Embedding sensors in urban buses is a promising strategy to deploy city-wide wireless sensor networks. By taking advantage of the mobility of buses, it is possible to achieve extended spatial coverage with fewer sensors as compared to a static setup. The trade-offs are that urban buses only cover part of the city, and that the frequency of the buses, and consequently of the data collection, is inhomogeneous

Abstract This paper proposes a novel three-dimensional guidance method based on clock synchronization algorithms, creatively solving the problems of randomized change, non-connection and even communication outage caused by packet loss and delay in the co-guidance of loitering munitions. The proposed method is characterized by fast convergence of the aspect angle rate in the longitudinal plane, and

High-order graph matching is a problem of establishing the correspondences between two sets of visual features subject to high-order matching constraints. This is an NP-hard combinatorial optimization problem and formulated as a maximization problem of matching score over all permutations of features. Artificial electric field algorithm (AEFA) (Yadav et al., 2019) is a proven optimization algorithm

In this paper a noise gradient strategy on the Adam optimizer is introduced, in order to reduce the training time of our enhanced Chauffeur hybrid deep model. This neural network was modified to take into account the time dependence of the input visual information from a time-distributed convolution, with the aim of increasing the autonomy of a self-driving vehicle. The effectiveness of the proposed

A graph G=(V,E) is δ-hyperbolic if for any four vertices u,v,w,x, the two larger of the three distance sums d(u,v)+d(w,x), d(u,w)+d(v,x), d(u,x)+d(v,w) differ by at most 2δ≥0. This paper describes the eccentricity terrain of a δ-hyperbolic graph. The eccentricity function eG(v)=max⁡{d(v,u):u∈V} partitions vertices of G into eccentricity layers Ck(G)={v∈V:eG(v)=rad(G)+k}, k∈N, where rad(G)=min⁡{eG(v):v∈V}

We provide a formal treatment of security of digital signatures against subversion attacks (SAs). Our model of subversion generalizes previous work in several directions, and is inspired by the proliferation of software attacks (e.g., malware and buffer overflow attacks), and by the recent revelations of Edward Snowden about intelligence agencies trying to surreptitiously sabotage cryptographic algorithms

Classification of biological neuron types and networks poses challenges to the full understanding of the brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal types and networks based on the communication metrics of neurons. This presents advantages against the existing approaches since the mutual information or the delay between

In this paper we study the adjacency spectrum of families of finite rooted trees with regular branching properties. In particular, we show that in the case of constant branching, the eigenvalues are realized as the roots of a family of generalized Fibonacci polynomials and produce a limiting distribution for the eigenvalues as the tree depth goes to infinity. We indicate how these results can be extended

A recent line of research has developed around logics of belief based on information confirmed by a reliable source. In this paper, we provide a finer analysis and extension of this framework, where the confirmation comes from multiple possibly conflicting sources and is of a probabilistic nature. We combine Belnap-Dunn logic and non-standard probabilities to account for potentially contradictory information

Recent results show that a constraint satisfaction problem (CSP) defined over rational numbers with their natural ordering has a solution if and only if it has a definable solution. The proof uses advanced results from topology and modern model theory. The aim of this paper is threefold. (1) We give a simple purely-logical proof of the claim and show that the advanced results from topology and model

We investigate how various forms of bisimulation can be characterised using the technology of logical relations. The approach taken is that each form of bisimulation corresponds to an algebraic structure derived from a transition system, and the general result is that a relation $R$ between two transition systems on state spaces $S$ and $T$ is a bisimulation if and only if the derived algebraic structures

We present and discuss natural deduction systems and associated modal lambda calculi for constructive variants of the necessity fragments of the modal logics K, T, K4, GL and S4. These systems are in the dual-context style: they feature two distinct zones of assumptions, one of which can be thought as modal, and the other as intuitionistic. We show that these calculi have their roots in patterns found

A system of polynomial ordinary differential equations (ODEs) is specified via a vector of multivariate polynomials, or vector field, $F$. A safety assertion $\psi\rightarrow[F]\phi$ means that the trajectory of the system will lie in a subset $\phi$ (the postcondition) of the state-space, whenever the initial state belongs to a subset $\psi$ (the precondition). We consider the case when $\phi$ and

In 2008, Ben-Amram, Jones and Kristiansen showed that for a simple programming language - representing non-deterministic imperative programs with bounded loops, and arithmetics limited to addition and multiplication - it is possible to decide precisely whether a program has certain growth-rate properties, in particular whether a computed value, or the program's running time, has a polynomial growth

We present a completely new approach to quantum circuit optimisation, based on the ZX-calculus. We first interpret quantum circuits as ZX-diagrams, which provide a flexible, lower-level language for describing quantum computations graphically. Then, using the rules of the ZX-calculus, we give a simplification strategy for ZX-diagrams based on the two graph transformations of local complementation and

We introduce a logical approach to formalizing statistical properties of machine learning. Specifically, we propose a formal model for statistical classification based on a Kripke model, and formalize various notions of classification performance, robustness, and fairness of classifiers by using epistemic logic. Then we show some relationships among properties of classifiers and those between classification

As the usage of theorem prover technology expands, so too does the reliance on correctness of the tools. Metamath Zero is a verification system that aims for simplicity of logic and implementation, without compromising on efficiency of verification. It is formally specified in its own language, and supports a number of translations to and from other proof languages. This paper describes the abstract

In this paper we put forward the viewpoint that the notion of stress testing financial institutions and engineered systems can also be made viable appropos the stress testing an individual's strength of conviction in a probability distribution. The difference is interpretation and perspective. To make our case we consider a game theoretic setup entailing two players, an adversarial C, and an amicable

Throughout the years, social norms have been promoted as an informal enforcement mechanism for achieving beneficial collective outcomes. Among the most used methods to foster interactions, framing the context of a situation or setting in-game rules have shown strong results as mediators on how an individual interacts with their peers. Nevertheless, we found that there is a lack of research regarding

We consider graphical games as introduced by Kearns et al. (2001). First we analyse the interaction of graphicality with a notion of strategic equivalence of games, providing a minimal complexity graphical description for games. Then we study the interplay between graphicality and the classical decomposition of games proposed by Candogan et al. (2011), characterizing the graphical properties of each

We introduce the notion of separable games, which refines and generalizes that of graphical games. We prove that there exists a minimal splitting with respect to which a game is separable. Moreover we prove that in every strategic equivalence class, there is a game separable with respect to the minimal splitting in the class. This game is also graphical with respect to the smallest graph in the class

An objective of network neutrality is that the design of regulations for the Internet will ensure that it remains a public, open platform where innovations can thrive. While there is broad agreement that preserving the content quality of service falls under the purview of net neutrality, the role of differential pricing, especially the practice of \emph {zero-rating} remains controversial. Even though

The combined cooling, heating and power (CCHP) system is a typical distributed, electricity-gas integrated energy scheme in a community. First, it generates electricity by use of gas, and then exploits the waste heat to supply community with heat and cooling. In this paper, we consider a smart city consisting of a number of communities (CCHPs) and an agent of power grid (APG), where CCHPs can sell

A cyber security problem in a networked system formulated as a resilient graph problem based on a game-theoretic approach is considered. The connectivity of the underlying graph of the network system is reduced by an attacker who removes some of the edges whereas the defender attempts to recover them. Both players are subject to energy constraints so that their actions are restricted and cannot be

We consider a scenario where the retailers can select different prices to the users in a smart grid. Each user's demand consists of an elastic component and an inelastic component. The retailer's objective is to maximize the revenue, minimize the operating cost, and maximize the user's welfare. The retailer wants to optimize a convex combination of the above objectives using a price signal. The discriminations

We study a vertical market with an upsteam supplier and multiple downstream retailers. Demand uncertainty falls to the supplier who acts first and sets a uniform wholesale price before the retailers observe the realized demand and engage in retail competition. Our focus is on the supplier's optimal pricing decision. We express the price elasticity of expected demand in terms of the mean residual demand

Econometric inference allows an analyst to back out the values of agents in a mechanism from the rules of the mechanism and bids of the agents. This paper gives an algorithm to solve the problem of inferring the values of agents in a dominant-strategy mechanism from the social choice function implemented by the mechanism and the per-unit prices paid by the agents (the agent bids are not observed).

We study the problem of computing data-driven personalized reserve prices in eager second price auctions without having any assumption on valuation distributions. Here, the input is a data-set that contains the submitted bids of $n$ buyers in a set of auctions and the problem is to return personalized reserve prices $\textbf r$ that maximize the revenue earned on these auctions by running eager second

Motivated by advances is nanoscale applications and simplistic robot agents, we look at problems based on using a global signal to move all agents when given a limited number of directional signals and immovable geometry. We study a model where unit square particles move within a 2D grid based on uniform external forces. Movement is based on a sequence of uniform commands which cause all particles

Quantum Computers (QCs), once they mature, will be able to solve some problems faster than Classic Computers. This phenomenon is called "quantum advantage" (or a stronger term "quantum supremacy"). Quantum advantage will help us to speed up computations in many areas, from artificial intelligence to medicine. However, QC power can also be leveraged to break modern cryptographic algorithms, which pervade

Modern adiabatic quantum computers (AQC) are already used to solve difficult combinatorial optimisation problems in various domains of science. Currently, only a few applications of AQC in computer vision have been demonstrated. We review AQC and derive a new algorithm for correspondence problems on point sets suitable for execution on AQC. Our algorithm has a subquadratic computational complexity

In this paper an efficient and reliable method for stochastic yield estimation is presented. Since one main challenge of uncertainty quantification is the computational feasibility, we propose a hybrid approach where most of the Monte Carlo sample points are evaluated with a surrogate model, and only a few sample points are reevaluated with the original high fidelity model. Gaussian Process Regression

In this paper, we propose an iterative splitting method to solve the partial differential equations in option pricing problems. We focus on the Heston stochastic volatility model and the derived two-dimensional partial differential equation (PDE). We take the European option as an example and conduct numerical experiments using different boundary conditions. The iterative splitting method transforms

Materials representation plays a key role in machine learning based prediction of materials properties and new materials discovery. Currently both graph and 3D voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of

This paper presents a new simulator for dynamic modelling of interactions between flooding and people in crowded areas. The simulator is developed in FLAMEGPU (a Flexible Large scale Agent-based Modelling Environment for the GPU), which allows to model multiple agent interactions while benefitting from the speed-up of GPUs. Flooding variables including terrain data are represented by a hydrodynamic

We show that there is a defining equation of degree at most $\mathsf{poly}(n)$ for the (Zariski closure of the) set of the non-rigid matrices: that is, we show that for every large enough field $\mathbb{F}$, there is a non-zero $n^2$-variate polynomial $P \in \mathbb{F}(x_{1, 1}, \ldots, x_{n, n})$ of degree at most $\mathsf{poly}(n)$ such that every matrix $M$ which can be written as a sum of a matrix

Despite the interest in the complexity class MA, the randomized analog of NP, there is just a couple of known natural (promise-)MA-complete problems, the first due to Bravyi and Terhal (SIAM Journal of Computing 2009) and the second due to Bravyi (Quantum Information and Computation 2015). Surprisingly, both problems are stated using terminology from quantum computation. This fact makes it hard for

In cellular automata with multiple speeds for each cell $i$ there is a positive integer $p_i$ such that this cell updates its state still periodically but only at times which are a multiple of $p_i$. Additionally there is a finite upper bound on all $p_i$. Manzoni and Umeo have described an algorithm for these (one-dimensional) cellular automata which solves the Firing Squad Synchronization Problem

We give new quantum algorithms for evaluating composed functions whose inputs may be shared between bottom-level gates. Let $f$ be a Boolean function and consider a function $F$ obtained by applying $f$ to conjunctions of possibly overlapping subsets of $n$ variables. If $f$ has quantum query complexity $Q(f)$, we give an algorithm for evaluating $F$ using $\tilde{O}(\sqrt{Q(f) \cdot n})$ quantum queries

In 2008, Ben-Amram, Jones and Kristiansen showed that for a simple programming language - representing non-deterministic imperative programs with bounded loops, and arithmetics limited to addition and multiplication - it is possible to decide precisely whether a program has certain growth-rate properties, in particular whether a computed value, or the program's running time, has a polynomial growth

Internet of Drones (IoD) is a new area which is based on incorporation of social networks into Internet of Things (IoT). In near future the social network of IoT devices is expected to be highly convoluted due to the exponential growth of heterogeneous smart devices. Searching the right objects and services in optimal time through best path will be a challenging task. Information searching techniques

Based on the dimension reduction of hyperspectral remote sensing image, a new neural network method is used to classify the hyperspectral remote sensing image of carbon dioxide in detail. Firstly, the Kernel Principal Component Analysis (KPCA) and Genetic Algorithms (GA) are used to reduce the dimension of hyperspectral remote sensing images; secondly, the traditional remote sensing image classification

With the rapid development of modern cities, relatively backward traffic management methods, inadequate road planning and construction, and the surge in car ownership, the problem of ”urban traffic congestion” has become a problem faced by modern urban management. Intelligent Transportation System (ITS) is gradually becoming the research direction for solving the problem of traffic congestion in various

Fault diagnosis has always been vital to providing a high level of dependability in systems. The comparison approach is one of the most prevalent diagnosis techniques that offers a simple and yet practical way to identify faulty nodes in a system. Even though several comparison-based diagnostic models have already been introduced, the majority of them only diagnose permanent faults in static networks

The behaviour analysis of the electric vehicle is helpful to grasp the running condition , improve the running efficiency and ensure the safe operation of the vehicle. With the development of Internet of things (IoT) technology, it has become a reality to monitor and analyze the car behaviour. By analyzing the functional requirements of the electric vehicle behaviour analysis management system, this

Aiming at the problem that the location of the secondary base station affects the interference between the primary and secondary systems directly and the reasonable allocation of channel resources, an Internet of Things (IoT) sensor network resource allocation scheme using an improved chaotic firefly algorithm is proposed. This solution builds a multi-objective optimization model based on interference

Abstract Hierarchical architecture of Wireless Network on Chips (WNoCs) composes of wired level and wireless level. In this architecture, subnetworks in wired level are connected by wireless. One of the main reliability challenges in the wired level of WNoC architecture is the crosstalk fault. Crosstalk fault occurs among the long and adjacent wires of wired level of WNoC due to tandem data traversal

Abstract Unstructured big data processing requires efficient computational styles to rapidly analyze continuously changing data. Incremental processing is a promising technique to update search results without re-computing the whole process. One of the most important mining algorithms is PageRank which necessitates incremental processing and iterative computations to keep the mining results up-to-date

Abstract Multidimensional numeric arrays are often serialized to binary formats for efficient storage and processing. These representations can be stored as binary objects in existing relational database management systems. To minimize data transfer overhead when arrays are large and only parts of arrays are accessed, it is favorable to split these arrays into separately stored chunks. We process queries

Abstract This paper investigates long-term visual object tracking which is a complex problem in computer vision community and big data analysis, due to the variation of the target and the surrounding environment. A novel tracking algorithm based on local correlation filtering and global keypoint matching is proposed to solve problems occurred during long-term tracking such as occlusion, target-losing

Abstract One of the biggest challenges in a Smart City is how to describe and dispose of the enormous and multiple sources of information, and how to share and merge it into a single infrastructure, in a timely and correct manner. A Smart City requires computational platforms, which allow the interconnection of multiple and embedded systems, such that the technology is integrated with people, and can

Compressive sensing (CS) has been widely used in wireless sensor networks (WSNs). In WSNs, the sensors are battery-powered and hence their communication and processing powers are limited. One of the dominant features of the CS is its complex recovery phase. Thus, great care should be taken into account when designing the CS recovery algorithm for WSNs. In this paper, we propose a distributed and cooperative

Local feature detection is a fundamental problem in computer vision. Recently, the research of local feature detection has been switched from handcrafted methods to learning based ones, especially deep learning based ones. A recent successful deep learning based feature detector is the covariant local feature detector that conducts keypoint detection by predicting the transformation of keypoints from

Time deposit has the characteristics of strong stability and low cost. It is a stable source of funds for banks. In this paper, S_Kohonen network is used to predict the success rate of fixed deposit in bank telephone marketing. Firstly, the output layer is added after the competition layer of unsupervised Kohonen network, which makes Kohonen network become S_Kohonen network with supervised learning

This paper discusses the application of nature-inspired swarm intelligence methods for optimal allocation and sizing of distributed generation (DG) in the radial distribution system (RDS). Introducing DG units in the RDS will enhance the technical and economic benefits, if they are optimally deployed. The objective functions considered are to improve the technical aspects and net economical saving

Nucleotide sequencing finds the exact order of nucleotides present in a DNA molecule. The correct DNA sequence is required to obtain the desired information about the complete genetic makeup of an organism. The DNA fragment assembly correctly combines the DNA information present in the form of fragments as a sequence. Reconstruction of the original DNA sequence from large fragments is a challenging

We investigate a distributed maximal independent set reconfiguration problem, in which there are two MIS for which every node is given its membership status, and the nodes need to communicate with their neighbors to find a reconfiguration schedule from the first MIS to the second. We forbid two neighbors to change their membership status at the same step. We provide efficient solutions when the intermediate

In this text, we prove the existence of an asymptotic growth rate of the number of dominating sets (and variants) on finite rectangular grids, when the dimensions of the grid grow to infinity. Moreover, we provide, for each of the variants, an algorithm which computes the growth rate. We also give bounds on these rates provided by a computer program.

We study the scheduling problem with calibrations and time slot costs. In this problem, the machine has to be calibrated to run a job and such a calibration only remains valid for a fixed time period of length T, after which it must be recalibrated in order to execute jobs. On the other hand, a certain cost will be incurred when the machine executes a job and such a cost is determined by the time slot

Let there be a set M of m parallel machines and a set J of n jobs, where each job j takes pi,j time units on machine Mi. In makespan minimization the goal is to schedule each job non-preemptively on a machine such that the length of the schedule, the makespan, is minimum. We investigate a generalization of makespan minimization on unrelated parallel machines (R||Cmax) where J is partitioned into b