On Minimum Maximal Distance-k Matchings

We study the computational complexity of several problems connected with finding a maximal distance-$k$ matching of minimum cardinality or minimum weight in a given graph. We introduce the class of $k$-equimatchable graphs which is an edge analogue of $k$-equipackable graphs. We prove that the recognition of $k$-equimatchable graphs is co-NP-complete for any fixed $k \ge 2$. We provide a simple characterization for the class of strongly chordal graphs with equal $k$-packing and $k$-domination numbers. We also prove that for any fixed integer $\ell \ge 1$ the problem of finding a minimum weight maximal distance-$2\ell$ matching and the problem of finding a minimum weight $(2 \ell - 1)$-independent dominating set cannot be approximated in polynomial time in chordal graphs within a factor of $\delta \ln |V(G)|$ unless $\mathrm{P} = \mathrm{NP}$, where $\delta$ is a fixed constant (thereby improving the NP-hardness result of Chang for the independent domination case). Finally, we show the NP-hardness of the minimum maximal induced matching and independent dominating set problems in large-girth planar graphs.Comment: 15 pages, 4 figure

On Existential MSO and its Relation to ETH

Impagliazzo et al. proposed a framework, based on the logic fragment defining the complexity class SNP, to identify problems that are equivalent to k-CNF-Sat modulo subexponential-time reducibility (serf-reducibility). The subexponential-time solvability of any of these problems implies the failure of the Exponential Time Hypothesis (ETH). In this paper, we extend the framework of Impagliazzo et al., and identify a larger set of problems that are equivalent to k-CNF-Sat modulo serf-reducibility. We propose a complexity class, referred to as Linear Monadic NP, that consists of all problems expressible in existential monadic second order logic whose expressions have a linear measure in terms of a complexity parameter, which is usually the universe size of the problem. This research direction can be traced back to Fagin\u27s celebrated theorem stating that NP coincides with the class of problems expressible in existential second order logic. Monadic NP, a well-studied class in the literature, is the restriction of the aforementioned logic fragment to existential monadic second order logic. The proposed class Linear Monadic NP is then the restriction of Monadic NP to problems whose expressions have linear measure in the complexity parameter. We show that Linear Monadic NP includes many natural complete problems such as the satisfiability of linear-size circuits, dominating set, independent dominating set, and perfect code. Therefore, for any of these problems, its subexponential-time solvability is equivalent to the failure of ETH. We prove, using logic games, that the aforementioned problems are inexpressible in the monadic fragment of SNP, and hence, are not captured by the framework of Impagliazzo et al. Finally, we show that Feedback Vertex Set is inexpressible in existential monadic second order logic, and hence is not in Linear Monadic NP, and investigate the existence of certain reductions between Feedback Vertex Set (and variants of it) and 3-CNF-Sat

Launching generic attacks on iOS with approved third-party applications

Abstract. iOS is Apple’s mobile operating system, which is used on iPhone, iPad and iPod touch. Any third-party applications developed for iOS devices are required to go through Apple’s application vetting pro-cess and appear on the official iTunes App Store upon approval. When an application is downloaded from the store and installed on an iOS device, it is given a limited set of privileges, which are enforced by iOS applica-tion sandbox. Although details of the vetting process and the sandbox are kept as black box by Apple, it was generally believed that these iOS security mechanisms are effective in defending against malwares. In this paper, we propose a generic attack vector that enables third-party applications to launch attacks on non-jailbroken iOS devices. Fol-lowing this generic attack mechanism, we are able to construct multiple proof-of-concept attacks, such as cracking device PIN and taking snap-shots without user’s awareness. Our applications embedded with the at-tack codes have passed Apple’s vetting process and work as intended on non-jailbroken devices. Our proof-of-concept attacks have shown that Apple’s vetting process and iOS sandbox have weaknesses which can be exploited by third-party applications. We further provide corresponding mitigation strategies for both vetting and sandbox mechanisms, in order to defend against the proposed attack vector.

TAI-SARNET: Deep Transferred Atrous-Inception CNN for Small Samples SAR ATR

Since Synthetic Aperture Radar (SAR) targets are full of coherent speckle noise, the traditional deep learning models are difficult to effectively extract key features of the targets and share high computational complexity. To solve the problem, an effective lightweight Convolutional Neural Network (CNN) model incorporating transfer learning is proposed for better handling SAR targets recognition tasks. In this work, firstly we propose the Atrous-Inception module, which combines both atrous convolution and inception module to obtain rich global receptive fields, while strictly controlling the parameter amount and realizing lightweight network architecture. Secondly, the transfer learning strategy is used to effectively transfer the prior knowledge of the optical, non-optical, hybrid optical and non-optical domains to the SAR target recognition tasks, thereby improving the model\u2019s recognition performance on small sample SAR target datasets. Finally, the model constructed in this paper is verified to be 97.97% on ten types of MSTAR datasets under standard operating conditions, reaching a mainstream target recognition rate. Meanwhile, the method presented in this paper shows strong robustness and generalization performance on a small number of randomly sampled SAR target datasets

The complexity of approximately counting in 2-spin systems on kk-uniform bounded-degree hypergraphs

One of the most important recent developments in the complexity of approximate counting is the classification of the complexity of approximating the partition functions of antiferromagnetic 2-spin systems on bounded-degree graphs. This classification is based on a beautiful connection to the so-called uniqueness phase transition from statistical physics on the infinite $\Delta$-regular tree. Our objective is to study the impact of this classification on unweighted 2-spin models on $k$-uniform hypergraphs. As has already been indicated by Yin and Zhao, the connection between the uniqueness phase transition and the complexity of approximate counting breaks down in the hypergraph setting. Nevertheless, we show that for every non-trivial symmetric $k$-ary Boolean function $f$ there exists a degree bound $\Delta_0$ so that for all $\Delta \geq \Delta_0$ the following problem is NP-hard: given a $k$-uniform hypergraph with maximum degree at most $\Delta$, approximate the partition function of the hypergraph 2-spin model associated with $f$. It is NP-hard to approximate this partition function even within an exponential factor. By contrast, if $f$ is a trivial symmetric Boolean function (e.g., any function $f$ that is excluded from our result), then the partition function of the corresponding hypergraph 2-spin model can be computed exactly in polynomial time

The Observer

Student newspaper for Central Washington University for December 3-9, 2015. Vol. 101, No. 9.https://digitalcommons.cwu.edu/cwu_student_newspaper/5691/thumbnail.jp

Re: Ornament

Re:Ornament calls for a rethinking of ornament within the history and practice of design, urging a broad reconsideration of ornament’s value and a complete reimagining of ornament’s future potential. Charting the arc of ornament in the Western tradition, this thesis reexamines the impact of modernism’s rejection of ornament—and, with it, its embedded culture, history, knowledge and craft. Studying ornament’s structure as a language, I make the case for ornament’s inherent beauty and excess and speculate on how ornament could apply to thinking and making beyond design. Through graphic form, material exploration and pattern thinking, I negotiate these complexities with work that is intrinsically structural, deeply ornamental and often a hybrid of the material and the digital, the hand and the machine. As such, my work is not only a response to—or rebuttal of—modernism, but also a call to action and an invitation to remember, recalibrate and remake our perception and use of ornament today

Geographische Räume, neu konstruiert

Die als technosozialer Prozess verstandene Digitalisierung beeinflusst nahezu alle Bereiche der Gesellschaft. Die damit im Zusammenhang stehenden Entwicklungen verlaufen in der Regel langsam und über längere Zeiträume, weshalb entsprechende Veränderungen oft erst im Nachhinein deutlich werden. Noch weniger offensichtlich sind die Auswirkungen der digitalen Technologien auf das Konzept des geographischen Raums, das, verstanden als eine Reihe von sozial konstruierten Beziehungen zwischen auf der Erdoberfläche befindlichen Einheiten, bereits für sich genommen abstrakt ist. Dennoch unterliegt der geographische Raum als Konzept derzeit einem tiefgreifenden Wandel. Digitale Technologien können Geographien ermöglichen oder behindern, ihre Gestaltung und Wahrnehmung beeinflussen oder Handlungen auslösen, die eine räumliche Manifestation haben. Dieses Kapitel bietet eine Diskussion geographischer Wissensordnungen, die sich unter dem Einfluss der Digitalisierung zu verändern scheinen. Eine Einführung in die technologischen und soziokulturellen Aspekte des Einflusses digitaler Prozesse auf geographische Räume liefert zunächst die Grundlagen für die zu diskutierenden Veränderungsprozesse. Darauf aufbauend werden verschiedene digital-geographische Raumvorstellungen aus der Humangeographie vorgestellt, da diese die Kontexte bilden, in denen digital beeinflusste geographische Informationen entstehen. Letztere bilden die Grundlage für Wissen. Daher werden verschiedene prototypische Formen geographischer Information kurz vorgestellt. Die anschließende Diskussion der sich wandelnden geographischen Wissensordnungen zeigt, dass die Digitalisierung zu einer Mischform des Wissens über geographische Sachverhalte führt: Einerseits gibt es digital geprägtes lokales Erfahrungswissen (aus erster Hand), das andererseits auch Merkmale von formalisiertem propositionalem Wissen aufweist. Darüber hinaus wird in diesem Kapitel argumentiert, dass trotz gegenteiliger Prognosen, insbesondere aus den 1990er Jahren, die Geographie als organisierendes Strukturelement für Wissen an Bedeutung gewinnt, und zwar nicht in traditioneller Weise in Bezug auf Länder oder Regionen, sondern in unregelmäßiger und hyperlokaler Weise über Orte, die sowohl digital als auch physisch präsent sind