Toward Sensor Modular Autonomy for Persistent Land Intelligence Surveillance and Reconnaissance (ISR)

Currently, most land Intelligence, Surveillance and Reconnaissance (ISR) assets (e.g. EO/IR cameras) are simply data collectors. Understanding, decision making and sensor control are performed by the human operators, involving high cognitive load. Any automation in the system has traditionally involved bespoke design of centralised systems that are highly specific for the assets/targets/environment under consideration, resulting in complex, non-flexible systems that exhibit poor interoperability. We address a concept of Autonomous Sensor Modules (ASMs) for land ISR, where these modules have the ability to make low-level decisions on their own in order to fulfil a higher-level objective, and plug in, with the minimum of preconfiguration, to a High Level Decision Making Module (HLDMM) through a middleware integration layer. The dual requisites of autonomy and interoperability create challenges around information fusion and asset management in an autonomous hierarchical system, which are addressed in this work. This paper presents the results of a demonstration system, known as Sensing for Asset Protection with Integrated Electronic Networked Technology (SAPIENT), which was shown in realistic base protection scenarios with live sensors and targets. The SAPIENT system performed sensor cueing, intelligent fusion, sensor tasking, target hand-off and compensation for compromised sensors, without human control, and enabled rapid integration of ISR assets at the time of system deployment, rather than at design-time. Potential benefits include rapid interoperability for coalition operations, situation understanding with low operator cognitive burden and autonomous sensor management in heterogenous sensor systems

An Osteoblast-Derived Proteinase Controls Tumor Cell Survival via TGF-beta Activation in the Bone Microenvironment

Breast to bone metastases frequently induce a "vicious cycle" in which osteoclast mediated bone resorption and proteolysis results in the release of bone matrix sequestered factors that drive tumor growth. While osteoclasts express numerous proteinases, analysis of human breast to bone metastases unexpectedly revealed that bone forming osteoblasts were consistently positive for the proteinase, MMP-2. Given the role of MMP-2 in extracellular matrix degradation and growth factor/cytokine processing, we tested whether osteoblast derived MMP-2 contributed to the vicious cycle of tumor progression in the bone microenvironment.To test our hypothesis, we utilized murine models of the osteolytic tumor-bone microenvironment in immunocompetent wild type and MMP-2 null mice. In longitudinal studies, we found that host MMP-2 significantly contributed to tumor progression in bone by protecting against apoptosis and promoting cancer cell survival (caspase-3; immunohistochemistry). Our data also indicate that host MMP-2 contributes to tumor induced osteolysis (μCT, histomorphometry). Further ex vivo/in vitro experiments with wild type and MMP-2 null osteoclast and osteoblast cultures identified that 1) the absence of MMP-2 did not have a deleterious effect on osteoclast function (cd11B isolation, osteoclast differentiation, transwell migration and dentin resorption assay); and 2) that osteoblast derived MMP-2 promoted tumor survival by regulating the bioavailability of TGFβ, a factor critical for cell-cell communication in the bone (ELISA, immunoblot assay, clonal and soft agar assays).Collectively, these studies identify a novel "mini-vicious cycle" between the osteoblast and metastatic cancer cells that is key for initial tumor survival in the bone microenvironment. In conclusion, the findings of our study suggest that the targeted inhibition of MMP-2 and/or TGFβ would be beneficial for the treatment of bone metastases

CONSIDERING VIDEO AS A VOLUME

We present an alternative approach to viewing video information. Video frames can be combined to form a volume in much the same way that medical CT images can be processed. Once the volume has been formed, techniques from medical imaging can be applied and novel views and data visualization of the original video data obtained.

AN EVALUATION OF IMAGE DENOISING TECHNIQUES APPLIED TO CT BAGGAGE SCREENING IMAGERY

This paper investigates the efficacy of several popular denoising methods in the previously unconsidered context of Computed Tomography (CT) baggage imagery. The performance of a dedicated CT baggage denoising approach (alpha-weighted mean separation and histogram equalisation) is compared to the following popular denoising techniques: anisotropic diffusion; total variation denoising; bilateral filtering; translation invariant wavelet shrinkage and non-local means filtering. In addition to a standard qualitative performance analysis (visual comparisons), denoising performance is evaluated with a recently developed 3D SIFT-based analysis technique that quantifies the impact of denoising on the implementation of automated 3D object recognition. The study yields encouraging results in both the qualitative and quantitative analyses, with wavelet thresholding producing the most satisfactory results. The results serve as a strong indication that simple denoising will aid human and computerised analyses of 3D CT baggage imagery for transport security screening. Index Terms — Image denoising, baggage CT, 3D SIFT 1