Biblio

Robots operating alongside humans in field environments have the potential to greatly increase the situational awareness of their human teammates. A significant challenge, however, is the efficient conveyance of what the robot perceives to the human in order to achieve improved situational awareness. We believe augmented reality (AR), which allows a human to simultaneously perceive the real world and digital information situated virtually in the real world, has the potential to address this issue. We propose to demonstrate that augmented reality can be used to enable human-robot cooperative search, where the robot can both share search results and assist the human teammate in navigating to a search target.

Fast, accurate three dimensional reconstructions of plasma equilibria, crucial for physics interpretation of fusion data generated within confinement devices like stellarators/ tokamaks, are computationally very expensive and routinely require days, even weeks, to complete using serial approaches. Here, we present a parallel implementation of the three dimensional plasma reconstruction code, V3FIT. A formal analysis to identify the performance bottlenecks and scalability limits of this new parallel implementation, which combines both task and data parallelism, is presented. The theoretical findings are supported by empirical performance results on several thousands of processor cores of a Cray XC30 supercomputer. Parallel V3FIT is shown to deliver over 40X speedup, enabling fusion scientists to carry out three dimensional plasma equilibrium reconstructions at unprecedented scales in only a few hours (instead of in days/weeks) for the first time.

3D steganography is used in order to embed or hide information into 3D objects without causing visible or machine detectable modifications. In this paper we rethink about a high capacity 3D steganography based on the Hamiltonian path quantization, and increase its resistance to steganalysis. We analyze the parameters that may influence the distortion of a 3D shape as well as the resistance of the steganography to 3D steganalysis. According to the experimental results, the proposed high capacity 3D steganographic method has an increased resistance to steganalysis.

This paper establishes a probability model of multiple paths scheme of quantum key distribution with public nodes among a set of paths which are used to transmit the key between the source node and the destination node. Then in order to be used in universal net topologies, combining with the key routing in the QKD network, the algorithm of the multiple paths scheme of key distribution we propose includes two major aspects: one is an approach which can confirm the number and the distance of the selection of paths, and the other is the strategy of stochastic paths with labels that can decrease the number of public nodes and avoid the phenomenon that the old scheme may produce loops and often get the nodes apart from the destination node father than current nodes. Finally, the paper demonstrates the rationality of the probability model and strategies about the algorithm.

Cloud computing emerged in the last years to handle systems with large-scale services sharing between vast numbers of users. It provides enormous storage for data and computing power to users over the Internet. There are many issues with the high growth of data. Data security is one of the most important issues in cloud computing. There are many algorithms and implementation for data security. These algorithms provided various encryption methods. In this work, We present a comprehensive study between Symmetric key and Asymmetric key encryption algorithms that enhanced data security in cloud computing system. We discuss AES, DES, 3DES and Blowfish for symmetric encryption algorithms, and RSA, DSA, Diffie-Hellman and Elliptic Curve, for asymmetric encryption algorithms.

The advancement in technology has changed how people work and what software and hardware people use. From conventional personal computer to GPU, hardware technology and capability have dramatically improved so does the operating systems that come along. Unfortunately, current industry practice to compare OS is performed with single perspective. It is either benchmark the hardware level performance or performs penetration testing to check the security features of an OS. This rigid method of benchmarking does not really reflect the true performance of an OS as the performance analysis is not comprehensive and conclusive. To illustrate this deficiency, the study performed hardware level and operational level benchmarking on Windows XP, Windows 7 and Windows 8 and the results indicate that there are instances where Windows XP excels over its newer counterparts. Overall, the research shows Windows 8 is a superior OS in comparison to its predecessors running on the same hardware. Furthermore, the findings also show that the automated benchmarking tools are proved less efficient benchmark systems that run on Windows XP and older OS as they do not support DirectX 11 and other advanced features that the hardware supports. There lies the need to have a unified benchmarking approach to compare other aspects of OS such as user oriented tasks and security parameters to provide a complete comparison. Therefore, this paper is proposing a unified approach for Operating System (OS) comparisons with the help of a Windows OS case study. This unified approach includes comparison of OS from three aspects which are; hardware level, operational level performance and security tests.

The symmetric block ciphers, which represent a core element for building cryptographic communications systems and protocols, are used in providing message confidentiality, authentication and integrity. Various limitations in hardware and software resources, especially in terminal devices used in mobile communications, affect the selection of appropriate cryptosystem and its parameters. In this paper, an implementation of three symmetric ciphers (DES, 3DES, AES) used in different operating modes are analyzed on Android platform. The cryptosystems' performance is analyzed in different scenarios using several variable parameters: cipher, key size, plaintext size and number of threads. Also, the influence of parallelization supported by multi-core CPUs on cryptosystem performance is analyzed. Finally, some conclusions about the parameter selection for optimal efficiency are given.

This paper introduces SONA (Spatiotemporal system Organized for Natural Analysis), a tabletop and tangible controller system for exploring geotagged information, and more specifically, CCTV. SONA's goal is to support a more natural method of interacting with data. Our new interactions are placed in the context of a physical security environment, closed circuit television (CCTV). We present a three-layered detail on demand set of view filters for CCTV feeds on a digital map. These filters are controlled with a novel tangible device for direct interaction. We validate SONA's tangible controller approach with a user study comparing SONA with the existing CCTV multi-screen method. The results of the study show that SONA's tangible interaction method is superior to the multi-screen approach, both in terms of quantitative results, and is preferred by users.

This paper describes an experiment carried out to demonstrate robustness and trustworthiness of an orchestrated two-layer network test-bed (PROnet). A Robotic Operating System Industrial (ROS-I) distributed application makes use of end-to-end flow services offered by PROnet. The PROnet Orchestrator is used to provision reliable end-to-end Ethernet flows to support the ROS-I application required data exchange. For maximum reliability, the Orchestrator provisions network resource redundancy at both layers, i.e., Ethernet and optical. Experimental results show that the robotic application is not interrupted by a fiber outage.

3D imaging has been a hot research topic recently due to a high demand from various applications of security, health, autonomous vehicle and robotics. Yet Stereoscopic 3D imaging is limited due to its principles which mimics the human eye technique thus the camera separation baseline defines amount of 3D depth can be captured. Holoscopic 3D (H3D) Imaging is based on the “Fly's eye” technique that uses coherent replication of light to record a spatial image of a real scene using a microlens array (MLA) which gives the complete 3D parallax. H3D Imaging has been considered a promising 3D imaging technique which pursues the simple form of 3D acquisition using a single aperture camera therefore it is the most suited for scalable digitization, security and autonomous applications. This paper proposes 360-degree holoscopic 3D imaging system design for immersive 3D acquisition and stitching.

This paper presents software visualization tool that utilizes the modified city metaphor to represent software system and related analysis data in virtual reality environment. To better address all three kinds of software aspects we propose a new layouting algorithm that provides a higher level of detail and position the buildings according to the coupling between classes that they represent. Resulting layout allows us to visualize software metrics and source code modifications at the granularity of methods, visualize method invocations involved in program execution and to support the remodularization analysis. To further reduce the cognitive load and increase efficiency of 3D visualization we allow users to observe and interact with our city in immersive virtual reality environment that also provides a source code browsing feature. We demonstrate the use of our approach on two open-source systems.

The Internet of Things (IoT) has become ubiquitous in our daily life as billions of devices are connected through the Internet infrastructure. However, the rapid increase of IoT devices brings many non-traditional challenges for system design and implementation. In this paper, we focus on the hardware security vulnerabilities and ultra-low power design requirement of IoT devices. We briefly survey the existing design methods to address these issues. Then we propose an approximate computing based information hiding approach that provides security with low power. We demonstrate that this security primitive can be applied for security applications such as digital watermarking, fingerprinting, device authentication, and lightweight encryption.

Many aspects of our daily lives now rely on computers, including communications, transportation, government, finance, medicine, and education. However, with increased dependence comes increased vulnerability. Therefore recognizing attacks quickly is critical. In this paper, we introduce a new anomaly detection algorithm based on persistent homology, a tool which computes summary statistics of a manifold. The idea is to represent a cyber network with a dynamic point cloud and compare the statistics over time. The robustness of persistent homology makes for a very strong comparison invariant.

The prevalence of wireless networks and the convenience of mobile cameras enable many new video applications other than security and entertainment. From behavioral diagnosis to wellness monitoring, cameras are increasing used for observations in various educational and medical settings. Videos collected for such applications are considered protected health information under privacy laws in many countries. At the same time, there is an increasing need to share such video data across a wide spectrum of stakeholders including professionals, therapists and families facing similar challenges. Visual privacy protection techniques, such as blurring or object removal, can be used to mitigate privacy concern, but they also obliterate important visual cues of affect and social behaviors that are crucial for the target applications. In this paper, we propose a method of manipulating facial expression and body shape to conceal the identity of individuals while preserving the underlying affect states. The experiment results demonstrate the effectiveness of our method.

This paper describes Smartpig, an algorithm for the iterative mosaicking of images of a planar surface using a unique parameterization which decomposes inter-image projective warps into camera intrinsics, fronto-parallel projections, and inter-image similarities. The constraints resulting from the inter-image alignments within an image set are stored in an undirected graph structure allowing efficient optimization of image projections on the plane. Camera pose is also directly recoverable from the graph, making Smartpig a feasible solution to the problem of simultaneous location and mapping (SLAM). Smartpig is demonstrated on a set of 144 high resolution aerial images and evaluated with a number of metrics against ground control.

Most Depth Image Based Rendering (DIBR) techniques produce synthesized images which contain non-uniform geometric distortions affecting edges coherency. This type of distortions are challenging for common image quality metrics. Morphological filters maintain important geometric information such as edges across different resolution levels. There is inherent congruence between the morphological pyramid decomposition scheme and human visual perception. In this paper, multi-scale measure, morphological pyramid peak signal-to-noise ratio MP-PSNR, based on morphological pyramid decomposition is proposed for the evaluation of DIBR synthesized images. It is shown that MPPSNR achieves much higher correlation with human judgment compared to the state-of-the-art image quality measures in this context.

We propose a dense continuous-time tracking and mapping method for RGB-D cameras. We parametrize the camera trajectory using continuous B-splines and optimize the trajectory through dense, direct image alignment. Our method also directly models rolling shutter in both RGB and depth images within the optimization, which improves tracking and reconstruction quality for low-cost CMOS sensors. Using a continuous trajectory representation has a number of advantages over a discrete-time representation (e.g. camera poses at the frame interval). With splines, less variables need to be optimized than with a discrete representation, since the trajectory can be represented with fewer control points than frames. Splines also naturally include smoothness constraints on derivatives of the trajectory estimate. Finally, the continuous trajectory representation allows to compensate for rolling shutter effects, since a pose estimate is available at any exposure time of an image. Our approach demonstrates superior quality in tracking and reconstruction compared to approaches with discrete-time or global shutter assumptions.

Mobile and aerial robots used in urban search and rescue (USAR) operations have shown the potential for allowing us to explore, survey and assess collapsed structures effectively at a safe distance. RGB-D cameras, such as the Microsoft Kinect, allow us to capture 3D depth data in addition to RGB images, providing a significantly richer user experience than flat video, which may provide improved situational awareness for first responders. However, the richer data comes at a higher cost in terms of data throughput and computing power requirements. In this paper we consider the problem of live streaming RGB-D data over wired and wireless communication channels, using low-power, embedded computing equipment. When assessing a disaster environment, a range camera is typically mounted on a ground or aerial robot along with the onboard computer system. Ground robots can use both wireless radio and tethers for communications, whereas aerial robots can only use wireless communication. We propose a hybrid lossless and lossy streaming compression format designed specifically for RGB-D data and investigate the feasibility and usefulness of live-streaming this data in disaster situations.