Context/Resource-Aware Mission Planning Based on BNs and Concurrent MDPs for Autonomous UAVs

Rationale: It is very likely that we will miss Bing-Neel syndrome (BNS) when its initial sign is anemia. Patient concerns: A 59-year-old woman presented with episodic loss of consciousness, anemia, and extremity muscle strength scores (5-) and extremity tendon reflexes (++).Diagnoses: Magnetic Resonance Imaging (MRI) showed abnormal signal in the left hippocampus, left insula, and right occipital lobe. Quantitative serum immunoglobulins showed elevated immunoglobulinm (IgM) (60.6g/L). Bone marrow biopsy showed lymphoplasmacytic lymphoma (LPL) and tested positive for the MYD88 L265P mutation suggesting Waldenström macroglobulinemia (WM).Interventions: The patient underwent 3 plasma exchange treatments in the department of hematology followed by chemotherapy (cyclophosphamide for injection, bortezomib for injection).

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“…[ 30 ] MRI often shows edema at the lesion site, showing long T2 signal and fluid attenuated inversion recovery (FLAIR) high signal. [ 31 ]…”

Section: Discussionmentioning

confidence: 99%

Anemia ‐ an initial manifestation of Bing‐Neel syndrome: A case report

Yang

Chong

et al. 2022

Medicine

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“…We take as a case study a tracking mission where the aim is to detect and track a potential target (for more details see [30]). We define the mission planning using the concurrent BFMs (BFM navigation, BFM landing, BFM tracking).…”

Section: Example Of Mission Planning With Bfm Modelmentioning

confidence: 99%

“…We illustrate in this section the use of the pattern driven approach for two cases of study. For more details about these examples, please refer to [30,31].…”

Section: Bn Generation Examplesmentioning

confidence: 99%

Embedded Bayesian Network Contribution for a Safe Mission Planning of Autonomous Vehicles

Dezan

Zermani²,

Hireche

2020

Algorithms

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Bayesian Networks (BN) are probabilistic models that are commonly used for the diagnosis in numerous domains (medicine, finance, transport, robotics, …). In the case of autonomous vehicles, they can contribute to elaborate intelligent monitors that can take the environmental context into account. We show in this paper some main abilities of BN that can help in the elaboration of fault detection isolation and recovery (FDIR) modules. One of the main difficulty with the BN model is generally to elaborate these ones according to the case of study. Then, we propose some automatic generation techniques from failure mode and effects analysis (FMEA)-like tables using the pattern design approach. Once defined, these modules have to operate online for autonomous vehicles. In a second part, we propose a design methodology to embed the real-time and non-intrusive implementations of the BN modules using FPGA-SoC support. We show that the FPGA implementation can offer an interesting speed-up with very limited energy cost. Lastly, we show how these BN modules can be incorporated into the decision-making model for the mission planning of unmanned aerial vehicles (UAVs). We illustrate the integration by means of two models: the Decision Network model that is a straightforward extension of the BN model, and the BFM model that is an extension of the Markov Decision Process (MDP) decision-making model incorporating a BN. We illustrate the different proposals with realistic examples and show that the hybrid implementation on FPGA-SoC can offer some benefits.

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“…In real-life applications this assumption is not always true, besides in this work DPR was not fully implemented. In [9], authors have designed a system which can decide whether to reconfigure a system according to diagnostic indicators that include application QoS values. The decision method is based on Markov decision process and Bayesian networks, and consider available QoS criteria.…”

Section: State Of the Artmentioning

confidence: 99%