Patching Neural Barrier Functions Using Hamilton-Jacobi Reachability

Learning-based control algorithms have led to major advances in robotics at the cost of decreased safety guarantees. Recently, neural networks have also been used to characterize safety through the use of barrier functions for complex nonlinear systems. Learned barrier functions approximately encode and enforce a desired safety constraint through a value function, but do not provide any formal guarantees. In this paper, we propose a local dynamic programming (DP) based approach to "patch" an almost-safe learned barrier at potentially unsafe points in the state space. This algorithm, HJ-Patch, obtains a novel barrier that provides formal safety guarantees, yet retains the global structure of the learned barrier. Our local DP based reachability algorithm, HJ-Patch, updates the barrier function "minimally" at points that both (a) neighbor the barrier safety boundary and (b) do not satisfy the safety condition. We view this as a key step to bridging the gap between learning-based barrier functions and Hamilton-Jacobi reachability analysis, providing a framework for further integration of these approaches. We demonstrate that for well-trained barriers we reduce the computational load by 2 orders of magnitude with respect to standard DP-based reachability, and demonstrate scalability to a 6-dimensional system, which is at the limit of standard DP-based reachability.Comment: 8 pages, submitted to IEEE Conference on Decision and Control (CDC), 202

Learning Safety Certificates for Neural Controllers

Learning-based methods are promising for tackling the inherent nonlinearity and model uncertainty in path-tracking control problems, but the lack of safety guarantee of neural controllers restricts their practical use in self-driving vehicles. We propose methods for training and certifying barrier functions that are themselves represented as neural networks, for ensuring safety properties of learning-based neural controllers in self-driving with realistic nonlinear dynamics. We describe how to identify safe and unsafe regions of the state space and minimize the violation of the barrier conditions to train neural barrier functions. We then show how to leverage the recent advances in robustness analysis of neural networks to bound the Lie derivatives of the barrier functions and certify the barrier conditions. Although understanding the vehicle dynamics is important for designing the training and certification procedures, the proposed algorithms are sampling-based and do not assume access to analytic forms of the dynamics. Thus the methods are generally applicable to nonlinear vehicle dynamics with model uncertainty and partial observability. We demonstrate the effectiveness of the methods for quantitatively certifying safety of neural controllers in different simulation environments ranging from simple kinematic models to the TORCS high-fidelity vehicle dynamics modeling environment as a blackbox simulator

Особенности аудита прогнозной информации

The aim of the article is to outline the special features of audit of forward-looking information. Nowadays audit of forward-looking financial information is considered of the modern trends in accounting and business audit. The author shows special methods and procedures of accounting forward-looking information.В данной статье освящаются особенности аудита прогнозной информации. На сегодняшний день аудиторская проверка прогнозной финансовой информации является одним из ведущих трендов бухучета и бизнес-аудита. рассматриваются действующие стандарты КСО и их реализация в условиях мировой экономики и российских реалий. В статье показаны специальные методы и процедуры учета прогнозной информации

Особенности аудита прогнозной информации

The aim of the article is to outline the special features of audit of forward-looking information. Nowadays audit of forward-looking financial information is considered of the modern trends in accounting and business audit. The author shows special methods and procedures of accounting forward-looking information.В данной статье освящаются особенности аудита прогнозной информации. На сегодняшний день аудиторская проверка прогнозной финансовой информации является одним из ведущих трендов бухучета и бизнес-аудита. рассматриваются действующие стандарты КСО и их реализация в условиях мировой экономики и российских реалий. В статье показаны специальные методы и процедуры учета прогнозной информации

Distribution and Variation of Mining-Induced Stress in the Reverse Fault-Affected Coal Body

This study aimed to explore the stress distribution and variation of reverse fault-affected mined coal body. A mechanical analysis model of the coal body in the reverse fault area was first established, then the coal body stress characterization equation was derived, and the stress distribution pattern on the coal body was calculated. Subsequently, applying the Mohr–Coulomb strength criterion revealed the following relationship: the closer is the distance to the reverse fault, the worse is the stability of the coal body, and that the coal body strength influences the stress concentration of the coal body in front of the working face. Moreover, simulation with FLAC3D was carried out to verify the coal body stress calculated by the mechanical model as well as the fluctuation of the coal body stress concentration. It could be concluded that while mining the hanging wall of the reverse fault, the stress concentration of mined coal body decreases with the increase of reverse fault dip angle, but increases with the increase of reverse fault throw; the stress concentration magnitude generated during footwall mining is lesser than that during hanging-wall mining. In other words, the magnitude of coal body stress concentration can be affected by the hanging wall and footwall mining, as well as parameters of the reverse fault. Finally, intrinsically safe GZY25 borehole stress sensors were used to monitor the coal body stresses in the reverse fault area under the influence of mining in Xinchun Coal Mine and ZuoQiuka Coal Mine. It was found that the coal body stress concentration in front of the working face either increased gradually or increased first before decreasing. It can be concluded that with the decrease of the distance between the working face and reverse fault, the vertical stress of the coal body increases, and the vertical stress of the coal body begins to increase obviously at a certain position. At this point, the vertical stress of the coal body can be generalized to 1.02–1.39 times of the initial vertical stress. Furthermore, the stress concentration coefficient of coal body is related to the distance from the reverse fault, and two changes occur: ① if the coal-bearing capacity does not exceed its strength, the coal stress in front of the working face increases gradually, and the stress concentration factor increases gradually; ② the stress concentration coefficient of mining coal body increases first, such that when the coal body bearing capacity exceeds its strength, the coal body fails and loses all its effective bearing capacity, followed by the decrease in coal body stress concentration coefficient

New Antifungal Metabolites from the Mariana Trench Sediment-Associated Actinomycete Streptomyces sp. SY1965

New streptothiazolidine A (1), streptodiketopiperazines A (2) and B (3), and (S)-1-(3-ethylphenyl)-1,2-ethanediol (4), together with eight known compounds (5–12), were isolated from the Mariana Trench sediment-associated actinomycete Streptomyces sp. SY1965. The racemic mixtures of (±)-streptodiketopiperazine (2 and 3) and (±)-1-(3-ethylphenyl)-1,2-ethanediol (4 and 5) were separated on a chiral high-performance liquid chromatography (HPLC) column. Structures of the new compounds were elucidated by their high-resolution electrospray ionization mass spectroscopy (HRESIMS) data and extensive nuclear magnetic resonance (NMR) spectroscopic analyses. Streptothiazolidine A is a novel salicylamide analogue with a unique thiazolidine-contained side chain and its absolute configuration was established by a combination of nuclear Overhauser effect spectroscopy (NOESY) experiment, electronic circular dichroism (ECD) and 13C NMR calculations. New streptothiazolidine A (1) and streptodiketopiperazines A (2) and B (3) showed antifungal activity against Candida albicans with MIC values of 47, 42, and 42 g/mL, respectively

Performance Analysis of Multi-Tote Storage and Retrieval Autonomous Mobile Robot Systems

Multi-tote storage and retrieval (MTSR) autonomous mobile robots (AMRs) can carry multiple product totes, store and retrieve them from different shelf-rack tiers, and transport the retrieved totes to a workstation where the products are picked to fulfill customer orders. In each robot trip, totes retrieved in the previous trip must be stored. This leads to a mixed storage and retrieval route. We analyze this mixed storage and retrieval route problem and derive the optimal travel route, denoted by the optimal hybrid route (OHR), by selecting the first storage location from a given set of open locations and alternating between retrieval and storage jobs. Moreover, we propose an effective heuristic routing policy, the Intelligent Search (IS) pick sequence policy, based on a local shortest path. Numerical results show that the IS policy leads to shorter travel times than the well-known S-shape policy, while the gap with the OHR policy in practical scenarios is small. Based on the IS policy, we model the stochastic behavior of the system, using a semi-open queuing network (SOQN). This model is able to accurately estimate order throughput times and system throughput capacity as a function of the number of robots in the system. We find that, compared with a single-tote storage and retrieval AMR system, the throughput capacity of the five-tote storage and retrieval MR system increases by nearly 50% with the same number of robots. The model can also be used to optimize the number of workstations and assigning robots to workstations. We also investigate the effect of potential robot blocking in the storage aisles on IS policy

Performance Analysis of Multi-Tote Storage and Retrieval Autonomous Mobile Robot Systems

Multi -tote storage and retrieval (MTSR) autonomous mobile robots can carry multiple product totes, store and retrieve them from different shelf rack tiers, and transport them to a workstation where the products are picked to fulfill customer orders. In each robot trip, totes retrieved during the previous trip must be stored. This leads to a mixed storage and retrieval route. We analyze this mixed storage and retrieval route problem and derive the optimal travel route for a multiblock warehouse by a layered graph algorithm, based on storage first -retrieval second and mixed storage and retrieval policies. We also propose an effective heuristic routing policy, the closest retrieval (CR) sequence policy, based on a local shortest path. Numerical results show that the CR policy leads to shorter travel times than the well-known S -shape policy, whereas the gap with the optimal mixed storage and retrieval policy in practical scenarios is small. Based on the CR policy, we model the stochastic behavior of the system using a semiopen queuing network (SOQN). This model can accurately estimate average tote throughput time and system throughput capacity as a function of the number of robots in the system. We use the SOQN and corresponding closed queuing network models to optimize the total annual cost as a function of the warehouse shape, the number of robots, and tote buffer positions on the robots for a given average tote throughput time and throughput capacity. Compared with robots that retrieve a single tote per trip, an MTSR system with at least five buffer positions can achieve lower operational costs while meeting given average tote throughput time and tote throughput capacity constraints

A novel tensor-information bottleneck method for multi-input single-output applications

Ensuring timeliness and mobility for multimedia computing is a crucial task for wireless communication. Previous algorithms that utilize information channels, such as the information bottleneck method, have shown great performance and efficiency, which guarantees timeliness. However, such methods suit only in handling single variable tasks such as image processing, but are in-applicable to multivariable applications such as video processing. To address this critical shortcoming, we propose a novel tensor information channel which extends the current single-input single-output matrix information channel to a more practical multi-input single-output tensor information channel. In comparison with the classic information channel, our tensor information channel not only performs better in experiments, but also allows for a wider range of practical applications. We further build an innovative tensor-information bottleneck method upon the state-of-the-art information bottleneck method. Experiments on video shot boundary detection are conducted using benchmark data sets to demonstrate the effectiveness of our proposed approach compared with state-of-the-art methods. In specific, our approach yields a 6.2% increase compared with the information channel-based method, and when compared to other state-of-the-art methods, we achieve 0.1%-17.7% performance gains under different experimental configurations

Dual-Salts Electrolyte with Fluoroethylene Carbonate Additive for High-Voltage Li-Metal Batteries

The combination of Li-metal anode and high-voltage cathode is regarded as a solution for the next-generation high-energy-density secondary batteries. However, a traditional electrolyte is either incompatible with the Li-metal anode or vulnerable to high voltage. This work reports a 1 M dual-salts Localized-High-Concentration-Electrolyte with Fluoroethylene carbonate (FEC) additive. It enables stable cycling of Li||LiNi0.8Co0.1Mn0.1O2 (NMC811) battery, which shows 81.5% capacity retention after 300 cycles with a charge/discharge current density of 1 C and a voltage range of 2.7–4.4 V. Scanning electron microscopy (SEM) images show that this electrolyte not only largely reduced Li dendrites and ‘dead’ Li on anode surface but also well protected the microstructure of NMC811 cathode. Possible components of both solid-electrolyte interlayer (SEI) and cathode-electrolyte interlayer (CEI) were characterized by energy-dispersive X-ray spectroscopy (EDX). The result illustrates that FEC protected Li salts from decomposition on the anode side and suppressed the decomposition of solvents on the cathode side.</p