DS-K3DOM: 3-D Dynamic Occupancy Mapping with Kernel Inference and Dempster-Shafer Evidential Theory

Occupancy mapping has been widely utilized to represent the surroundings for autonomous robots to perform tasks such as navigation and manipulation. While occupancy mapping in 2-D environments has been well-studied, there have been few approaches suitable for 3-D dynamic occupancy mapping which is essential for aerial robots. This paper presents a novel 3-D dynamic occupancy mapping algorithm called DSK3DOM. We first establish a Bayesian method to sequentially update occupancy maps for a stream of measurements based on the random finite set theory. Then, we approximate it with particles in the Dempster-Shafer domain to enable real time computation. Moreover, the algorithm applies kernel based inference with Dirichlet basic belief assignment to enable dense mapping from sparse measurements. The efficacy of the proposed algorithm is demonstrated through simulations and real experiments.Comment: 7 pages, 2 figures, submitted to ICRA 202

VCGIDB: A database and web resource for the genomic islands from Vibrio cholerae

Vibrio cholerae is the causative agent of cholera, which is a severe, life-threatening diarrheal disease. The current seventh pandemic has not been eradicated and the outbreak is still ongoing around the world. The evolution of the pandemic-causing strain has been greatly influenced by lateral gene transfer, and the mechanisms of acquisition of pathogenicity in V. cholerae are mainly involved with genomic islands (GIs). Thus, detecting GIs and their comprehensive information is necessary to understand the continuing resurgence and newly emerging pathogenic V. cholerae strains. In this study, 798 V. cholerae strains were tested using the GI-Scanner algorithm, which was developed to detect candidate GIs and identify them in a comparative genomics approach. The algorithm predicted 435 highly possible genomic islands, and we built a database, called Vibrio cholerae Genomic Island Database (VCGIDB). This database shows advanced results that were acquired from a large genome set using phylogeny-based predictions. Moreover, VCGIDB is a highly expendable database that does not require intensive computation, which enables us to update it with a greater number of genomes using a novel genomic island prediction method. The VCGIDB website allows the user to browse the data and presents the results in a visual manner.

A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking

This paper investigates non-myopic path planning of mobile sensors for multi-target tracking. Such problem has posed a high computational complexity issue and/or the necessity of high-level decision making. Existing works tackle these issues by heuristically assigning targets to each sensing agent and solving the split problem for each agent. However, such heuristic methods reduce the target estimation performance in the absence of considering the changes of target state estimation along time. In this work, we detour the task-assignment problem by reformulating the general non-myopic planning problem to a distributed optimization problem with respect to targets. By combining alternating direction method of multipliers (ADMM) and local trajectory optimization method, we solve the problem and induce consensus (i.e., high-level decisions) automatically among the targets. In addition, we propose a modified receding-horizon control (RHC) scheme and edge-cutting method for efficient real-time operation. The proposed algorithm is validated through simulations in various scenarios.Comment: Copyright 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

A study on the differences in the perceived importance of jet fighter performance improvement factors

The rapid advancement in software-based technology has significantly shortened product life cycles, leading to the proliferation of new products. However, the high initial investment makes it practically impossible for armed forces to rapidly replace existing weapons systems with new ones due to technological obsolescence. A more realistic alternative is to focus on performance improvements (or weapon upgrades) in existing systems. The challenge lies in making the right upgrades with the right technology at the right cost and time given the limited defense budget. Unfortunately, weapons upgrade decisions have mostly been based on costs and politically considered budget allocations to different branches of the armed forces rather than by considering a comprehensive range of decision factors. In light of the escalating national security threats, it is necessary to maximize the cost-effectiveness of weapons upgrade projects and effectively address rising national security challenges. The objective of this study is to develop a performance improvement Decision Index that quantifies the opinions of field-operating experts. Field experts are believed to possess the necessary expertise to select the appropriate fighter types, technologies, and upgrade timings, making it beneficial to factor in their opinions to determine what, how, and when to upgrade. Specifically, this study aims to establish weighted values for major decision factors regarding fighter performance improvement programs in the Republic of Korea Air Force. To achieve this, we collected survey data from 134 active-duty pilots and maintenance, operations, and repair (MRO) personnel from major fighter wings of the Republic of Korea Air Force and analyzed the data using the Fuzzy-AHP (Analytical Hierarchy Process). The analysis results indicate that the highest weighted value is given to the “relative (fighter) performance”against hostile nations, followed by “operating rate,” “durability,” “performance improvement cycle,” and “budget.” Furthermore, this study identified perceptual differences among field experts—particularly between pilots and MRO personnel—regarding the importance of relative performance, budget, performance improvement intervals, and operating rates of different fighter types. The proposed performance improvement index aims to provide a quantitative tool that incorporates field experts’ opinions into the decision-making process to upgrade weapons, facilitating balanced decisions and departing from a policymaker-centered approach. This balanced approach to weapons upgrade decisions will contribute to maximizing cost-effectiveness and, eventually, enhancing combat readiness

Axion Haloscope Using an 18 T High Temperature Superconducting Magnet

We report details on the axion dark matter search experiment that uses the innovative technologies of a High-Temperature Superconducting (HTS) magnet and a Josephson Parametric Converter (JPC). An 18 T HTS solenoid magnet is developed for this experiment. The JPC is used as the first stage amplifier to achieve a near quantum-limited low-noise condition. The first dark matter axion search was performed with the 18 T axion haloscope. The scan frequency range is from 4.7789 GHz to 4.8094 GHz (30.5 MHz range). No significant signal consistent with Galactic dark matter axion is observed. Our results set the best limit of the axion-photon-photon coupling ($g_{a\gamma\gamma}$) in the axion mass range of 19.764 to 19.890 $\mu$eV. Using the Bayesian method, the upper bounds of $g_{a\gamma\gamma}$ are set at 0.98$\times|g_{a\gamma\gamma}^{\text{KSVZ}}|$ (1.11$\times|g_{a\gamma\gamma}^{\text{KSVZ}}|$) in the mass ranges of 19.764 to 19.771 $\mu$eV (19.863 to 19.890 $\mu$eV), and at 1.76 $\times|g_{a\gamma\gamma}^{\text{KSVZ}}|$ in the mass ranges of 19.772 to 19.863 $\mu$eV with 90\% confidence level, respectively. We report design, construction, operation, and data analysis of the 18 T axion haloscope experiment.Comment: PRD published versio