Standardization of data collection for the Lifetime Surveillance of Astronaut Health (LSAH)

Problems due to the lack of data standardization and data management have lead to work inefficiencies for the staff working with the vision data for the Lifetime Surveillance of Astronaut Health. Data has been collected over 50 years in a variety of manners and then entered into a software. The lack of communication between the electronic health record (EHR) form designer, epidemiologists, and optometrists has led to some level to confusion on the capability of the EHR system and how its forms can be designed to fit all the needs of the relevant parties. EHR form customizations or form redesigns were found to be critical for using NASA's EHR system in the most beneficial way for its patients, optometrists, and epidemiologists. In order to implement a protocol, data being collected was examined to find the differences in data collection methods. Changes were implemented through the establishment of a process improvement team (PIT). Based on the findings of the PIT, suggestions have been made to improve the current EHR system. If the suggestions are implemented correctly, this will not only improve efficiency of the staff at NASA and its contractors, but set guidelines for changes in other forms such as the vision exam forms. Because NASA is at the forefront of such research and health surveillance the impact of this management change could have a drastic improvement on the collection of and adaptability of the EHR. Accurate data collection from this 50+ year study is ongoing and is going to help current and future generations understand the implications of space flight on human health. It is imperative that the vast amount of information is documented correctly.^

Experimentel ADS-B based surveillance

This paper describes an ADS-B implementation in air-to-air and ground based experimental surveillance within a prototype ATM system. The relations between airborne and ground systems related to surveillance are detailed, and the prototype surveillance systems and their algorithms described. Their performance is analysed, based both on simulated and real data.

Automatic Adaptation of Airport Surface Surveillance to Sensor Quality

This paper describes a novel method to enhance current airport surveillance systems used in Advanced Surveillance Monitoring Guidance and Control Systems (A-SMGCS). The proposed method allows for the automatic calibration of measurement models and enhanced detection of nonideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the surveillance processing chain and a rule based expert system aimed to change the data processing methods

Sustainable Air Traffic Management System Development Methodology

As it is defined in ATM 2000+ Strategy (Eurocontrol 2001), the mission of the Air Traffic Management (ATM) System is: “For all the phases of a flight, the ATM system should facilitate a safe, efficient, and expedite traffic flow, through the provision of adaptable ATM services that can be dimensioned in relation to the requirements of all the users and areas of the European air space. The ATM services should comply with the demand, be compatible, operate under uniform principles, respect the environment and satisfy the national security requirements.” The objective of this paper is to present a methodology designed to evaluate the status of the ATM system in terms of the relationship between the offered capacity and traffic demand, identifying weakness areas and proposing solutions. The first part of the methodology relates to the characterization and evaluation of the current system, while a second part proposes an approach to analyze the possible development limit. As part of the work, general criteria are established to define the framework in which the analysis and diagnostic methodology presented is placed. They are: the use of Air Traffic Control (ATC) sectors as analysis unit, the presence of network effects, the tactical focus, the relative character of the analysis, objectivity and a high level assessment that allows assumptions on the human and Communications, Navigation and Surveillance (CNS) elements, considered as the typical high density air traffic resources. The steps followed by the methodology start with the definition of indicators and metrics, like the nominal criticality or the nominal efficiency of a sector; scenario characterization where the necessary data is collected; network effects analysis to study the relations among the constitutive elements of the ATC system; diagnostic by means of the “System Status Diagram”; analytical study of the ATC system development limit; and finally, formulation of conclusions and proposal for improvement. This methodology was employed by Aena (Spanish Airports Manager and Air Navigation Service Provider) and INECO (Spanish Transport Engineering Company) in the analysis of the Spanish ATM System in the frame of the Spanish airspace capacity sustainability program, although it could be applied elsewhere.

In situ surveillance of capacitive pressure transmitter dynamic poles

In this work, a methodology is proposed to find the dynamic poles of a capacitive pressure transmitter in order to enhance and extend the online surveillance of this type of sensor based on the response time measurement by applying noise analysis techniques and the dynamic data system procedure. Several measurements taken from a pressurized water reactor have been analyzed. The methodology proposes an autoregressive fit whose order is determined by the sensor dynamic poles. Nevertheless, the signals that have been analyzed could not be filtered properly in order to remove the plant noise; thus, this was considered as an additional pair of complex conjugate poles. With this methodology we have come up with the numerical value of the sensor second real pole in spite of its low influence on the sensor dynamic response. This opens up a more accurate online sensor surveillance since the previous methods were achieved by considering one real pole only.

AR modelling and DDS for in situ surveillance of capacitive pressure transmitters

In this work, a methodology is proposed to find the dynamics poles of a capacitive pressure transmitter in order to enhance and extend the on line surveillance of this type of sensors based on the response time measurement by applying noise analysis techniques and the Dynamic Data System. Several measurements have been analyzed taken from a Pressurized Water Reactor. The methodology proposes an autoregressive fit whose order is determined by the sensor dynamics poles. Nevertheless, the signals that have been analyzed, could not be filtered properly in order to remove the plant noise, thus, this was considered as an additional pair of complex conjugate poles. With this methodology we have come up with the numerical value of the sensor second real pole in spite of its low influence on the sensor dynamic response. This opens up a more accurate on line sensor surveillance since the previous methods were achieved by considering one real pole only.

Low-Cost Radar-Based Target Identification Prototype using an Expert System

Smart and green cities are hot topics in current research because people are becoming more conscious about their impact on the environment and the sustainability of their cities as the population increases. Many researchers are searching for mechanisms that can reduce power consumption and pollution in the city environment. This paper addresses the issue of public lighting and how it can be improved in order to achieve a more energy efficient city. This work is focused on making the process of turning the streetlights on and off more intelligent so that they consume less power and cause less light pollution. The proposed solution is comprised of a radar device and an expert system implemented on a low-cost platform based on a DSP. By analyzing the radar echo in both the frequency and time domains, the system is able to detect and identify objects moving in front of it. This information is used to decide whether or not the streetlight should be turned on. Experimental results show that the proposed system can provide hit rates over 80%, promising a good performance. In addition, the proposed solution could be useful in kind of other applications such as intelligent security and surveillance systems and home automation.

Foreground segmentation in depth imagery using depth and spatial dynamic models for video surveillance applications

Low-cost systems that can obtain a high-quality foreground segmentation almostindependently of the existing illumination conditions for indoor environments are verydesirable, especially for security and surveillance applications. In this paper, a novelforeground segmentation algorithm that uses only a Kinect depth sensor is proposedto satisfy the aforementioned system characteristics. This is achieved by combininga mixture of Gaussians-based background subtraction algorithm with a new Bayesiannetwork that robustly predicts the foreground/background regions between consecutivetime steps. The Bayesian network explicitly exploits the intrinsic characteristics ofthe depth data by means of two dynamic models that estimate the spatial and depthevolution of the foreground/background regions. The most remarkable contribution is thedepth-based dynamic model that predicts the changes in the foreground depth distributionbetween consecutive time steps. This is a key difference with regard to visible imagery,where the color/gray distribution of the foreground is typically assumed to be constant.Experiments carried out on two different depth-based databases demonstrate that theproposed combination of algorithms is able to obtain a more accurate segmentation of theforeground/background than other state-of-the art approaches.

Cognitive Surveillance Architecture for Scenario Understanding

Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.

Premature Sister Chromatid Separation Is Poorly Detected by the Spindle Assembly Checkpoint as a Result of System-Level Feedback

Sister chromatid cohesion, mediated by the cohesin complex, is essential for faithful mitosis. Nevertheless, evidence suggests that the surveillance mechanism that governs mitotic fidelity, the spindle assembly checkpoint (SAC), is not robust enough to halt cell division when cohesion loss occurs prematurely. The mechanism behind this poor response is not properly understood. Using developing Drosophila brains, we show that full sister chromatid separation elicits a weak checkpoint response resulting in abnormal mitotic exit after a short delay. Quantitative live-cell imaging approaches combined with mathematical modeling indicate that weak SAC activation upon cohesion loss is caused by weak signal generation. This is further attenuated by several feedback loops in the mitotic signaling network. We propose that multiple feedback loops involving cyclin-dependent kinase 1 (Cdk1) gradually impair error-correction efficiency and accelerate mitotic exit upon premature loss of cohesion. Our findings explain how cohesion defects may escape SAC surveillance.

Computerized allocation of police traffic services; reference volume I. Computer-sensor system description. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Operator's manual : detection system, ground movement (Honeywell Inc. MAGID T4, DT-509/GSQ), FSN 6350-150-6807.

"14 February 1972."

Operator, organizational, and intermediate (direct support and general support) maintenance manual, installation, operation and checkout procedures for Joint-Services Interior Intrusion Detection System (J-SIIDS).

Includes index.

Operator, organizational, direct support, and general support maintenance manual : installation, operation, and checkout procedures for Joint-Services Interior Intrusion Detection System (J-SIIDS).

"19 May 1983."

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04