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Evaluation methods for the autonomy of unmanned systems
YueChao Wang,JinGuo Liu
Chinese Science Bulletin , 2012, DOI: 10.1007/s11434-012-5183-2
Abstract: Future military and civilian unmanned systems will be extensively used on land, under the sea, in air, and in space. Evaluation of their autonomy is critical to realize the autonomous operation ability of unmanned systems. This paper discussed the basic concepts of autonomy and the significance of autonomy evaluation, and then surveys and describes existing evaluating methods. Based on analyses of key technologies and these technologies’ technical readiness levels, a cobweb evaluation model as a universal evaluation model has been used to evaluate unmanned systems. If the technology warps (aspects of autonomy) and wefts (levels of those aspects) of unmanned systems can be determined for the cobweb model, the model can handle the mutual coupling, high dimensions, and diversity of warp lines. This model potentially has wide application in evaluating various unmanned systems.
Integrated Simulation Environment for Unmanned Autonomous Systems—Towards a Conceptual Framework  [PDF]
M. G. Perhinschi,M. R. Napolitano,S. Tamayo
Modelling and Simulation in Engineering , 2010, DOI: 10.1155/2010/736201
Abstract: The paper initiates a comprehensive conceptual framework for an integrated simulation environment for unmanned autonomous systems (UAS) that is capable of supporting the design, analysis, testing, and evaluation from a “system of systems” perspective. The paper also investigates the current state of the art of modeling and performance assessment of UAS and their components and identifies directions for future developments. All the components of a comprehensive simulation environment focused on the testing and evaluation of UAS are identified and defined through detailed analysis of current and future required capabilities and performance. The generality and completeness of the simulation environment is ensured by including all operational domains, types of agents, external systems, missions, and interactions between components. The conceptual framework for the simulation environment is formulated with flexibility, modularity, generality, and portability as key objectives. The development of the conceptual framework for the UAS simulation reveals important aspects related to the mechanisms and interactions that determine specific UAS characteristics including complexity, adaptability, synergy, and high impact of artificial and human intelligence on system performance and effectiveness. 1. Introduction The increasing need of avoiding the exposure of humans to “dull, dirty, or dangerous” [1] missions in conjunction with the sustained multidisciplinary technological progress in the past two decades is the main reasons behind the exponential growth rate in the development, deployment, and operation of unmanned autonomous systems (UASs). More than twenty countries have invested substantial resources towards the development and the manufacturing UASs for a wide range of applications, both in the military and civilian domains [2]. Although human personnel are part of the overall system, the UAS includes as primary component one or several unmanned vehicles (UVs) accomplishing their role within the mission with different levels of autonomy, ranging from remote control to fully automated mission completion [3, 4] including adaptation and decision making in response to changing operational conditions. Most UAS applications rely on aerial vehicles (UAVs); however, land, maritime, and space vehicles are also commonly used fulfilling primary or secondary roles within the system. The US military has currently more than 3 dozens of UAV platforms in service [1] ranging from small size to full size aircraft with different propulsion systems, including fixed wing UVs,
Sunglint Detection for Unmanned and Automated Platforms  [PDF]
Shungudzemwoyo Pascal Garaba,Jan Schulz,Marcel Robert Wernand,Oliver Zielinski
Sensors , 2012, DOI: 10.3390/s120912545
Abstract: We present an empirical quality control protocol for above-water radiometric sampling focussing on identifying sunglint situations. Using hyperspectral radiometers, measurements were taken on an automated and unmanned seaborne platform in northwest European shelf seas. In parallel, a camera system was used to capture sea surface and sky images of the investigated points. The quality control consists of meteorological flags, to mask dusk, dawn, precipitation and low light conditions, utilizing incoming solar irradiance (ES) spectra. Using 629 from a total of 3,121 spectral measurements that passed the test conditions of the meteorological flagging, a new sunglint flag was developed. To predict sunglint conspicuous in the simultaneously available sea surface images a sunglint image detection algorithm was developed and implemented. Applying this algorithm, two sets of data, one with (having too much or detectable white pixels or sunglint) and one without sunglint (having least visible/detectable white pixel or sunglint), were derived. To identify the most effective sunglint flagging criteria we evaluated the spectral characteristics of these two data sets using water leaving radiance (LW) and remote sensing reflectance (RRS). Spectral conditions satisfying ‘mean LW (700–950 nm) < 2 mW?m?2?nm?1?Sr?1’ or alternatively ‘minimum RRS (700–950 nm) < 0.010 Sr?1’, mask most measurements affected by sunglint, providing an efficient empirical flagging of sunglint in automated quality control.
Multilevel communication optimal LU and QR factorizations for hierarchical platforms  [PDF]
Laura Grigori,Mathias Jacquelin,Amal Khabou
Computer Science , 2013,
Abstract: This study focuses on the performance of two classical dense linear algebra algorithms, the LU and the QR factorizations, on multilevel hierarchical platforms. We first introduce a new model called Hierarchical Cluster Platform (HCP), encapsulating the characteristics of such platforms. The focus is set on reducing the communication requirements of studied algorithms at each level of the hierarchy. Lower bounds on communications are therefore extended with respect to the HCP model. We then introduce multilevel LU and QR algorithms tailored for those platforms, and provide a detailed performance analysis. We also provide a set of numerical experiments and performance predictions demonstrating the need for such algorithms on large platforms.
Hierarchical Parallel Matrix Multiplication on Large-Scale Distributed Memory Platforms  [PDF]
Jean-Noel Quintin,Khalid Hasanov,Alexey Lastovetsky
Computer Science , 2013,
Abstract: Matrix multiplication is a very important computation kernel both in its own right as a building block of many scientific applications and as a popular representative for other scientific applications. Cannon algorithm which dates back to 1969 was the first efficient algorithm for parallel matrix multiplication providing theoretically optimal communication cost. However this algorithm requires a square number of processors. In the mid 1990s, the SUMMA algorithm was introduced. SUMMA overcomes the shortcomings of Cannon algorithm as it can be used on a non-square number of processors as well. Since then the number of processors in HPC platforms has increased by two orders of magnitude making the contribution of communication in the overall execution time more significant. Therefore, the state of the art parallel matrix multiplication algorithms should be revisited to reduce the communication cost further. This paper introduces a new parallel matrix multiplication algorithm, Hierarchical SUMMA (HSUMMA), which is a redesign of SUMMA. Our algorithm reduces the communication cost of SUMMA by introducing a two-level virtual hierarchy into the two-dimensional arrangement of processors. Experiments on an IBM BlueGene-P demonstrate the reduction of communication cost up to 2.08 times on 2048 cores and up to 5.89 times on 16384 cores.
Trust Levels Definition On Virtual Learning Platforms Through Semantic Languages
Paulo A. Gaona-Garcia,Jesús Soto-Carrión,Carlos E. Montenegro-Marin
International Journal of Interactive Multimedia and Artificial Intelligence , 2010,
Abstract: Trust level concept is a topic that has opened a knowledge area about the profile evaluation and the people participation in Social Networks. These have presented a high knowledge profit, but at the same time it is necessary to analyze a group of variables to determine the trust participants’ degree.In addition, this is a topic that from some years ago has been presenting a big expectation to settle some alternatives to generate confidence in an activer community on internet. To establish these parameters it is important to define a model to abstract some variables that are involved in this process. For this, it is relevant to take into account the semantic languages as one of the alternatives that allow these kinds of activities. The purpose of this article is to analyze the Trust Levels definition in the contents that are shared on Open Source Virtual learning Platforms through the use of a model of representation of semantic languages. The last ones allow determining the trust in the use of learning objects that are shared in this kind of platforms
High-throughput Execution of Hierarchical Analysis Pipelines on Hybrid Cluster Platforms  [PDF]
George Teodoro,Tony Pan,Tahsin M. Kurc,Jun Kong,Lee A. D. Cooper,Joel H. Saltz
Computer Science , 2012,
Abstract: We propose, implement, and experimentally evaluate a runtime middleware to support high-throughput execution on hybrid cluster machines of large-scale analysis applications. A hybrid cluster machine consists of computation nodes which have multiple CPUs and general purpose graphics processing units (GPUs). Our work targets scientific analysis applications in which datasets are processed in application-specific data chunks, and the processing of a data chunk is expressed as a hierarchical pipeline of operations. The proposed middleware system combines a bag-of-tasks style execution with coarse-grain dataflow execution. Data chunks and associated data processing pipelines are scheduled across cluster nodes using a demand driven approach, while within a node operations in a given pipeline instance are scheduled across CPUs and GPUs. The runtime system implements several optimizations, including performance aware task scheduling, architecture aware process placement, data locality conscious task assignment, and data prefetching and asynchronous data copy, to maximize utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. The application and performance benefits of the runtime middleware are demonstrated using an image analysis application, which is employed in a brain cancer study, on a state-of-the-art hybrid cluster in which each node has two 6-core CPUs and three GPUs. Our results show that implementing and scheduling application data processing as a set of fine-grain operations provide more opportunities for runtime optimizations and attain better performance than a coarser-grain, monolithic implementation. The proposed runtime system can achieve high-throughput processing of large datasets - we were able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles at about 150 tiles/second rate on 100 nodes.
Rejoinder: Bayesian Checking of the Second Levels of Hierarchical Models  [PDF]
M. J. Bayarri,M. E. Castellanos
Statistics , 2008, DOI: 10.1214/07-STS235REJ
Abstract: Rejoinder: Bayesian Checking of the Second Levels of Hierarchical Models [arXiv:0802.0743]
Comment: Bayesian Checking of the Second Levels of Hierarchical Models  [PDF]
Valen E. Johnson
Statistics , 2008, DOI: 10.1214/07-STS235D
Abstract: Comment: Bayesian Checking of the Second Levels of Hierarchical Models [arXiv:0802.0743]
Comment: Bayesian Checking of the Second Levels of Hierarchical Models  [PDF]
Andrew Gelman
Statistics , 2008, DOI: 10.1214/07-STS235A
Abstract: Comment: Bayesian Checking of the Second Levels of Hierarchical Models [arXiv:0802.0743]
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