OpenRaiser/Intern-Atlas huggingface dataset:
Witness of unsatisfiability for a random 3-satisfiability formula
Venue: arXiv cs.CC 2013
Year: 2013

The random 3-satisfiability (3-SAT) problem is in the unsatisfiable (UNSAT) phase when the clause density $α$ exceeds a critical value $α_s \approx 4.267$. However, rigorously proving the unsatisfiability of a given large 3-SAT instance is extremely difficult. In this paper we apply the mean-field theory of statistical physics to the unsatisfiability problem, and show that a specific type of UNSAT witnesses (Feige-Kim-Ofek witnesses) can in principle be constructed when the clause density $α> 19$. We then construct Feige-Kim-Ofek witnesses for single 3-SAT instances through a simple random sampling algorithm and a focused local search algorithm. The random sampling algorithm works only when $α$ scales at least linearly with the variable number $N$, but the focused local search algorithm works for clause densty $α> c N^{b}$ with $b \approx 0.59$ and prefactor $c \approx 8$. The exponent $b$ can be further decreased by enlarging the single parameter $S$ of the focused local search algorithm.
Fast Arithmetic in Algorithmic Self-Assembly
Venue: arXiv cs.DS 2013
Year: 2013

In this paper we consider the time complexity of computing the sum and product of two $n$-bit numbers within the tile self-assembly model. The (abstract) tile assembly model is a mathematical model of self-assembly in which system components are square tiles with different glue types assigned to tile edges. Assembly is driven by the attachment of singleton tiles to a growing seed assembly when the net force of glue attraction for a tile exceeds some fixed threshold. Within this frame work, we examine the time complexity of computing the sum or product of 2 n-bit numbers, where the input numbers are encoded in an initial seed assembly, and the output is encoded in the final, terminal assembly of the system. We show that the problems of addition and multiplication have worst case lower bounds of $Ω(\sqrt{n})$ in 2D assembly, and $Ω(\sqrt[3]{n})$ in 3D assembly. In the case of addition, we design algorithms for both 2D and 3D that meet this bound with worst case run times of $O(\sqrt{n})$ and $O(\sqrt[3]{n})$ respectively, which beats the previous best known upper bound of O(n). Further, we consider average case complexity of addition over uniformly distributed n-bit strings and show how to achieve $O(\log n)$ average case time with a simultaneous $O(\sqrt{n})$ worst case run time in 2D. For multiplication, we present an $O(n^{5/6})$ time multiplication algorithm which works in 3D, which beats the previous best known upper bound of O(n). As additional evidence for the speed of our algorithms, we implement our addition algorithms, along with the simpler O(n) time addition algorithm, into a probabilistic run-time simulator and compare the timing results.
Automatic Detection of Non-deverbal Event Nouns for Quick Lexicon Production
Venue: arXiv cs.CL 2013
Year: 2013

In this work we present the results of our experimental work on the develop-ment of lexical class-based lexica by automatic means. The objective is to as-sess the use of linguistic lexical-class based information as a feature selection methodology for the use of classifiers in quick lexical development. The results show that the approach can help in re-ducing the human effort required in the development of language resources sig-nificantly.
The Price of Connectivity for Vertex Cover
Venue: arXiv cs.DM 2013
Year: 2013

The vertex cover number of a graph is the minimum number of vertices that are needed to cover all edges. When those vertices are further required to induce a connected subgraph, the corresponding number is called the connected vertex cover number, and is always greater or equal to the vertex cover number. Connected vertex covers are found in many applications, and the relationship between those two graph invariants is therefore a natural question to investigate. For that purpose, we introduce the {\em Price of Connectivity}, defined as the ratio between the two vertex cover numbers. We prove that the price of connectivity is at most 2 for arbitrary graphs. We further consider graph classes in which the price of connectivity of every induced subgraph is bounded by some real number $t$. We obtain forbidden induced subgraph characterizations for every real value $t \leq 3/2$. We also investigate critical graphs for this property, namely, graphs whose price of connectivity is strictly greater than that of any proper induced subgraph. Those are the only graphs that can appear in a forbidden subgraph characterization for the hereditary property of having a price of connectivity at most $t$. In particular, we completely characterize the critical graphs that are also chordal. Finally, we also consider the question of computing the price of connectivity of a given graph. Unsurprisingly, the decision version of this question is NP-hard. In fact, we show that it is even complete for the class $Θ_2^P = P^{NP[\log]}$, the class of decision problems that can be solved in polynomial time, provided we can make $O(\log n)$ queries to an NP-oracle. This paves the way for a thorough investigation of the complexity of problems involving ratios of graph invariants.
A local constant-factor approximation algorithm for MDS problem in anonymous network
Venue: arXiv cs.DS 2013
Year: 2013

In research on distributed local algorithms it is commonly assumed that each vertex has a unique identifier in the entire graph. However, it turns out that in case of certain classes of graphs (for example not lift-closed bounded degree graphs) identifiers are unnecessary and only a port ordering is needed. One of the open issues was whether identifiers are essential in planar graphs. In this paper, we answer this question and we propose an algorithm which returns constant approximation of the MDS problem in CONGEST model. The algorithm doesn't use any additional information about the structure of the graph and the nodes don't have unique identifiers. We hope that this paper will be very helpful as a hint for further comparisons of the unique identifier model and the model with only a port numbering in other classes of graphs.
Optimization of the parity-check matrix density in QC-LDPC code-based McEliece cryptosystems
Venue: arXiv cs.IT 2013
Year: 2013

Low-density parity-check (LDPC) codes are one of the most promising families of codes to replace the Goppa codes originally used in the McEliece cryptosystem. In fact, it has been shown that by using quasi-cyclic low-density parity-check (QC-LDPC) codes in this system, drastic reductions in the public key size can be achieved, while maintaining fixed security levels. Recently, some proposals have appeared in the literature using codes with denser parity-check matrices, named moderate-density parity-check (MDPC) codes. However, the density of the parity-check matrices to be used in QC-LDPC code-based variants of the McEliece cryptosystem has never been optimized. This paper aims at filling such gap, by proposing a procedure for selecting the density of the private parity-check matrix, based on the security level and the decryption complexity. We provide some examples of the system parameters obtained through the proposed technique.
Multi-User Multi-Carrier Differential Chaos Shift Keying Communication System
Venue: arXiv cs.OH 2013
Year: 2013

In this paper, a multi user Multi-Carrier Differential Chaos Shift Keying (MC-DCSK) modulation is presented. The system endeavors to provide a good trade-off between robustness, energy efficiency and high data rate, while still being simple. In this architecture of MC-DCSK system, for each user, chaotic reference sequence is transmitted over a predefined subcarrier frequency. Multiple modulated data streams are transmitted over the remaining subcarriers allocated for each user. This transmitter structure saves energy and increases the spectral efficiency of the conventional DCSK system.
Kernel Sparse Models for Automated Tumor Segmentation
Venue: arXiv cs.CV 2013
Year: 2013

In this paper, we propose sparse coding-based approaches for segmentation of tumor regions from MR images. Sparse coding with data-adapted dictionaries has been successfully employed in several image recovery and vision problems. The proposed approaches obtain sparse codes for each pixel in brain magnetic resonance images considering their intensity values and location information. Since it is trivial to obtain pixel-wise sparse codes, and combining multiple features in the sparse coding setup is not straightforward, we propose to perform sparse coding in a high-dimensional feature space where non-linear similarities can be effectively modeled. We use the training data from expert-segmented images to obtain kernel dictionaries with the kernel K-lines clustering procedure. For a test image, sparse codes are computed with these kernel dictionaries, and they are used to identify the tumor regions. This approach is completely automated, and does not require user intervention to initialize the tumor regions in a test image. Furthermore, a low complexity segmentation approach based on kernel sparse codes, which allows the user to initialize the tumor region, is also presented. Results obtained with both the proposed approaches are validated against manual segmentation by an expert radiologist, and the proposed methods lead to accurate tumor identification.
Revealing Cluster Structure of Graph by Path Following Replicator Dynamic
Venue: arXiv cs.LG 2013
Year: 2013

In this paper, we propose a path following replicator dynamic, and investigate its potentials in uncovering the underlying cluster structure of a graph. The proposed dynamic is a generalization of the discrete replicator dynamic. The replicator dynamic has been successfully used to extract dense clusters of graphs; however, it is often sensitive to the degree distribution of a graph, and usually biased by vertices with large degrees, thus may fail to detect the densest cluster. To overcome this problem, we introduce a dynamic parameter, called path parameter, into the evolution process. The path parameter can be interpreted as the maximal possible probability of a current cluster containing a vertex, and it monotonically increases as evolution process proceeds. By limiting the maximal probability, the phenomenon of some vertices dominating the early stage of evolution process is suppressed, thus making evolution process more robust. To solve the optimization problem with a fixed path parameter, we propose an efficient fixed point algorithm. The time complexity of the path following replicator dynamic is only linear in the number of edges of a graph, thus it can analyze graphs with millions of vertices and tens of millions of edges on a common PC in a few minutes. Besides, it can be naturally generalized to hypergraph and graph with edges of different orders. We apply it to four important problems: maximum clique problem, densest k-subgraph problem, structure fitting, and discovery of high-density regions. The extensive experimental results clearly demonstrate its advantages, in terms of robustness, scalability and flexility.
Work Issues in Software Engineering
Venue: arXiv cs.SE 2013
Year: 2013

Using data from a web-based survey of software developers, the author attempts to determine root causes of "death march" projects and excessive work hours in the software industry in relation to company practices and management. Special emphasis is placed on the factor of business/technical supervisor background. An analysis of variance revealed significant differences between these supervisor groups with regard to a "Pointy-Haired Boss" (PHB) sentiment index. This difference, combined with correlations between the PHB index and the endpoints of project failure and use of software engineering practices, indicate some disparity in the suitability of businessbackground supervisors to manage software development projects compared with their technical-background counterparts. Other survey data points to improved project management skills as the biggest necessity for supervisors in the business-background group.
Secure Wireless Communications via Cooperative Transmitting
Venue: arXiv cs.CR 2013
Year: 2013

Information theoretic secrecy is combined with cryptographic secrecy to create a secret-key exchange protocol for wireless networks. A network of transmitters, which already have cryptographically secured channels between them, cooperate to exchange a secret key with a new receiver at a random location, in the presence of passive eavesdroppers at unknown locations. Two spatial point processes: homogeneous Poisson process and independent uniformly distributed points are used for the spatial distributions of transmitters and eavesdroppers. We analyse the impact of the number of cooperating transmitters and the number of eavesdroppers on the area fraction where secure communication is possible. Upper bounds on the probability of existence of positive secrecy between the cooperating transmitters and the receiver are derived. The closeness of the upper bounds to the real value is then estimated by means of numerical simulations. Simulations also indicate that a deterministic spatial distribution for the transmitters e.g. hexagonal and square lattices, increases the probability of existence of positive secrecy capacity compared to the random spatial distributions. For the same number of friendly nodes, cooperative transmitting provides a dramatically larger secrecy region than cooperative jamming and cooperative relaying.
Is Cheeger-type Approximation Possible for Nonuniform Sparsest Cut?
Venue: arXiv cs.DS 2013
Year: 2013

In the {\em nonuniform sparsest cut} problem, given two undirected graphs $G$ and $H$ over the same set of vertices $V$, we want to find a cut $(S,V-S)$ that minimizes the ratio between the fraction of $G$-edges that are cut and the fraction of $H$-edges that are cut. The ratio (which is at most 1 in an optimal solution) is called the {\em sparsity} of the cut. In the {\em uniform sparsest cut} problem, $H$ is a clique over $V$. If $G$ is regular, it is possible to find a solution to the uniform sparsest cut of cost $O(\sqrt{opt})$ in nearly linear time. Is such an approximation, which we call "Cheege-type" approximation, achievable in the non-uniform case? We show that the answer is negative, assuming the Unique Games Conjecture, for general H. Furthermore, the Leighton-Rao linear programming relaxation and the spectral relaxation fail to find such an approximation even if $H$ is a clique over a subset of vertices. Using semidefinite programming, however, we can find Cheeger-type approximations in polynomial time whenever the adjacency matrix of $H$ has rank 1. (This includes the cases in which $H$ is a clique over a subset of vertices.)
Efficient Codes for Limited View Adversarial Channels
Venue: arXiv cs.IT 2013
Year: 2013

We introduce randomized Limited View (LV) adversary codes that provide protection against an adversary that uses their partial view of the communication to construct an adversarial error vector to be added to the channel. For a codeword of length N, the adversary selects a subset of ρ_rN of the codeword components to "see", and then "adds" an adversarial error vector of weight ρ_wN to the codeword. Performance of the code is measured by the probability of the decoder failure in recovering the sent message. An (N, q^{RN},δ)-limited view adversary code ensures that the success chance of the adversary in making decoder fail, is bounded by δwhen the information rate of the code is at least R. Our main motivation to study these codes is providing protection for wireless communication at the physical layer of networks. We formalize the definition of adversarial error and decoder failure, construct a code with efficient encoding and decoding that allows the adversary to, depending on the code rate, read up to half of the sent codeword and add error on the same coordinates. The code is non-linear, has an efficient decoding algorithm, and is constructed using a message authentication code (MAC) and a Folded Reed-Solomon (FRS) code. The decoding algorithm uses an innovative approach that combines the list decoding algorithm of the FRS codes and the MAC verification algorithm to eliminate the exponential size of the list output from the decoding algorithm. We discuss application of our results to Reliable Message Transmission problem, and open problems for future work.
Research and Simulation on Drivers' Route Choice Behavior Cognition Model
Venue: arXiv cs.NI 2013
Year: 2013

This paper studied the behavior-cognitive model of drivers during their travel based on the current research on driver behavior. Firstly, a route choice behavior-cognitive model was proposed for describing the decision-making mechanism of drivers during his travel; then, simulation experiments were carried out on the cosimulation VBc-vissim platform. From the experimental results, dynamic behavior features of drivers during their travel can be properly explained by the behavior-cognitive model, thus optimal path can be obtained from this model.
Fourth-order flows in surface modelling
Venue: arXiv cs.GR 2013
Year: 2013

This short article is a brief account of the usage of fourth-order curvature flow in surface modelling.
Probabilistic Topic and Syntax Modeling with Part-of-Speech LDA
Venue: arXiv cs.CL 2013
Year: 2013

This article presents a probabilistic generative model for text based on semantic topics and syntactic classes called Part-of-Speech LDA (POSLDA). POSLDA simultaneously uncovers short-range syntactic patterns (syntax) and long-range semantic patterns (topics) that exist in document collections. This results in word distributions that are specific to both topics (sports, education, ...) and parts-of-speech (nouns, verbs, ...). For example, multinomial distributions over words are uncovered that can be understood as "nouns about weather" or "verbs about law". We describe the model and an approximate inference algorithm and then demonstrate the quality of the learned topics both qualitatively and quantitatively. Then, we discuss an NLP application where the output of POSLDA can lead to strong improvements in quality: unsupervised part-of-speech tagging. We describe algorithms for this task that make use of POSLDA-learned distributions that result in improved performance beyond the state of the art.
On Periodic Reference Tracking Using Batch-Mode Reinforcement Learning with Application to Gene Regulatory Network Control
Venue: arXiv cs.SY 2013
Year: 2013

In this paper, we consider the periodic reference tracking problem in the framework of batch-mode reinforcement learning, which studies methods for solving optimal control problems from the sole knowledge of a set of trajectories. In particular, we extend an existing batch-mode reinforcement learning algorithm, known as Fitted Q Iteration, to the periodic reference tracking problem. The presented periodic reference tracking algorithm explicitly exploits a priori knowledge of the future values of the reference trajectory and its periodicity. We discuss the properties of our approach and illustrate it on the problem of reference tracking for a synthetic biology gene regulatory network known as the generalised repressilator. This system can produce decaying but long-lived oscillations, which makes it an interesting system for the tracking problem. In our companion paper we also take a look at the regulation problem of the toggle switch system, where the main goal is to drive the system's states to a specific bounded region in the state space.
Type-theoretical natural language semantics: on the system F for meaning assembly
Venue: arXiv cs.LO 2013
Year: 2013

This paper presents and extends our type theoretical framework for a compositional treatment of natural language semantics with some lexical features like coercions (e.g. of a town into a football club) and copredication (e.g. on a town as a set of people and as a location). The second order typed lambda calculus was shown to be a good framework, and here we discuss how to introduced predefined types and coercive subtyping which are much more natural than internally coded similar constructs. Linguistic applications of these new features are also exemplified.
Computing Motion with 3D Memristive Grid
Venue: arXiv cs.CV 2013
Year: 2013

Computing the relative motion of objects is an important navigation task that we routinely perform by relying on inherently unreliable biological cells in the retina. The non-linear and adaptive response of memristive devices make them excellent building blocks for realizing complex synaptic-like architectures that are common in the human retina. Here, we introduce a novel memristive thresholding scheme that facilitates the detection of moving edges. In addition, a double-layered 3-D memristive network is employed for modeling the motion computations that take place in both the Outer Plexiform Layer (OPL) and Inner Plexiform Layer (IPL) that enables the detection of on-center and off-center transient responses. Applying the transient detection results, it is shown that it is possible to generate an estimation of the speed and direction a moving object.
Optical Flow Sensing and the Inverse Perception Problem for Flying Bats
Venue: arXiv cs.SY 2013
Year: 2013

The movements of birds, bats, and other flying species are governed by complex sensorimotor systems that allow the animals to react to stationary environmental features as well as to wind disturbances, other animals in nearby airspace, and a wide variety of unexpected challenges. The paper and talk will describe research that analyzes the three-dimensional trajectories of bats flying in a habitat in Texas. The trajectories are computed with stereoscopic methods using data from synchronous thermal videos that were recorded with high temporal and spatial resolution from three viewpoints. Following our previously reported work, we examine the possibility that bat trajectories in this habitat are governed by optical flow sensing that interpolates periodic distance measurements from echolocation. Using an idealized geometry of bat eyes, we introduce the concept of time-to-transit, and recall some research that suggests that this quantity is computed by the animals' visual cortex. Several steering control laws based on time-to-transit are proposed for an idealized flight model, and it is shown that these can be used to replicate the observed flight of what we identify as typical bats. Although the vision-based motion control laws we propose and the protocols for switching between them are quite simple, some of the trajectories that have been synthesized are qualitatively bat-like. Examination of the control protocols that generate these trajectories suggests that bat motions are governed both by their reactions to a subset of key feature points as well by their memories of where these feature points are located.
On Optimal Input Design for Feed-forward Control
Venue: arXiv cs.SY 2013
Year: 2013

This paper considers optimal input design when the intended use of the identified model is to construct a feed-forward controller based on measurable disturbances. The objective is to find a minimum power excitation signal to be used in system identification experiment, such that the corresponding model-based feed-forward controller guarantees, with a given probability, that the variance of the output signal is within given specifications. To start with, some low order model problems are analytically solved and fundamental properties of the optimal input signal solution are presented. The optimal input signal contains feed-forward control and depends of the noise model and transfer function of the system in a specific way. Next, we show how to apply the partial correlation approach to closed loop optimal experiment design to the general feed-forward problem. A framework for optimal input signal design for feed-forward control is presented and numerically evaluated on a temperature control problem.