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Ionizing radiation (IR) is known to cause fetal programming, but the physiological effects of low-dose IR are not fully understood. This study examined the effect of low (50 mGy) to non-lethal (300 and 1000 mGy) radiation exposure during late gestation on cardiac metabolism and oxidative stress in adult offspring. Pregnant C57BL/6J mice were exposed to 50, 300, or 1000 mGy of gamma radiation or Sham irradiation on gestational day 15. Sixteen weeks after birth, 18F-Fluorodeoxyglucose (FDG) uptake was examined in the offspring using Positron Emission Tomography imaging. Western blot was used to determine changes in oxidative stress, antioxidants, and insulin signaling related proteins. Male and female offspring from irradiated dams had lower body weights when compared to the Sham. 1000 mGy female offspring demonstrated a significant increase in 18F-FDG uptake, glycogen content, and oxidative stress. 300 and 1000 mGy female mice exhibited increased superoxide dismutase activity, decreased glutathione peroxidase activity, and decreased reduced/oxidized glutathione ratio. We conclude that non-lethal radiation during late gestation can alter glucose uptake and increase oxidative stress in female offspring. These data provide evidence that low doses of IR during the third trimester are not harmful but higher, non-lethal doses can alter cardiac metabolism later in life and sex may have a role in fetal programming.

With the development and the competition between airports, they share more and more similarities with malls with the presence of international brands, large commercial spaces, many bars and restaurants, but also many services intended to complete or improve passengers’ experience. In a typical mall, consumers engage in many activities above and beyond shopping (they can socialize, pass time and so on). But research about passengers in airport generally focuses only on shopping and excludes the other activities. The aim of this research is to investigate the similarities and differences between airports and malls, in terms of activities’ patterns as well as passengers’ profiles. Our data is derived from a survey administrated in an international mid-size airport during summer 2017. First, using principal component analysis, we identified few differences, but many common points between airports and malls. Secondly, based on passengers’ activities and a hierarchical clustering method, we identified 4 clusters of passengers. Our results can have direct implications for airport management, to refine segmenting and targeting, and also to improve passengers’ overall airport experience.

The R&D group at Lockheed-Martin Canada has developed a target identifier function called ID Box. This computer program performs five main functions: first it transforms the sensor attribute input into a few contact ID declarations, second, it evaluates the association score between the contact declarations and the ID propositions of a current target track, third it performs attribute contact to track fusion using a modification of the Dempster-Shafer evidential theory, fourth the ID Box, using a platform library, produces a translator that unifies the information within track identity and the attribute input, and fifth, it manages the distribution of results to a system human computer interface. Our exhaustive platform library enables the ID Box to fuse attribute data from almost all kinds of sensor or information sources that may be found on large warships or patrol aircraft. These attributes are the radar cross section and the moving parts from surveillance radars, allegiance from interrogator systems, emitter composition from electronics support measure systems, spoken language from communication intercept systems, acoustical signature from sonar systems, propulsion types from IR detectors, dimensional data from imaging systems and other classification attributes from various systems or operators including dynamical parameters from positional trackers. This paper presents and describes the ID Box.

The Recognized Maritime Picture (RMP) is defined as a composite picture of activity over a maritime area of interest. In simplistic terms, building an RAMP comes down to finding if an object of interest, a ship in our case, is there or not, determining what it is, determining what it is doing and determining if some type of follow-on action is required. The Canadian Department of National Defence currently has access to or may, in the near future, have access to a number of civilians, military and allied information or sensor systems to accomplish these purposes. These systems include automatic self-reporting positional systems, air patrol surveillance systems, high frequency surface radars, electronic intelligence systems, radar space systems and high frequency direction finding sensors. The ability to make full use of these systems is limited by the existing capability to fuse data from all sources in a timely, accurate and complete manner. This paper presents an information fusion systems under development that correlates and fuses these information and sensor data sources. This fusion system, named Adaptive Fuzzy Logic Correlator, correlates the information in batch but fuses and constructs ship tracks sequentially. It applies standard Kalman filter techniques and fuzzy logic correlation techniques. We propose a set of recommendations that should improve the ship identification process. Particularly it is proposed to utilize as many non-redundant sources of information as possible that address specific vessel attributes. Another important recommendation states that the information fusion and data association techniques should be capable of dealing with incomplete and imprecise information. Some fuzzy logic techniques capable of tolerating imprecise and dissimilar data are proposed.

Tracking maneuvering targets is a complex problem which has generated a great deal of effort over the past several years. It has now been well established that in terms of tracking accuracy, the Interacting Multiple Model (IMM) algorithm, where state estimates are mixed, performs significantly better for maneuvering targets than other types of filters. However, the complexity of the IMM algorithm can prohibit its use in these applications of which similar algorithms cannot provide the necessary accuracy and which can ont afford the computational load of IMM algorithm. This paper presents the evaluation of the tracking accuracy of a multiple model track filter using three different constant-velocity models running in parallel and a maneuver detector. The output estimate is defined by selecting the model whose likelihood function is lower than a target maneuver threshold.

The aim of this paper is to explore the problem of fusing identity and attribute information emanating from different sources, and to offer the decision maker a quantitative analysis based on statistical methodology that can enhance his/her decision making process regarding the identity of detected objects. Two identity information fusion architectures are discussed here. The first is concerned with the fusion of identity declarations where the sources are expected to provide only useful and complete results such as an identity declaration. The second is concerned with the fusion of attribute information using a modified version of the Dempster-Shafer evidential combination algorithm.

The research and development group at Loral Canada is now at the second phase of the development of a data fusion demonstration model (DFDM) for a naval anti-air warfare to be used as a workbench tool to perform exploratory research. This project has emphatically addressed how the concepts related to fusion could be implemented within the Canadian Patrol Frigate (CPF) software environment. The project has been designed to read data passively on the CPF bus without any modification to the CPF software. This has brought to light important time alignment issues since the CPF sensors and the CPF command and control system were not important time alignment issues since the CPF sensors and the CPF command and control system were not originally designed to support a track management function which fuses information. The fusion of data from non-organic sensors with the tactical Link-11 data has produced stimulating spatial alignment problems which have been overcome by the use of a geodetic referencing coordinate system. Some benchmark scenarios have been selected to quantitatively demonstrate the capabilities of this fusion implementation. This paper describes the implementation design of DFDM (version 2), and summarizes the results obtained so far when fusing the scenarios simulated data.

The research and development group at Loral Canada is in the second phase in the development of a data fusion demonstration model (DFDM) for a naval anti-air warfare platform to be used as a workbench tool to perform exploratory research. The software has been designed to be implemented within the software environment of the Canadian Patrol Frigate (CPF). The second version of DFDM has the capability to fuse data from the following CPF sensors: surveillance radars, electronics support measure, identification friend or foe, communication intercept operator and a tactical data link. During the first phase, the project has demonstrated the feasibility of fusing the sensor attribute information using a modified version of the Dempster-Shafer evidential combination algorithm. A significant enhancement has been the addition of pruning rules to reduce the set of identity propositions which otherwise would be too large to comply with the DFDM real- time requirements. Another improvement has been the use of fuzzy logic to make possible the fusion of apparently incomplete attribute information coming from different sensors. This paper describes the main features of the evidential combination algorithm that we have implemented in the DFDM system. A benchmark scenario has been selected to quantitatively demonstrate the capability of the attribute fusion algorithm.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Tracking algorithms commonly use practical models of target motion to estimate the target's kinematic quantities such as the position, the velocity and in certain cases, the acceleration. When there is a maneuver, the tracking algorithm should detect the error created by this change and correct the situation to adapt itself to this new change or new tracking model. There are different approaches in the literature for handling maneuver detection using different filtering techniques. A thorough literature survey about different types of filtering techniques used for maneuver detection has been performed. The focus of this study has been the parallel filtering techniques. Some of those techniques given by different authors are summarized in this paper. This paper presents a parallel filter design using three linear Kalman filters with a simple switching algorithm for maneuver detection selected for the Multi Sensor Data Fusion (MSDF) for an anti-air warfare (AAW) surveillance radar. This design is relatively simple compared to other parallel Kalman filter techniques and requires modest computer resources. The parallel filter design has been compared with a single Kalman filter design previously used. The simulation results have shown a great deal of improvement with parallel filtering, particularly in speed estimations and in filtering stability when a target is maneuvering.

The target tracking case, where radar and IRST contacts are fused at the central level fusion architecture, with special attention to the coordinate system, has been analyzed in this presentation. Tracking targets by fusing contacts from dissimilar sensors in a central level fusion process is acknowledged to be the most powerful tracking technique. This approach maximizes the synergy among the data, consequently the accuracy of the tracking. Among the various tactical possibilities offered by data fusion, this approach permits to perform accurate tracking when the platform is 'almost' electromagnetically silent. Tracking targets with sparse use of radar is possible only if the angle contacts obtained from passive sensors are fused optimally with the parsimonious and intermittent radar contact. Usually, the range and angle data provided by a surveillance radar permit to use cartesian coordinates and track with a conventional Kalman filter using linear target model and measurement model equations. On the other hand the nature of the angle-only data provided by a passive sensor does not permit to take advantage of the linear models and the IRST tracker provides ambiguous angle tracks. To benefit from central level fusion, the state estimation process in the fusion function must be performed in a coordinate system that accommodates the radar as well as the IRST contacts. A simple simulation is done in three dimensions and in three different coordinate systems: cartesian, spherical and modified spherical. The analysis shows the feasibility of data fusion in all three coordinate systems.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The 1960s were marked by the setting up of Medicare by federal and provincial governments in Canada. The official aim of this undertaking was to eliminate inequality of access to medical care, and in the first instance inequality on the basis of incomes. Governments were also concerned with inequality in the regional distribution of medical services. The objective of this paper is to document these two dimensions of accessibility to medical services as present in Quebec in 1991 in terms of household consumption of such services. Data for this study come from administrative files, principally those of the Quebec ministry of health. The paper reviews measures taken by the Quebec government to attract doctors to locate in outlying regions of the province. In spite of these measures, results obtained indicate that significant differences existed in 1991 between outlying and central regions and that results for intermediate regions occur between these two poles. After controlling for age of head and household composition, differences by income are no longer significant.

A case study in which the Dempster-Shafer evidential reasoning theory is applied to a naval identity and attribute fusion problem is described. Two identity information fusion architectures are discussed: the first concerns the fusion of identity declarations where the sources are expected to provide only useful and complete results such as an identity declaration, and the second architecture addresses the fusion of incomplete attribute information coming from various sources. The emphasis is put on the second architecture. The use of fuzzy logic for proposition generation is described as well as techniques for managing the number of propositions generated.