Background: Public databases such as the NCBI Gene Expression Omnibus contain extensive and exponentially increasing amounts of high-throughput data that can be applied to molecular phenotype characterization. Collect...
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Background: Public databases such as the NCBI Gene Expression Omnibus contain extensive and exponentially increasing amounts of high-throughput data that can be applied to molecular phenotype characterization. Collectively, these data can be analyzed for such purposes as disease diagnosis or phenotype classification. One family of algorithms that has proven useful for disease classification is based on relative expression analysis and includes the Top-Scoring Pair (TSP), k-Top-Scoring Pairs (k-TSP), Top-Scoring Triplet (TST) and Differential Rank Conservation (DIRAC) algorithms. These relative expression analysis algorithms hold significant advantages for identifying interpretable molecular signatures for disease classification, and have been implemented previously on a variety of computational platforms with varying degrees of usability. To increase the user-base and maximize the utility of these methods, we developed the program AUREA (Adaptive Unified Relative Expression Analyzer)-a cross-platform tool that has a consistent application programming interface (API), an easy-to-use graphical user interface (GUI), fast running times and automated parameter discovery. Results: Herein, we describe AUREA, an efficient, cohesive, and user-friendly open-source software system that comprises a suite of methods for relative expression analysis. AUREA incorporates existing methods, while extending their capabilities and bringing uniformity to their interfaces. We demonstrate that combining these algorithms and adaptively tuning parameters on the training sets makes these algorithms more consistent in their performance and demonstrate the effectiveness of our adaptive parameter tuner by comparing accuracy across diverse datasets. Conclusions: We have integrated several relative expression analysis algorithms and provided a unified interface for their implementation while making data acquisition, parameter fixing, data merging, and results analysis 'point- and -click' simple.
Middleware designed to describe sensing, control, and computational communications of components within unmanned systems enables the creation of clean interfaces between the low-level mechanics of such systems and the...
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Middleware designed to describe sensing, control, and computational communications of components within unmanned systems enables the creation of clean interfaces between the low-level mechanics of such systems and the higher-level logic designed to control them. This paper presents a modeling environment with a domain-specific ontology for autonomous systems, capable of generating software necessary for intercomputer communications according to existing autonomous systems middleware standards. Metamodels are used to specify the domain-specific modeling language to model the messages used, the interfaces between components, and some of the functionality of the components that transmit and receive messages. The generated code supports the high data rates expected in autonomous systems that use lossy message compression. Tests for the messaging infrastructure are also generated for the messages. Also, using this research, this code generation process can be extended to any component-based platform with a similar ontology. The case study and test environment for the software generated by this project is an autonomous ground vehicle, modeled on a Ford Escape Hybrid and used in laboratory experiments.
This paper presents a new spacecraft attitude determination system based on small optical devices and Linux-based software. This technology intends to support nanosatellite operations by providing low-cost, low-mass, ...
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This paper presents a new spacecraft attitude determination system based on small optical devices and Linux-based software. This technology intends to support nanosatellite operations by providing low-cost, low-mass, low-volume, low-power, and redundant attitude determination capabilities with quick and straightforward onboard programmability for real-time spacecraft operations. The chosen commercial-off-the-shelf optical devices perform sensing and image processing on the same circuit board, and they are biologically inspired by insects' vision systems, which measure optical flow and/or track objects while navigating the environment. The firmware on the devices is modified here to enable communication with PC/104 form-factor embedded computers running RealTime applicationinterface for Linux. Algorithms are developed for operations using optical flow mode and point-tracking mode, and an application programming interface, along with Simulink(R) S-functions, is created. The performances of the proposed system, used in optical flow mode, point-tracking mode, and a combination of the two, are assessed using a spacecraft simulator at Rensselaer Polytechnic Institute, and they are compared with measurements from the PhaseSpace(R) motion-tracking system.
A software interface between the MATLAB/Simulink environment and the Satellite Tool Kit Environment is introduced. This research is based on the need for validating model performance and visualizing simultaneous multi...
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A software interface between the MATLAB/Simulink environment and the Satellite Tool Kit Environment is introduced. This research is based on the need for validating model performance and visualizing simultaneous multiple-spacecraft proximity maneuvers for emerging missions. It is common for spacecraft systems to be modeled with MATLAB and Simulink. Furthermore, the software package Satellite Tool Kit is often used for animating and evaluating spacecraft maneuvers. In this research, a MATLAB/Satellite Tool Kit interface was developed to propagate six-degree-of-freedom spacecraft models, compared against Satellite-Tool-Kit-generated ephemeris, and animated for analysis. MATLAB script with necessary formatting is used for Satellite Tool Kit initialization and animation. The MATLAB/Satellite Tool Kit simulation interface allows variations in number, shape, and dimensions of spacecraft. Additionally, numerous model and simulation parameters can be selected and synchronized between MATLAB and Satellite Tool Kit. Furthermore, either predetermined, or randomly distributed, initial spacecraft positions and orientations are permitted by the interface. The paper gives enough details to allow the interested readers to adapt to their needs and further develop the proposed software interface.
A new area-based distributed mobile cache system, a sustainable distributed Geocast technology, enables data caching temporarily in a designated local area using short-range communication technologies such as WiFi and...
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A new area-based distributed mobile cache system, a sustainable distributed Geocast technology, enables data caching temporarily in a designated local area using short-range communication technologies such as WiFi and Bluetooth. This system needs no infrastructure network and servers. This caching capability and mechanisms are expected to enhance short-range communications as a time-offset communication in a physical world. For that reason, it is sure to accelerate new location-based communication services. This paper reports a developed middleware for a widespread embedded operating system, and a software development kit with an open application programming interface. This middleware is expected to spur third-party developers to produce widely various applications using this proposed platform. Some pseudo-code is provided. Procedures to use this platform are also explained using an implemented geo-location social game(1).
Feature point matching is an important step for many vision-based unmanned-aerial-vehicle applications. This paper presents the development of a new feature descriptor for feature point matching that is well suited fo...
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Feature point matching is an important step for many vision-based unmanned-aerial-vehicle applications. This paper presents the development of a new feature descriptor for feature point matching that is well suited for micro unmanned aerial vehicles equipped with a low-resource, compact, lightweight, low-power embedded vision sensor. The Basis Sparse-Coding Inspired Similarity descriptor uses theory taken from sparse coding to provide an efficient image feature description method for frame-to-frame feature point matching. This descriptor requires simple mathematical operations, uses comparatively small memory storage, and can support color and grayscale feature descriptions. It is an excellent candidate for implementation on low-resource systems that require real-time performance, where complex mathematical operations are prohibitively expensive. To demonstrate its performance, the feature matching result was used to calculate a frame-to-frame homography that is essential to unmanned-aerial-vehicle applications such as pose estimation and obstacle detection for navigation. The proposed descriptor was tested on two video sequences and one dataset of real aerial images. Experimental results show that, along with performing in situations where existing complex descriptors cannot be used, the Basis Sparse-Coding Inspired Similarity descriptor also performs slightly better than these other methods on the task of homography calculation. Our experimental results and analysis show that the Basis Sparse-Coding Inspired Similarity descriptor is an excellent candidate for a resource-limited vision sensor for micro unmanned aerial vehicles.
Mobile GPUs will need substantial improvements to enable wireless devices to perform the complex graphics-related functions that many manufacturers, developers, and users want.
Mobile GPUs will need substantial improvements to enable wireless devices to perform the complex graphics-related functions that many manufacturers, developers, and users want.
Businesses are increasingly using location analytics-which integrates organizational and geographic data-to help identify trends, develop more accurate predictions, and make better decisions.
Businesses are increasingly using location analytics-which integrates organizational and geographic data-to help identify trends, develop more accurate predictions, and make better decisions.
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