Naval Reserve support to information Operations Warfighting

Since the mid-1990s, the Fleet Information Warfare Center (FIWC) has led the Navy's Information Operations (IO) support to the Fleet. Within the FIWC manning structure, there are in total 36 officer and 84 enlisted Naval Reserve billets that are manned to approximately 75 percent and located in Norfolk and San Diego Naval Reserve Centers. These Naval Reserve Force personnel could provide support to FIWC far and above what they are now contributing specifically in the areas of Computer Network Operations, Psychological Operations, Military Deception and Civil Affairs. Historically personnel conducting IO were primarily reservists and civilians in uniform with regular military officers being by far the minority. The Naval Reserve Force has the personnel to provide skilled IO operators but the lack of an effective manning document and training plans is hindering their opportunity to enhance FIWC's capabilities in lull spectrum IO. This research investigates the skill requirements of personnel in IO to verify that the Naval Reserve Force has the talent base for IO support and the feasibility of their expanded use in IO.http://archive.org/details/navalreservesupp109451098

Improving Dependability of Networks with Penalty and Revocation Mechanisms

Both malicious and non-malicious faults can dismantle computer networks. Thus, mitigating faults at various layers is essential in ensuring efficient and fair network resource utilization. In this thesis we take a step in this direction and study several ways to deal with faults by means of penalties and revocation mechanisms in networks that are lacking a centralized coordination point, either because of their scale or design. Compromised nodes can pose a serious threat to infrastructure, end-hosts and services. Such malicious elements can undermine the availability and fairness of networked systems. To deal with such nodes, we design and analyze protocols enabling their removal from the network in a fast and a secure way. We design these protocols for two different environments. In the former setting, we assume that there are multiple, but independent trusted points in the network which coordinate other nodes in the network. In the latter, we assume that all nodes play equal roles in the network and thus need to cooperate to carry out common functionality. We analyze these solutions and discuss possible deployment scenarios. Next we turn our attention to wireless edge networks. In this context, some nodes, without being malicious, can still behave in an unfair manner. To deal with the situation, we propose several self-penalty mechanisms. We implement the proposed protocols employing a commodity hardware and conduct experiments in real-world environments. The analysis of data collected in several measurement rounds revealed improvements in terms of higher fairness and throughput. We corroborate the results with simulations and an analytic model. And finally, we discuss how to measure fairness in dynamic settings, where nodes can have heterogeneous resource demands

The Internet of Everything

In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)

Medical Informatics

Information technology has been revolutionizing the everyday life of the common man, while medical science has been making rapid strides in understanding disease mechanisms, developing diagnostic techniques and effecting successful treatment regimen, even for those cases which would have been classified as a poor prognosis a decade earlier. The confluence of information technology and biomedicine has brought into its ambit additional dimensions of computerized databases for patient conditions, revolutionizing the way health care and patient information is recorded, processed, interpreted and utilized for improving the quality of life. This book consists of seven chapters dealing with the three primary issues of medical information acquisition from a patient's and health care professional's perspective, translational approaches from a researcher's point of view, and finally the application potential as required by the clinicians/physician. The book covers modern issues in Information Technology, Bioinformatics Methods and Clinical Applications. The chapters describe the basic process of acquisition of information in a health system, recent technological developments in biomedicine and the realistic evaluation of medical informatics

Strategies of development and maintenance in supervision, control, synchronization, data acquisition and processing in light sources

Programa Oficial de Doutoramento en Tecnoloxías da Información e as Comunicacións. 5032V01[Resumo] Os aceleradores de partículas e fontes de luz sincrotrón, evolucionan constantemente para estar na vangarda da tecnoloxía, levando os límites cada vez mais lonxe para explorar novos dominios e universos. Os sistemas de control son unha parte crucial desas instalacións científicas e buscan logra-la flexibilidade de manobra para poder facer experimentos moi variados, con configuracións diferentes que engloban moitos tipos de detectores, procedementos, mostras a estudar e contornas. As propostas de experimento son cada vez máis ambiciosas e van sempre un paso por diante do establecido. Precísanse detectores cada volta máis rápidos e eficientes, con máis ancho de banda e con máis resolución. Tamén é importante a operación simultánea de varios detectores tanto escalares como mono ou bidimensionáis, con mecanismos de sincronización de precisión que integren as singularidades de cada un. Este traballo estuda as solucións existentes no campo dos sistemas de control e adquisición de datos nos aceleradores de partículas e fontes de luz e raios X, ó tempo que explora novos requisitos e retos no que respecta á sincronización e velocidade de adquisición de datos para novos experimentos, a optimización do deseño, soporte, xestión de servizos e custos de operación. Tamén se estudan diferentes solucións adaptadas a cada contorna.[Resumen] Los aceleradores de partículas y fuentes de luz sincrotrón, evolucionan constantemente para estar en la vanguardia de la tecnología, y poder explorar nuevos dominios. Los sistemas de control son una parte fundamental de esas instalaciones científicas y buscan lograr la máxima flexibilidad para poder llevar a cabo experimentos más variados, con configuraciones diferentes que engloban varios tipos de detectores, procedimientos, muestras a estudiar y entornos. Los experimentos se proponen cada vez más ambiciosos y en ocasiones más allá de los límites establecidos. Se necesitan detectores cada vez más rápidos y eficientes, con más resolución y ancho de banda, que puedan sincronizarse simultáneamente con otros detectores tanto escalares como mono y bidimensionales, integrando las singularidades de cada uno y homogeneizando la adquisición de datos. Este trabajo estudia los sistemas de control y adquisición de datos de aceleradores de partículas y fuentes de luz y rayos X, y explora nuevos requisitos y retos en lo que respecta a la sincronización y velocidad de adquisición de datos, optimización y costo-eficiencia en el diseño, operación soporte, mantenimiento y gestión de servicios. También se estudian diferentes soluciones adaptadas a cada entorno.[Abstract] Particle accelerators and photon sources are constantly evolving, attaining the cutting-edge technologies to push the limits forward and explore new domains. The control systems are a crucial part of these installations and are required to provide flexible solutions to the new challenging experiments, with different kinds of detectors, setups, sample environments and procedures. Experiment proposals are more and more ambitious at each call and go often a step beyond the capabilities of the instrumentation. Detectors shall be faster, with higher efficiency, more resolution, more bandwidth and able to synchronize with other detectors of all kinds; scalars, one or two-dimensional, taking into account their singularities and homogenizing the data acquisition. This work examines the control and data acquisition systems for particle accelerators and X- ray / light sources and explores new requirements and challenges regarding synchronization and data acquisition bandwidth, optimization and cost-efficiency in the design / operation / support. It also studies different solutions depending on the environment

Geographic Information Systems for Real-Time Environmental Sensing at Multiple Scales

The purpose of this investigation was to design, implement, and apply a real-time geographic information system for data intensive water resource research and management. The research presented is part of an ongoing, interdisciplinary research program supporting the development of the Intelligent River® observation instrument. The objectives of this research were to 1) design and describe software architecture for a streaming environmental sensing information system, 2) implement and evaluate the proposed information system, and 3) apply the information system for monitoring, analysis, and visualization of an urban stormwater improvement project located in the City of Aiken, South Carolina, USA. This research contributes to the fields of software architecture and urban ecohydrology. The first contribution is a formal architectural description of a streaming environmental sensing information system. This research demonstrates the operation of the information system and provides a reference point for future software implementations. Contributions to urban ecohydrology are in three areas. First, a characterization of soil properties for the study region of the City of Aiken, SC is provided. The analysis includes an evaluation of spatial structure for soil hydrologic properties. Findings indicate no detectable structure at the scales explored during the study. The second contribution to ecohydrology comes from a long-term, continuous monitoring program for bioinfiltration basin structures located in the study area. Results include an analysis of soil moisture dynamics based on data collected at multiple depths with high spatial and temporal resolution. A novel metric is introduced to evaluate the long-term performance of bioinfiltration basin structures based on soil moisture observation data. Findings indicate a decrease in basin performance over time for the monitored sites. The third contribution to the field of ecohydrology is the development and application of a spatially and temporally explicit rainfall infiltration and excess model. The model enables the simulation and visualization of bioinfiltration basin hydrologic response at within-catchment scales. The model is validated against observed soil moisture data. Results include visualizations and stormwater volume calculations based on measured versus predicted bioinfiltration basin performance over time

The Internet of Everything

In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)

Transmission Modeling with Smartphone-based Sensing

Infectious disease spread is difficult to accurately measure and model. Even for well-studied pathogens, uncertainties remain regarding the dynamics of mixing behavior and how to balance simulation-generated estimates with empirical data. Smartphone-based sensing data promises the availability of inferred proximate contacts, with which we can improve transmission models. This dissertation addresses the problem of informing transmission models with proximity contact data by breaking it down into three sub-questions. Firstly, can proximity contact data inform transmission models? To this question, an extended-Kalman-filter enhanced System Dynamics Susceptible-Infectious-Removed (EKF-SD-SIR) model demonstrated the filtering approach, as a framework, for informing Systems Dynamics models with proximity contact data. This combination results in recurrently-regrounded system status as empirical data arrive throughout disease transmission simulations---simultaneously considering empirical data accuracy, growing simulation error between measurements, and supporting estimation of changing model parameters. However, as revealed by this investigation, this filtering approach is limited by the quality and reliability of sensing-informed proximate contacts, which leads to the dissertation's second and third questions---investigating the impact of temporal and spatial resolution on sensing inferred proximity contact data for transmission models. GPS co-location and Bluetooth beaconing are two of those common measurement modalities to sense proximity contacts with different underlying technologies and tradeoffs. However, both measurement modalities have shortcomings and are prone to false positives or negatives when used to detect proximate contacts because unmeasured environmental influences bias the data. Will differences in sensing modalities impact transmission models informed by proximity contact data? The second part of this dissertation compares GPS- and Bluetooth-inferred proximate contacts by accessing their impact on simulated attack rates in corresponding proximate-contact-informed agent-based Susceptible-Exposed-Infectious-Recovered (ABM-SEIR) models of four distinct contagious diseases. Results show that the inferred proximate contacts resulting from these two measurement modalities are different and give rise to significantly different attack rates across multiple data collections and pathogens. While the advent of commodity mobile devices has eased the collection of proximity contact data, battery capacity and associated costs impose tradeoffs between the frequency and scanning duration used for proximate-contact detection. The choice of a balanced sensing regime involves specifying temporal resolutions and interpreting sensing data---depending on circumstances such as the characteristics of a particular pathogen, accompanying disease, and underlying population. How will the temporal resolution of sensing impact transmission models informed by proximity contact data? Furthermore, how will circumstances alter the impact of temporal resolution? The third part of this dissertation investigates the impacts of sensing regimes on findings from two sampling methods of sensing at widely varying inter-observation intervals by synthetically downsampling proximity contact data from five contact network studies---with each of these five studies measuring participant-participant contact every 5 minutes for durations of four or more weeks. The impact of downsampling is evaluated through ABM-SEIR simulations from both population- and individual-level for 12 distinct contagious diseases and associated variants of concern. Studies in this part find that for epidemiological models employing proximity contact data, both the observation paradigms and the inter-observation interval configured to collect proximity contact data exert impacts on the simulation results. Moreover, the impact is subject to the population characteristics and pathogen infectiousness reflective (such as the basic reproduction number, $R_0$). By comparing the performance of two sampling methods of sensing, we found that in most cases, periodically observing for a certain duration can collect proximity contact data that allows agent-based models to produce a reasonable estimation of the attack rate. However, higher-resolution data are preferred for modeling individual infection risk. Findings from this part of the dissertation represent a step towards providing the empirical basis for guidelines to inform data collection that is at once efficient and effective. This dissertation addresses the problem of informing transmission models with proximity contact data in three steps. Firstly, the demonstration of an EKF-SD-SIR model suggests that the filtering approach could improve System Dynamics transmission models by leveraging proximity contact data. In addition, experiments with the EKF-SD-SIR model also revealed that the filtering approach is constrained by the limited quality and reliability of sensing-data-inferred proximate contacts. The following two parts of this dissertation investigate spatial-temporal factors that could impact the quality and reliability of sensor-collected proximity contact data. In the second step, the impact of spatial resolution is illustrated by differences between two typical sensing modalities---Bluetooth beaconing versus GPS co-location. Experiments show that, in general, proximity contact data collected with Bluetooth beaconing lead to transmission models with results different from those driven by proximity contact data collected with GPS co-location. Awareness of the differences between sensing modalities can aid researchers in incorporating proximity contact data into transmission models. Finally, in the third step, the impact of temporal resolution is elucidated by investigating the differences between results of transmission models led by proximity contact data collected with varying observation frequencies. These differences led by varying observation frequencies are evaluated under circumstances with alternative assumptions regarding sampling method, disease/pathogen type, and the underlying population. Experiments show that the impact of sensing regimes is influenced by the type of diseases/pathogens and underlying population, while sampling once in a while can be a decent choice across all situations. This dissertation demonstrated the value of a filtering approach to enhance transmission models with sensor-collected proximity contact data, as well as explored spatial-temporal factors that will impact the accuracy and reliability of sensor-collected proximity contact data. Furthermore, this dissertation suggested guidance for future sensor-based proximity contact data collection and highlighted needs and opportunities for further research on sensing-inferred proximity contact data for transmission models