scholarly journals Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data

2008 ◽  
Vol 5 (1) ◽  
pp. 57-71 ◽  
Author(s):  
Nicola Segata ◽  
Enrico Blanzieri ◽  
Corrado Priami
Keyword(s):  
Gene Expression ◽  
Systems Biology ◽  
High Throughput ◽  
System Level ◽  
Expression Data ◽  
Differential Analysis ◽  
Computational Systems Biology ◽  
Microarray Gene Expression ◽  
High Throughput Data ◽  
Computational Systems

Summary The paradigmatic shift occurred in biology that led first to high-throughput experimental techniques and later to computational systems biology must be applied also to the analysis paradigm of the relation between local models and data to obtain an effective prediction tool. In this work we introduce a unifying notational framework for systems biology models and high-throughput data in order to allow new integrations on the systemic scale like the use of in silico predictions to support the mining of gene expression datasets. Using the framework, we propose two applications concerning the use of system level models to support the differential analysis of microarray expression data. We tested the potentialities of the approach with a specific microarray experiment on the phosphate system in Saccharomyces cerevisiae and a computational model of the PHO pathway that supports the systems biology concepts.

Application of Multidisciplinary Design Optimization to a Resource Satellite

2012 ◽  
Vol 195-196 ◽  
pp. 1066-1077
Author(s):  
Wen Rui Wu ◽  
Hai Huang ◽  
Bei Bei Wu
Keyword(s):  
Design Optimization ◽  
System Design ◽  
Multidisciplinary Design Optimization ◽  
Research Work ◽  
Thermal Control ◽  
Satellite System ◽  
Collaborative Optimization ◽  
System Level ◽  
Multidisciplinary Design ◽  
Satellite Mission

Satellite system design is a process involving various branches of knowledge, in which the designer usually needs to tradeoff many essentials and takes remarkable time. While multidisciplinary design optimization (MDO) method provides an effective approach for complicated system design, it seems especially suitable for such kind design purpose. By applying MDO in satellite system design, the efficiency of design can be expected to be improved and powerful technical supports can be obtained, which means better performance, faster design process and lower cost. According to the Resource satellite mission, width of ground cover and ground resolution are taken as the performance measurement, which combined with total mass of satellite is accounted in the optimization objective in system level. The design variables and constraints of the problem are dealt with disciplines or subsystems such as GNC, power, structure and thermal control. Corresponding analysis modules close to practical engineering are modeled. A MDO program system is developed by integrating collaborative optimization (CO) methods in iSIGHT. The result shows that the comprehensive objective can be improved, which also indicates MDO is feasible and efficient to solve the spacecraft design problem. The technology can be consulted for further research work.

scholarly journals AIOSAT - Autonomous Indoor & Outdoor Safety Tracking System

2019 ◽  
Vol 26 (1) ◽  
pp. 21-32
Author(s):  
Iñigo Adin ◽  
Paul Zabalegui ◽  
Alejandro Perez ◽  
Jaione Arrizabalaga ◽  
Jon Goya ◽  
...  
Keyword(s):  
Rural Areas ◽  
Tracking System ◽  
Dead Reckoning ◽  
Wide Band ◽  
Satellite System ◽  
System Level ◽  
Horizon 2020 ◽  
Rescue Workers ◽  
Global Navigation Satellite ◽  
Map Data

Abstract Even though satellite-based positioning increases rescue workers’ safety and efficiency, signal availability, reliability, and accuracy are often poor during fire operations, due to terrain formation, natural and structural obstacles or even the conditions of the operation. In central Europe, the stakeholders report a strong necessity to complement the location for mixed indoor-outdoor and GNSS blocked scenarios. As such, location information often needs to be augmented. For that, European Global Navigation Satellite System Galileo could help by improving the availability of the satellites with different features. Moreover, a multi-sensored collaborative system could also take advantage of the rescue personnel who are already involved in firefighting and complement the input data for positioning. The Autonomous Indoor & Outdoor Safety Tracking System (AIOSAT) is a multinational project founded through the Horizon 2020 program, with seven partners from Spain, Netherlands and Belgium. It is reaching the first year of progress (out of 3) and the overarching objective of AIOSAT system is to advance beyond the state of the art in tracking rescue workers by creating a high availability and high integrity team positioning and tracking system. On the system level approach, this goal is achieved by fusing the GNSS, EDAS/EGNOS, pedestrian dead reckoning and ultra-wide band ranging information, possibly augmented with map data. The system should be able to work both inside buildings and rural areas, which are the test cases defined by the final users involved in the consortium and the advisory board panel of the project

scholarly journals Blind Spoofing GNSS Constellation Detection Using a Multi-Antenna Snapshot Receiver

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5439
Author(s):  
Johannes Rossouw van der Merwe ◽  
Alexander Rügamer ◽  
Wolfgang Felber
Keyword(s):  
Clustering Algorithms ◽  
Satellite System ◽  
System Level ◽  
Navigation Satellite ◽  
Positioning Systems ◽  
Test Setup ◽  
Counter Method ◽  
Eigen Decomposition ◽  
Global Navigation Satellite ◽  
Gnss Constellation

Spoofing of global navigation satellite system (GNSS) signals threatens positioning systems. A counter-method is to detect the presence of spoofed signals, followed by a warning to the user. In this paper, a multi-antenna snapshot receiver is presented to detect the presence of a spoofing attack. The spatial similarities of the array steering vectors are analyzed, and different metrics are used to establish possible detector functions. These include subset methods, Eigen-decomposition, and clustering algorithms. The results generated within controlled spoofing conditions show that a spoofed constellation of GNSS satellites can be successfully detected. The derived system-level detectors increase performance in comparison to pair-wise methods. A controlled test setup achieved perfect detection; however, in real-world cases, the performance would not be as ideal. Some detection metrics and features for blind spoofing detecting, with an array of antennas, are identified, which opens the field for future advanced multi-detector developments.

High-Throughput, Resource-Efficient Multi-Dimensional Parallel Architecture for Space-Borne Sea-Land Segmentation

2020 ◽  
pp. 2150027
Author(s):  
Cunguang Zhang ◽  
Hongxun Jiang ◽  
Riwei Pan ◽  
Haiheng Cao ◽  
Mingliang Zhou
Keyword(s):  
Remote Sensing ◽  
High Throughput ◽  
Large Scale ◽  
Parallel Architecture ◽  
Remote Sensing Image ◽  
Satellite System ◽  
Peak Performance ◽  
Remote Sensing Images ◽  
Block Level ◽  
Remote Sensing Image Processing

Sea-land segmentation based on edge detection is commonly utilized in ship detection, coastline extraction, and satellite system applications due to its high accuracy and rapid speed. Pixel-level distribution statistics do not currently satisfy the requirements for high-resolution, large-scale remote sensing image processing. To address the above problem, in this paper, we propose a high-throughput hardware architecture for sea-land segmentation based on multi-dimensional parallel characteristics. The proposed architecture is well suited to wide remote sensing images. Efficient multi-dimensional block level statistics allow for relatively infrequent pixel-level memory access; a boundary block tracking process replaces the whole-image scanning process, markedly enhancing efficiency. The tracking efficiency is further improved by a convenient two-step scanning strategy that feeds back the path state in a timely manner for a large number of blocks in the same direction appearing in the algorithm. The proposed architecture was deployed on Xilinx Virtex k7-410t to find that its practical processing time for a [Formula: see text] remote sensing image is only about 0.4[Formula: see text]s. The peak performance is 1.625[Formula: see text]gbps, which is higher than other FPGA implementations of segmentation algorithms. The proposed structure is highly competitive in processing wide remote sensing images.

A Methodology to Manage System-level Uncertainty During Conceptual Design

2006 ◽  
Vol 128 (4) ◽  
pp. 959-968 ◽  
Author(s):  
Jay D. Martin ◽  
Timothy W. Simpson
Keyword(s):  
Decision Making ◽  
Conceptual Design ◽  
Kriging Model ◽  
Satellite System ◽  
System Level ◽  
Computationally Efficient ◽  
Design Decisions ◽  
Current Design ◽  
The Impact ◽  
Level Performance

Current design decisions must be made while considering uncertainty in both models of the design and inputs to the design. In most cases, high fidelity models are used with the assumption that the resulting model uncertainties are insignificant to the decision making process. This paper presents a methodology for managing uncertainty during system-level conceptual design of complex multidisciplinary systems. This methodology is based upon quantifying the information available in a set of observations of computationally expensive subsystem models with more computationally efficient kriging models. By using kriging models, the computational expense of a Monte Carlo simulation to assess the impact of the sources of uncertainty on system-level performance parameters becomes tractable. The use of a kriging model as an approximation to an original computer model introduces model uncertainty, which is included as part of the methodology. The methodology is demonstrated as a decision-making tool for the design of a satellite system.

Computational methodology to predict satellite system-level effects from impacts of untrackable space debris

2013 ◽  
Vol 88 ◽  
pp. 35-43 ◽  
Author(s):  
N. Welty ◽  
M. Rudolph ◽  
F. Schäfer ◽  
J. Apeldoorn ◽  
R. Janovsky
Keyword(s):  
Space Debris ◽  
Satellite System ◽  
System Level ◽  
Computational Methodology
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