A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems

This paper presents a modeling framework for schedulability analysis of distributed integrated modular avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL to analyze its schedulability by classical model checking (MC) and statistical model checking (SMC). The framework has been designed to enable three types of analysis: global SMC, global MC, and compositional MC. This allows an effective methodology including (1) quick schedulability falsification using global SMC analysis, (2) direct schedulability proofs using global MC analysis in simple cases, and (3) strict schedulability proofs using compositional MC analysis for larger state space. The framework is applied to the analysis of a concrete DIMA system.Comment: In Proceedings MARS/VPT 2018, arXiv:1803.0866

A Compositional Approach for Schedulability Analysis of Distributed Avionics Systems

This work presents a compositional approach for schedulability analysis of Distributed Integrated Modular Avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata in UPPAAL to verify its schedulability by model checking. However, direct model checking is infeasible due to the large state space. Therefore, we introduce the compositional analysis that checks each partition including its communication environment individually. Based on a notion of message interfaces, a number of message sender automata are built to model the environment for a partition. We define a timed selection simulation relation, which supports the construction of composite message interfaces. By using assume-guarantee reasoning, we ensure that each task meets the deadline and that communication constraints are also fulfilled globally. The approach is applied to the analysis of a concrete DIMA system.Comment: In Proceedings MeTRiD 2018, arXiv:1806.09330. arXiv admin note: text overlap with arXiv:1803.1105

Off-line Deduplication Method for Solid-State Disk Based on Hot and Cold Data

Solid-state disk (SSD) deduplication refers to the identification and deletion of duplicate data stored in an SSD. The reliability of SSDs is improved by deduplication. At present, the common data deduplication of SSDs is based on online data deduplication with Field Programmable Gate Array (FPGA) acceleration. The disadvantage is that FPGA, which has a complex structure. An off-line deduplication method for the SSD based on hot and cold data was proposed in this study to simplify the structure of an SSD deduplication, reduce the cost, and improve the efficiency of deduplication and access performance of SSDs. First, the wear-leveling algorithm was employed in the SSD to divide the data into cold and hot. Then, the corresponding fingerprint was generated for the cold data. Second, the fingerprint was compared, and the cold data with the same fingerprint were deleted. Finally, the cold and hot data were exchanged after deduplication. Results demonstrate that the duplicate recognition rate of the proposed method is 5% - 38%, which is close to that of the online deduplication method. In terms of access performance, the performance of SSDs using the proposed method is improved by 20% compared with that of traditional SSDs and is near the access performance of SSDs using online deduplication. This study provides certain reference for improving the reliability of existing SSDs

Real-time Accurate Runway Detection based on Airborne Multi-sensors Fusion

Existing methods of runway detection are more focused on image processing for remote sensing images based on computer vision techniques. However, these algorithms are too complicated and time-consuming to meet the demand for real-time airborne application. This paper proposes a novel runway detection method based on airborne multi-sensors data fusion which works in a coarse-to-fine hierarchical architecture. At the coarse layer, a vision projection model from world coordinate system to image coordinate system is built by fusing airborne navigation data and forward-looking sensing images, then a runway region of interest (ROI) is extracted from a whole image by the model. Furthermore, EDLines which is a real-time line segments detector is applied to extract straight line segments from ROI at the fine layer, and fragmented line segments generated by EDLines are linked into two long runway lines. Finally, some unique runway features (e.g. vanishing point and runway direction) are used to recognise airport runway. The proposed method is tested on an image dataset provided by a flight simulation system. The experimental results show that the method has advantages in terms of speed, recognition rate and false alarm rate

Recent Achievement in Gene Cloning and Functional Genomics in Soybean

Soybean is a model plant for photoperiodism as well as for symbiotic nitrogen fixation. However, a rather low efficiency in soybean transformation hampers functional analysis of genes isolated from soybean. In comparison, rapid development and progress in flowering time and photoperiodic response have been achieved in Arabidopsis and rice. As the soybean genomic information has been released since 2008, gene cloning and functional genomic studies have been revived as indicated by successfully characterizing genes involved in maturity and nematode resistance. Here, we review some major achievements in the cloning of some important genes and some specific features at genetic or genomic levels revealed by the analysis of functional genomics of soybean

Time Series Adaptive Online Prediction Method Combined with Modified LS-SVR and AGO

Fault or health condition prediction of the complex systems has attracted more attention in recent years. The complex systems often show complex dynamic behavior and uncertainty, which makes it difficult to establish a precise physical model. Therefore, the time series of complex system is used to implement prediction in practice. Aiming at time series online prediction, we propose a new method to improve the prediction accuracy in this paper, which is based on the grey system theory and incremental learning algorithm. In this method, the accumulated generating operation (AGO) with the raw time series is taken to improve the data quality and regularity firstly; then the prediction is conducted by a modified LS-SVR model, which simplifies the calculation process with incremental learning; finally, the inverse accumulated generating operation (IAGO) is performed to get the prediction results. The results of the prediction experiments indicate preliminarily that the proposed scheme is an effective prediction approach for its good prediction precision and less computing time. The method will be useful in actual application

Triassic sedimentation and postaccretionary crustal evolution along the Solonker suture zone in Inner Mongolia, China

Detrital zircon U-Pb dating of the Xingfuzhilu Formation in southern Inner Mongolia yields a maximum depositional age of around 220 Ma. The predominantly Permian and Triassic zircons are characterized by oscillatory zoning and euhedral shapes, with mostly positive zircon εHf(t) values (+2.0 to +16.4), indicating that they were derived from a proximal magmatic source. Early-Middle Paleozoic zircons have variable zircon εHf(t) values from −6.2 to +11.2 and are characterized by weak oscillatory zoning and subhedral-subrounded shapes, suggesting that the sources are a proximal magmatic arc, possibly mixed with components of the Ondor Sum magmatic arc and the magmatic arc at the northern margin of the North China Craton. The remnants of Precambrian blocks in the southeastern Central Asian Orogenic Belt (CAOB), and the North China Craton may also have been a minor source region for the Xingfuzhilu succession. These results, combined with regional data, indicate that a closing remnant ocean basin or narrow seaway possibly existed in the Middle Permian (Guadalupian) immediately prior to final collision of the CAOB and closure of the Paleo-Asian Ocean. Subsequent collision resulted in the crustal uplift and thickening along the Solonker suture zone, accompanied by possible slab break-off and lithospheric delamination during the Latest Permian to Middle Triassic. The resultant orogen in the Late Triassic underwent exhumation and denudation of rocks in response to the postorogenic collapse and regional extension. Vertical crustal growth in the Triassic is documented by detrital zircons from the Xingfuzhilu Formation and appears to have been widespread across entire eastern CAOB