139 research outputs found
Verifying collision avoidance behaviours for unmanned surface vehicles using probabilistic model checking
Collision avoidance is an essential safety requirement for unmanned surface vehicles (USVs). Normally, its practical verification is non-trivial, due to the stochastic behaviours of both the USVs and the intruders. This paper presents the probabilistic timed automata (PTAs) based formalism for three collision avoidance behaviours of USVs in uncertain dynamic environments, which are associated with the crossing situation in COLREGs. Steering right, acceleration, and deceleration are considered potential evasive manoeuvres. The state-of-the-art prism model checker is applied to analyse the underlying models. This work provides a framework and practical application of the probabilistic model checking for decision making in collision avoidance for USVs
Soft-Defined Heterogeneous Vehicular Network: Architecture and Challenges
Heterogeneous Vehicular NETworks (HetVNETs) can meet various
quality-of-service (QoS) requirements for intelligent transport system (ITS)
services by integrating different access networks coherently. However, the
current network architecture for HetVNET cannot efficiently deal with the
increasing demands of rapidly changing network landscape. Thanks to the
centralization and flexibility of the cloud radio access network (Cloud-RAN),
soft-defined networking (SDN) can conveniently be applied to support the
dynamic nature of future HetVNET functions and various applications while
reducing the operating costs. In this paper, we first propose the multi-layer
Cloud RAN architecture for implementing the new network, where the multi-domain
resources can be exploited as needed for vehicle users. Then, the high-level
design of soft-defined HetVNET is presented in detail. Finally, we briefly
discuss key challenges and solutions for this new network, corroborating its
feasibility in the emerging fifth-generation (5G) era
Bounded Relativization
Relativization is one of the most fundamental concepts in complexity theory, which explains the difficulty of resolving major open problems. In this paper, we propose a weaker notion of relativization called bounded relativization. For a complexity class ?, we say that a statement is ?-relativizing if the statement holds relative to every oracle ? ? ?. It is easy to see that every result that relativizes also ?-relativizes for every complexity class ?. On the other hand, we observe that many non-relativizing results, such as IP = PSPACE, are in fact PSPACE-relativizing.
First, we use the idea of bounded relativization to obtain new lower bound results, including the following nearly maximum circuit lower bound: for every constant ? > 0, BPE^{MCSP}/2^{?n} ? SIZE[2?/n].
We prove this by PSPACE-relativizing the recent pseudodeterministic pseudorandom generator by Lu, Oliveira, and Santhanam (STOC 2021).
Next, we study the limitations of PSPACE-relativizing proof techniques, and show that a seemingly minor improvement over the known results using PSPACE-relativizing techniques would imply a breakthrough separation NP ? L. For example:
- Impagliazzo and Wigderson (JCSS 2001) proved that if EXP ? BPP, then BPP admits infinitely-often subexponential-time heuristic derandomization. We show that their result is PSPACE-relativizing, and that improving it to worst-case derandomization using PSPACE-relativizing techniques implies NP ? L.
- Oliveira and Santhanam (STOC 2017) recently proved that every dense subset in P admits an infinitely-often subexponential-time pseudodeterministic construction, which we observe is PSPACE-relativizing. Improving this to almost-everywhere (pseudodeterministic) or (infinitely-often) deterministic constructions by PSPACE-relativizing techniques implies NP ? L.
- Santhanam (SICOMP 2009) proved that pr-MA does not have fixed polynomial-size circuits. This lower bound can be shown PSPACE-relativizing, and we show that improving it to an almost-everywhere lower bound using PSPACE-relativizing techniques implies NP ? L.
In fact, we show that if we can use PSPACE-relativizing techniques to obtain the above-mentioned improvements, then PSPACE ? EXPH. We obtain our barrier results by constructing suitable oracles computable in EXPH relative to which these improvements are impossible
CAT: Causal Audio Transformer for Audio Classification
The attention-based Transformers have been increasingly applied to audio
classification because of their global receptive field and ability to handle
long-term dependency. However, the existing frameworks which are mainly
extended from the Vision Transformers are not perfectly compatible with audio
signals. In this paper, we introduce a Causal Audio Transformer (CAT)
consisting of a Multi-Resolution Multi-Feature (MRMF) feature extraction with
an acoustic attention block for more optimized audio modeling. In addition, we
propose a causal module that alleviates over-fitting, helps with knowledge
transfer, and improves interpretability. CAT obtains higher or comparable
state-of-the-art classification performance on ESC50, AudioSet and UrbanSound8K
datasets, and can be easily generalized to other Transformer-based models.Comment: Accepted to ICASSP 202
Efficient path planning algorithms for Unmanned Surface Vehicle
The C-Enduro Unmanned Surface Vehicle (USV) is designed to operate at sea for extended periods of time (up to 3 months). To increase the endurance capability of the USV, an energy efficient path planning algorithm is developed. The proposed path planning algorithm integrates the Voronoi diagram, Visibility algorithm, Dijkstra search algorithm and takes also into account the sea current data. Ten USV simulated mission scenarios at different time of day and start/end points were analysed. The proposed approach shows that the amount of energy saved can be up to 21%. Moreover, the proposed algorithm can be used to calculate a collision free and energy efficient path to keep the USV safe and improve the USV capability. The safety distance between the USV and the coastline can also be configured by the user
Polynomial-Time Pseudodeterministic Construction of Primes
A randomized algorithm for a search problem is *pseudodeterministic* if it
produces a fixed canonical solution to the search problem with high
probability. In their seminal work on the topic, Gat and Goldwasser posed as
their main open problem whether prime numbers can be pseudodeterministically
constructed in polynomial time.
We provide a positive solution to this question in the infinitely-often
regime. In more detail, we give an *unconditional* polynomial-time randomized
algorithm such that, for infinitely many values of , outputs a
canonical -bit prime with high probability. More generally, we prove
that for every dense property of strings that can be decided in polynomial
time, there is an infinitely-often pseudodeterministic polynomial-time
construction of strings satisfying . This improves upon a
subexponential-time construction of Oliveira and Santhanam.
Our construction uses several new ideas, including a novel bootstrapping
technique for pseudodeterministic constructions, and a quantitative
optimization of the uniform hardness-randomness framework of Chen and Tell,
using a variant of the Shaltiel--Umans generator
An energy-efficient path planning algorithm for unmanned surface vehicles
The sea current state affects the energy consumption of Unmanned Surface Vehicles (USVs) significantly and the path planning approach plays an important role in determining how long the USV can travel. To improve the endurance of the USV, an energy efficient path planning approach for computing feasible paths for USVs that takes the energy consumption into account based on sea current data is proposed. The approach also ensures that the USV remains at a user-configurable safety distance away from all islands and coastlines. In the proposed approach, Voronoi diagram, Visibility graph, Dijkstra's search and energy consumption function are combined, which allows USVs to avoid obstacles while at the same time using minimum amount of energy. The Voronoi-Visibility (VV) energy-efficient path and the corresponding shortest path were simulated and compared for ten missions in Singapore Strait and five missions for islands off the coast of Croatia. Impact of parameters such as mission time, the USV speed and sea current state on the results were analysed. It is shown that the proposed VV algorithm improves the quality of the Voronoi energy efficient path while keeping the same level of computational efficiency as that of the Voronoi energy efficient path planning algorithm
High-throughput sequencing of methylated cytosine enriched by modification-dependent restriction endonuclease MspJI
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