly useful for finding unmet health needs, identifying disparities among demographic and socioeconomic subpopulations, characterizing the symptom burden of disabilities and chronic diseases, and tracking population patterns and trends. The full set of 14 Healthy Days Measures (the CDC HRQOL-14) has shown good measurement properties in several populations, languages, and settings. The brief standard CDC HRQOL-4 is now often used in surveys, surveillance systems, prevention research, and population health report cards

The effects of hemodynamic lag on functional connectivity and behavior after stroke

Stroke disrupts the brain's vascular supply, not only within but also outside areas of infarction. We investigated temporal delays (lag) in resting state functional magnetic resonance imaging signals in 130 stroke patients scanned two weeks, three months and 12 months post stroke onset. Thirty controls were scanned twice at an interval of three months. Hemodynamic lag was determined using cross-correlation with the global gray matter signal. Behavioral performance in multiple domains was assessed in all patients. Regional cerebral blood flow and carotid patency were assessed in subsets of the cohort using arterial spin labeling and carotid Doppler ultrasonography. Significant hemodynamic lag was observed in 30% of stroke patients sub-acutely. Approximately 10% of patients showed lag at one-year post-stroke. Hemodynamic lag corresponded to gross aberrancy in functional connectivity measures, performance deficits in multiple domains and local and global perfusion deficits. Correcting for lag partially normalized abnormalities in measured functional connectivity. Yet post-stroke FC-behavior relationships in the motor and attention systems persisted even after hemodynamic delays were corrected. Resting state fMRI can reliably identify areas of hemodynamic delay following stroke. Our data reveal that hemodynamic delay is common sub-acutely, alters functional connectivity, and may be of clinical importance

On the security of NoSQL cloud database services

Processing a vast volume of data generated by web, mobile and Internet-enabled devices, necessitates a scalable and flexible data management system. Database-as-a-Service (DBaaS) is a new cloud computing paradigm, promising a cost-effective and scalable, fully-managed database functionality meeting the requirements of online data processing. Although DBaaS offers many benefits it also introduces new threats and vulnerabilities. While many traditional data processing threats remain, DBaaS introduces new challenges such as confidentiality violation and information leakage in the presence of privileged malicious insiders and adds new dimension to the data security. We address the problem of building a secure DBaaS for a public cloud infrastructure where, the Cloud Service Provider (CSP) is not completely trusted by the data owner. We present a high level description of several architectures combining modern cryptographic primitives for achieving this goal. A novel searchable security scheme is proposed to leverage secure query processing in presence of a malicious cloud insider without disclosing sensitive information. A holistic database security scheme comprised of data confidentiality and information leakage prevention is proposed in this dissertation. The main contributions of our work are: (i) A searchable security scheme for non-relational databases of the cloud DBaaS; (ii) Leakage minimization in the untrusted cloud. The analysis of experiments that employ a set of established cryptographic techniques to protect databases and minimize information leakage, proves that the performance of the proposed solution is bounded by communication cost rather than by the cryptographic computational effort

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 333)

This bibliography lists 122 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

"Enriching 360-degree technologies through human-computer interaction: psychometric validation of two memory tasks"

This doctoral dissertation explores the domain of neuropsychological assessment, with the objective of gaining a comprehensive understanding of an individual's cognitive functioning and detecting possible impairments. Traditional assessment tools, while possessing inherent value, frequently exhibit a deficiency in ecological validity when evaluating memory, as they predominantly concentrate on short-term, regulated tasks. To overcome this constraint, immersive technologies, specifically virtual reality and 360° videos, have surfaced as promising instruments for augmenting the ecological validity of cognitive assessments. This work examines the potential advantages of immersive technologies, particularly 360° videos, in enhancing memory evaluation. First, a comprehensive overview of contemporary virtual reality tools employed in the assessment of memory, as well as their convergence with conventional assessment measures has been provided. Then, the present study utilizes cluster and network analysis techniques to categorize 360° videos according to their content and applications, thereby offering significant insights into the potential of this nascent medium. The study introduces then a novel platform, Mindscape, that aims to address the existing technological disparity, thereby enhancing the accessibility of clinicians and researchers in developing cognitive tasks within immersive environments. The conclusion of the thesis encompasses the psychometric validation of two memory tasks, which have been specifically developed with Mindscape to assess episodic and spatial memory. The findings demonstrate disparities in cognitive performance between individuals diagnosed with Mild Cognitive Impairment and those without cognitive impairments, underscoring the interrelated nature of cognitive processes and the promising prospects of virtual reality technology in improving the authenticity of real-world experiences. Overall, this dissertation aims to respond to the demand for practical and ecologically valid neuropsychological assessments within the dynamic field of neuropsychology. It achieves this by integrating user-friendly platforms and immersive cognitive tasks into its methodology. By highlighting a shift in the field of neuropsychology towards prioritizing functional and practical assessments over theoretical frameworks, this work indicates a changing perspective within the discipline. This study highlights the potential of comprehensive and purpose-oriented assessment methods in cognitive evaluations, emphasizing the ongoing significance of research in fully comprehending the capabilities of immersive technologies