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  • A delay-aware coverage metric for bus-based sensor networks
    Comput. Commun. (IF 2.766) Pub Date : 2020-03-31
    Pedro Cruz; Rodrigo S. Couto; Luís Henrique M.K. Costa; Anne Fladenmuller; Marcelo Dias de Amorim

    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

  • Distributed multi-munition cooperative guidance based on clock synchronization for switching and noisy networks
    J. Supercomput. (IF 2.157) Pub Date : 2020-03-31
    Sheng Yi, Xiaoyu She, Dong Guo, Tong Zhao, Chengwei Yang, Jie Li

    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

  • Discrete artificial electric field algorithm for high-order graph matching
    Appl. Soft Comput. (IF 4.873) Pub Date : 2020-03-31
    Anita; Anupam Yadav

    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

  • Noise gradient strategy for an enhanced hybrid convolutional-recurrent deep network to control a self-driving vehicle
    Appl. Soft Comput. (IF 4.873) Pub Date : 2020-03-30
    Dante Mújica-Vargas; Antonio Luna-Álvarez; José de Jesús Rubio; Blanca Carvajal-Gámez

    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

  • Eccentricity terrain of δ-hyperbolic graphs
    J. Comput. Syst. Sci. (IF 1.129) Pub Date : 2020-03-30
    Feodor F. Dragan; Heather M. Guarnera

    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}

  • Subversion-Resilient Signatures: Definitions, Constructions and Applications
    Theor. Comput. Sci. (IF 0.718) Pub Date : 2020-03-31
    Giuseppe Ateniese; Bernardo Magri; Daniele Venturi

    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

  • Objective Multi-variable Classification and Inference of Biological Neuronal Networks
    arXiv.cs.OH Pub Date : 2020-03-28
    Michael Taynnan Barros; Harun Siljak; Peter Mullen; Constantinos Papadias; Jari Hyttinen; Nicola Marchetti

    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

  • On the Spectrum of Finite, Rooted Homogeneous Trees
    arXiv.cs.OH Pub Date : 2019-03-17
    Daryl R. DeFord; Daniel N. Rockmore

    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

  • How to reason with inconsistent probabilistic information?
    arXiv.cs.LO Pub Date : 2020-03-28
    Marta Bílková; Sabine Frittella; Ondrej Majer; Sajad Nazari

    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

  • On amenability of constraint satisfaction problems
    arXiv.cs.LO Pub Date : 2020-03-29
    Michał R. Przybyłek

    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

  • Bisimulation as a Logical Relation
    arXiv.cs.LO Pub Date : 2020-03-30
    Claudio Hermida; Uday Reddy; Edmund Robinson; Alessio Santamaria

    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

  • Dual-Context Calculi for Modal Logic
    arXiv.cs.LO Pub Date : 2016-02-15
    G. A. Kavvos

    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

  • Complete algorithms for algebraic strongest postconditions and weakest preconditions in polynomial ODEs
    arXiv.cs.LO Pub Date : 2017-08-17
    Michele Boreale

    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

  • Tight Polynomial Worst-Case Bounds for Loop Programs
    arXiv.cs.LO Pub Date : 2019-06-24
    Amir M. Ben-Amram; Geoff Hamilton

    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

  • Graph-theoretic Simplification of Quantum Circuits with the ZX-calculus
    arXiv.cs.LO Pub Date : 2019-02-08
    Ross Duncan; Aleks Kissinger; Simon Perdrix; John van de Wetering

    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

  • Towards Logical Specification of Statistical Machine Learning
    arXiv.cs.LO Pub Date : 2019-07-24
    Yusuke Kawamoto

    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

  • Metamath Zero: The Cartesian Theorem Prover
    arXiv.cs.LO Pub Date : 2019-10-22
    Mario Carneiro

    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

  • Adversarial Stress Testing of Lifetime Distributions
    arXiv.cs.GT Pub Date : 2020-03-27
    Nozer Singpurwalla

    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

  • The Influence of Reward on the Social Valence of Interactions
    arXiv.cs.GT Pub Date : 2020-03-27
    Tomás Alves; Samuel Gomes; João Dias; Carlos Martinho

    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

  • Graphical Games and Decomposition
    arXiv.cs.GT Pub Date : 2020-03-29
    Laura Arditti; Giacomo Como; Fabio Fagnani

    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

  • Separable games
    arXiv.cs.GT Pub Date : 2020-03-29
    Laura Arditti; Giacomo Como; Fabio Fagnani

    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

  • Zero-Rating and Net Neutrality: Who Wins, Who Loses?
    arXiv.cs.GT Pub Date : 2020-02-13
    Niloofar Bayat; Richard Ma; Vishal Misra; Dan Rubenstein

    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

  • Combined Cooling, Heating, and Power System in Blockchain-Enabled Energy Management
    arXiv.cs.GT Pub Date : 2020-03-20
    Jianxiong Guo; Xingjian Ding; Weili Wu

    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

  • Dynamic Resilient Network Games with Applications to Multi-Agent Consensus
    arXiv.cs.GT Pub Date : 2020-03-30
    Yurid Nugraha; Ahmet Cetinkaya; TOmohisa Hayakawa; Hideaki Ishii; Quanyan Zhu

    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

  • Discriminatory Price Mechanism for Smart Grid
    arXiv.cs.GT Pub Date : 2020-03-30
    Diptangshu Sen; Kushaagra Goyal; Arnob Ghosh; Varun Ramamohan

    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

  • Monopoly Pricing in a Vertical Market with Demand Uncertainty
    arXiv.cs.GT Pub Date : 2017-09-27
    Stefanos Leonardos; Costis Melolidakis; Constandina Koki

    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

  • Inference from Auction Prices
    arXiv.cs.GT Pub Date : 2019-02-19
    Jason Hartline; Aleck Johnsen; Denis Nekipelov; Zihe Wang

    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).

  • Data-Driven Optimization of Personalized Reserve Prices
    arXiv.cs.GT Pub Date : 2019-05-04
    Mahsa Derakhshan; Negin Golrezaei; Renato Paes Leme

    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

  • Hardness of Reconfiguring Robot Swarms with Uniform External Control in Limited Directions
    arXiv.cs.ET Pub Date : 2020-03-29
    David Caballero; Angel A. Cantu; Timothy Gomez; Austin Luchsinger; Robert Schweller; Tim Wylie

    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 Advantage and Y2K Bug: Comparison
    arXiv.cs.ET Pub Date : 2019-07-24
    Lei Zhang; Andriy Miranskyy; Walid Rjaibi

    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

  • A Quantum Computational Approach to Correspondence Problems on Point Sets
    arXiv.cs.ET Pub Date : 2019-12-13
    Vladislav Golyanik; Christian Theobalt

    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

  • A Blackbox Yield Estimation Workflow with Gaussian Process Regression for Industrial Problems
    arXiv.cs.CE Pub Date : 2020-03-30
    Mona Fuhrländer; Sebastian Schöps

    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

  • An iterative splitting method for pricing European options under the Heston model
    arXiv.cs.CE Pub Date : 2020-03-29
    Hongshan Li; Zhongyi Huang

    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

  • Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks
    arXiv.cs.CE Pub Date : 2020-03-17
    Yong Zhao; Kunpeng Yuan; Yinqiao Liu; Steph-Yves Loius; Ming Hu; Jianjun Hu

    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

  • Agent-based simulator of dynamic flood-people interactions
    arXiv.cs.CE Pub Date : 2019-08-08
    Mohammad Shirvani; Georges Kesserwani; Paul Richmond

    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

  • A Polynomial Degree Bound on Defining Equations of Non-rigid Matrices and Small Linear Circuits
    arXiv.cs.CC Pub Date : 2020-03-29
    Mrinal Kumar; Ben Lee Volk

    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

  • A combinatorial MA-complete problem
    arXiv.cs.CC Pub Date : 2020-03-29
    Dorit Aharonov; Alex B. Grilo

    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

  • A faster algorithm for the FSSP in one-dimensional CA with multiple speeds
    arXiv.cs.CC Pub Date : 2020-03-30
    Thomas WorschKarlsruhe Institute of Technology

    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

  • Quantum algorithms and approximating polynomials for composed functions with shared inputs
    arXiv.cs.CC Pub Date : 2018-09-06
    Mark Bun; Robin Kothari; Justin Thaler

    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

  • Tight Polynomial Worst-Case Bounds for Loop Programs
    arXiv.cs.CC Pub Date : 2019-06-24
    Amir M. Ben-Amram; Geoff Hamilton

    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

  • A novel class based searching algorithm in small world internet of drone network
    Comput. Commun. (IF 2.766) Pub Date : 2020-03-30
    Abdul Rehman; Anand Paul; Awais Ahmad; Gwanggil Jeon

    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

  • Classification method of CO2 hyperspectral remote sensing data based on neural network
    Comput. Commun. (IF 2.766) Pub Date : 2020-03-30
    Le Zhang; Jinsong Wang; Zhiyong An

    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

  • Vehicle communication network in intelligent transportation system based on internet of things
    Comput. Commun. (IF 2.766) Pub Date : 2020-03-30
    Hong Zhang; Xinxin Lu

    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

  • A probabilistic comparison-based fault diagnosis for hybrid faults in mobile networks
    Comput. Commun. (IF 2.766) Pub Date : 2020-03-30
    Hazim Jarrah; Peter H.J. Chong; Chris Rapson; Nurul I. Sarkar; Jairo Gutierrez

    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

  • Research on the identification and management of vehicle behaviour based on Internet of things technology
    Comput. Commun. (IF 2.766) Pub Date : 2020-03-29
    Xueli Feng; Jie Hu

    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

  • Resource allocation solution for sensor networks using improved chaotic firefly algorithm in IoT environment
    Comput. Commun. (IF 2.766) Pub Date : 2020-03-29
    Zhiyong Wang; Dong Liu; Alireza Jolfaei

    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

  • On-Fly-TOD: an efficient mechanism for crosstalk fault reduction in WNoC
    J. Supercomput. (IF 2.157) Pub Date : 2020-03-30
    Zahra Shirmohammadi, Marjan Asadinia

    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

  • DiffPageRank: an efficient differential PageRank approach in MapReduce
    J. Supercomput. (IF 2.157) Pub Date : 2020-03-30
    Maryam Nooraei Abadeh, Mansooreh Mirzaie

    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

  • Strategies for array data retrieval from a relational back-end based on access patterns
    Computing (IF 2.063) Pub Date : 2020-03-30
    Andrej Andrejev, Kjell Orsborn, Tore Risch

    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

  • Long-term real time object tracking based on multi-scale local correlation filtering and global re-detection
    Computing (IF 2.063) Pub Date : 2020-03-30
    Qi Zhao, Boxue Zhang, Wenquan Feng, Zhiying Du, Hong Zhang, Daniel Sun

    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

  • Performance analysis of the ubiquitous and emergent properties of an autonomic reflective middleware for smart cities
    Computing (IF 2.063) Pub Date : 2020-03-30
    Jose Aguilar, M. Jerez, M. Mendonça, M. Sánchez

    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

  • Incremental and diffusion compressive sensing strategies over distributed networks
    Digit. Signal Process. (IF 2.792) Pub Date : 2020-03-30
    Ghanbar Azarnia; Mohammad Ali Tinati; Abbas Ali Sharifi; Hamid Shiri

    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

  • Improved covariant local feature detector
    Pattern Recogn. Lett. (IF 2.810) Pub Date : 2020-03-30
    Zhanqiang Huo; Yanqi Zhang; Hongmin Liu; Jing Wang; Xin Liu; Jiyong Zhang

    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

  • Prediction of bank telephone marketing results based on improved whale algorithms optimizing S_Kohonen network
    Appl. Soft Comput. (IF 4.873) Pub Date : 2020-03-30
    Chun Yan; Meixuan Li; Wei Liu

    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

  • Pareto optimality and game theory approach for optimal deployment of dg in radial distribution system to improve techno-economic benefits
    Appl. Soft Comput. (IF 4.873) Pub Date : 2020-03-30
    Srinivas Nagaballi; Vijay S. Kale

    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

  • Optimizing the DNA fragment assembly using metaheuristic-based overlap layout consensus approach
    Appl. Soft Comput. (IF 4.873) Pub Date : 2020-03-30
    Uzma; Zahid Halim

    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

  • Distributed Reconfiguration of Maximal Independent Sets
    J. Comput. Syst. Sci. (IF 1.129) Pub Date : 2020-03-30
    Keren Censor-Hillel; Mikaël Rabie

    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

  • Asymptotic growth rate of square grids dominating sets: a symbolic dynamics approach
    Theor. Comput. Sci. (IF 0.718) Pub Date : 2020-03-30
    Silvère Gangloff; Alexandre Talon

    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.

  • Calibration Scheduling with Time Slot Cost
    Theor. Comput. Sci. (IF 0.718) Pub Date : 2020-03-30
    Kai Wang

    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

  • Makespan minimization on unrelated parallel machines with a few bags
    Theor. Comput. Sci. (IF 0.718) Pub Date : 2020-03-30
    Daniel R. Page; Roberto Solis-Oba

    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

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