Consensus-based clustering and data aggregation in decentralized network of multi-agent systems.

Multi-agent systems are promising for applications in various fields. However, they require optimization algorithms that can handle large number of agents and heterogeneously connected networks in clustered environments. Planning algorithms performed in the decentralized communication model and clustered environment require precise knowledge about cluster information by compensating noise from other clusters. This article proposes a decentralized data aggregation algorithm using consensus method to perform COUNT and SUM aggregation in a clustered environment. The proposed algorithm introduces a trust value to perform accurate aggregation on cluster level. The correction parameter is used to adjust the accuracy of the solution and the computation time. The proposed algorithm is evaluated in simulations with large and sparse networks and small bandwidth. The results show that the proposed algorithm can achieve convergence on the aggregated data with reasonable accuracy and convergence time. In the future, the proposed tools will be useful for developing a robust decentralized task assignment algorithm in a heterogeneous multi-agent multi-task environment.

Ground Moving Target Tracking Filter Considering Terrain and Kinematics.

This paper addresses ground target tracking (GTT) for airborne radar. Digital terrain elevation data (DTED) are widely used for GTT as prior information under the premise that ground targets are constrained on terrain. Existing works fuse DTED to a tracking filter in a way that adopts only the assumption that the position of the target is constrained on the terrain. However, by kinematics, it is natural that the velocity of the moving ground target is constrained as well. Furthermore, DTED provides neither continuous nor accurate measurement of terrain elevation. To overcome such limitations, we propose a novel soft terrain constraint and a constraint-aided particle filter. To resolve the difficulties in applying the DTED to the GTT, first, we reconstruct the ground-truth terrain elevation using a Gaussian process and treat DTED as a noisy observation of it. Then, terrain constraint is formulated as joint soft constraints of position and velocity. Finally, we derive a Soft Terrain Constrained Particle Filter (STC-PF) that propagates particles while approximately satisfying the terrain constraint in the prediction step. In the numerical simulations, STC-PF outperforms the Smoothly Constrained Kalman Filter (SCKF) in terms of tracking performance because SCKF can only incorporate hard constraints.

Optimal Cooperative Guidance Laws for Two UAVs Under Sensor Information Deficiency Constraints.

This paper presents closed-form optimal cooperative guidance laws for two UAVs under information constraints that achieve the required relative approach angle. Two UAVs cooperate to optimize a common cost function under a coupled constraint on terminal velocity vectors and the information constraint which defines the sensor information availability. To handle the information constraint, a general two-player partially nested decentralized optimal control problem is considered in the continuous finite-horizon time domain. It is shown that under the state-separation principle the optimal solution of the decentralized control problem can be obtained by solving two centralized subproblems which cover the prediction problem for the information-deficient player and the prediction error minimization problem for the player with full information. Based on the solution of the decentralized optimal control problem, the explicit closed-form cooperative guidance laws that can be efficiently implemented on conventional guidance computers are derived. The performance of the proposed guidance laws is investigated on both centralized and decentralized cooperative scenarios with nonlinear engagement kinematics of networked two-UAV systems.

Deep Generative Models-Based Anomaly Detection for Spacecraft Control Systems.

A spacecraft attitude control system provides mechanical and electrical control to achieve the required functions under various mission scenarios. Although generally designed to be highly reliable, mission failure can occur if anomalies occur and the attitude control system fails to properly orient and stabilize the spacecraft. Because accessing spacecraft to directly repair such problems is usually infeasible, developing a continuous condition monitoring model is necessary to detect anomalies and respond accordingly. In this study, a method for detecting anomalies and characterizing failures for spacecraft attitude control systems is proposed. Herein, features are extracted from multidimensional time-series data of a simulation of the attitude control system. Then, the artificial neural network learning algorithms based on two types of generation models are applied. A Bayesian optimization algorithm with a Gaussian process is used to optimize the hyperparameters for the neural network to improve the performance. The performance is evaluated based on the reconstruction error through the algorithm using the newly generated data not used for learning as input data. Results show that the detection performance depends on the operating characteristics of each submode in the operation scenarios and type of generation model. The diagnostic results are monitored to detect anomalies in operation modes and scenarios.

Optimal Target Assignment with Seamless Handovers for Networked Radars.

This paper proposes a binary linear programming formulation for multiple target assignment of a radar network and demonstrates its applicability to obtain optimal solutions using an off-the-shelf mixed-integer linear programming solver. The goal of radar resource scheduling in this paper is to assign the maximum number of targets by handing over targets between networked radar systems to overcome physical limitations such as the detection range and simultaneous tracking capability of each radar. To achieve this, time windows are generated considering the relation between each radar and target considering incoming target information. Numerical experiments using a local-scale simulation were performed to verify the functionality of the formulation and a sensitivity analysis was conducted to identify the trend of the results with respect to several parameters. Additional experiments performed for a large-scale (battlefield) scenario confirmed that the proposed formulation is valid and applicable for hundreds of targets and corresponding radar network systems composed of five distributed radars. The performance of the scheduling solutions using the proposed formulation was better than that of the general greedy algorithm as a heuristic approach in terms of objective value as well as the number of handovers.

Three-Dimensional Laparoscopic Anatomical Segment 8 Liver Resection with Glissonian Approach.

BACKGROUND: Anatomical liver resection has been reported to have oncologic benefit over nonanatomical resection in surgery for hepatocellular carcinoma (HCC). Basic concept of anatomical resection is preventing tumor spread through the portal or venous flow. Few cases have been reported for laparoscopic anatomical segment 8 resection because of its technical difficulties. This video shows operative techniques for laparoscopic anatomical resection of segment 8, exposing middle and right hepatic vein and inferior vena cava using three-dimensional video. METHODS: A 61-year-old male was diagnosed to be a hepatitis B virus carrier 6 years ago. A 6.6-cm-sized HCC lesion was detected at segment 8 by computed tomography scan. We have used a high-definition, three-dimensional laparoscope with a deflectable tip (Olympus Medical Systems Corp., Japan), a trocar inserted in the right seventh intercostal space to obtain the optimal field of view on the superior-posterior portion of the liver. Using the Glissonian pedicle approach, we isolated and clamped the branch to the segment 8 to confirm the anatomical border of the segment 8. Segmentectomy was completed exposing the middle and right hepatic vein and inferior vena cava. RESULTS: Operation took 420 min. Estimated blood loss was 600 mL, and no red blood cell was transfused. Final pathology was an HCC with 0.3-cm safety margin. The patient discharged on the sixth day after operation with normal liver function test results. There was no operation-related complication from the operation day to the first outpatient visit day. CONCLUSIONS: Laparoscopic anatomical resection of segment 8 is feasible.

Polyarteritis nodosa presented as a dilatation of the intrahepatic bile duct.

Polyarteritis nodosa (PAN) is a systemic necrotizing vasculitis of small- and medium-sized arteries in multiorgan systems. PAN may affect the gastrointestinal tract in 14%-65% of patients, but rarely involves the biliary tract and liver. We describe a patient without underlying disease who was diagnosed with PAN during resection of the gallbladder and liver.

Bowel infarction due to intestinal mucormycosis in an immunocompetent patient.

Mucormycosis is a fatal opportunistic fungal infection that typically occurs in immunocompromised patients. The classical manifestation of mucormycosis is a rhinocerebral infection, and although primary gastrointestinal infection is uncommon, it has an extremely high mortality rate in immunocompromised patients. Furthermore, cases of gastrointestinal mucormycosis in an immunocompetent host are rarely reported. Here, we describe our experience of a male patient, with no underlying disease, who succumbed to a bowel infarction caused by intestinal mucormycosis during mechanical ventilatory care for severe pneumonia and septic shock.