OpenRaiser/Intern-Atlas huggingface dataset:
Mutual Community Detection across Multiple Partially Aligned Social Networks
Venue: arXiv cs.SI 2015
Year: 2015

Community detection in online social networks has been a hot research topic in recent years. Meanwhile, to enjoy more social network services, users nowadays are usually involved in multiple online social networks simultaneously, some of which can share common information and structures. Networks that involve some common users are named as multiple "partially aligned networks". In this paper, we want to detect communities of multiple partially aligned networks simultaneously, which is formally defined as the "Mutual Clustering" problem. The "Mutual Clustering" problem is very challenging as it has two important issues to address: (1) how to preserve the network characteristics in mutual community detection? and (2) how to utilize the information in other aligned networks to refine and disambiguate the community structures of the shared users? To solve these two challenges, a novel community detection method, MCD (Mutual Community Detector), is proposed in this paper. MCD can detect social community structures of users in multiple partially aligned networks at the same time with full considerations of (1) characteristics of each network, and (2) information of the shared users across aligned networks. Extensive experiments conducted on two real-world partially aligned heterogeneous social networks demonstrate that MCD can solve the "Mutual Clustering" problem very well.
Point-wise Map Recovery and Refinement from Functional Correspondence
Venue: arXiv cs.CV 2015
Year: 2015

Since their introduction in the shape analysis community, functional maps have met with considerable success due to their ability to compactly represent dense correspondences between deformable shapes, with applications ranging from shape matching and image segmentation, to exploration of large shape collections. Despite the numerous advantages of such representation, however, the problem of converting a given functional map back to a point-to-point map has received a surprisingly limited interest. In this paper we analyze the general problem of point-wise map recovery from arbitrary functional maps. In doing so, we rule out many of the assumptions required by the currently established approach -- most notably, the limiting requirement of the input shapes being nearly-isometric. We devise an efficient recovery process based on a simple probabilistic model. Experiments confirm that this approach achieves remarkable accuracy improvements in very challenging cases.
Cooperative Control in Production and Logistics
Venue: arXiv cs.SY 2015
Year: 2015

Classical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety of interacting, interdependent elements. A paradigm shift, e.g., novel organizing principles and methods, is needed for supporting the interoperability of dynamic alliances of agile and networked systems. Several solution proposals argue that the future of manufacturing and logistics lies in network-like, dynamic, open and reconfigurable systems of cooperative autonomous entities. The paper overviews various distributed approaches and technologies of control engineering and ICT that can support the realization of cooperative structures from the resource level to the level of networked enterprises. Standard results as well as recent advances from control theory, through cooperative game theory, distributed machine learning to holonic systems, cooperative enterprise modelling, system integration, and autonomous logistics processes are surveyed. A special emphasis is put on the theoretical developments and industrial applications of Robustly Feasible Model Predictive Control (RFMPC). Two case studies are also discussed: i) a holonic, PROSA-based approach to generate short-term forecasts for an additive manufacturing system by means of a delegate multi-agent system (D-MAS); and ii) an application of distributed RFMPC to a drinking water distribution system.
Translational and Scaling Formation Maneuver Control via a Bearing-Based Approach
Venue: arXiv cs.SY 2015
Year: 2015

This paper studies distributed maneuver control of multi-agent formations in arbitrary dimensions. The objective is to control the translation and scale of the formation while maintaining the desired formation pattern. Unlike conventional approaches where the target formation is defined by relative positions or distances, we propose a novel bearing-based approach where the target formation is defined by inter-neighbor bearings. Since the bearings are invariant to the translation and scale of the formation, the bearing-based approach provides a simple solution to the problem of translational and scaling formation maneuver control. Linear formation control laws for double-integrator dynamics are proposed and the global formation stability is analyzed. This paper also studies bearing-based formation control in the presence of practical problems including input disturbances, acceleration saturation, and collision avoidance. The theoretical results are illustrated with numerical simulations.
Safety Verification and Refutation by k-invariants and k-induction (extended version)
Venue: arXiv cs.LO 2015
Year: 2015

Most software verification tools can be classified into one of a number of established families, each of which has their own focus and strengths. For example, concrete counterexample generation in model checking, invariant inference in abstract interpretation and completeness via annotation for deductive verification. This creates a significant and fundamental usability problem as users may have to learn and use one technique to find potential problems but then need an entirely different one to show that they have been fixed. This paper presents a single, unified algorithm kIkI, which strictly generalises abstract interpretation, bounded model checking and k-induction. This not only combines the strengths of these techniques but allows them to interact and reinforce each other, giving a `single-tool' approach to verification.
A multipath energy-conserving routing protocol for wireless ad hoc networks lifetime improvement
Venue: arXiv cs.NI 2015
Year: 2015

Ad hoc networks are wireless mobile networks that can operate without infrastructure and without centralized network management. Traditional techniques of routing are not well adapted. Indeed, their lack of reactivity with respect to the variability of network changes makes them difficult to use. Moreover, conserving energy is a critical concern in the design of routing protocols for ad hoc networks, because most mobile nodes operate with limited battery capacity, and the energy depletion of a node affects not only the node itself but also the overall network lifetime. In all proposed single-path routing schemes a new path-discovery process is required once a path failure is detected, and this process causes delay and wastage of node resources. A multipath routing scheme is an alternative to maximize the network lifetime. In this paper, we propose an energy-efficient multipath routing protocol, called AOMR-LM (Ad hoc On-demand Multipath Routing with Lifetime Maximization), which preserves the residual energy of nodes and balances the consumed energy to increase the network lifetime. To achieve this goal, we used the residual energy of nodes for calculating the node energy level. The multipath selection mechanism uses this energy level to classify the paths. Two parameters are analyzed: the energy threshold beta and the coefficient alpha. These parameters are required to classify the nodes and to ensure the preservation of node energy. Our protocol improves the performance of mobile ad hoc networks by prolonging the lifetime of the network. This novel protocol has been compared with other protocols: AOMDV and ZD-AOMDV. The protocol performance has been evaluated in terms of network lifetime, energy consumption, and end-to-end delay.
"The Sum of Its Parts": Joint Learning of Word and Phrase Representations with Autoencoders
Venue: arXiv cs.CL 2015
Year: 2015

Recently, there has been a lot of effort to represent words in continuous vector spaces. Those representations have been shown to capture both semantic and syntactic information about words. However, distributed representations of phrases remain a challenge. We introduce a novel model that jointly learns word vector representations and their summation. Word representations are learnt using the word co-occurrence statistical information. To embed sequences of words (i.e. phrases) with different sizes into a common semantic space, we propose to average word vector representations. In contrast with previous methods which reported a posteriori some compositionality aspects by simple summation, we simultaneously train words to sum, while keeping the maximum information from the original vectors. We evaluate the quality of the word representations on several classical word evaluation tasks, and we introduce a novel task to evaluate the quality of the phrase representations. While our distributed representations compete with other methods of learning word representations on word evaluations, we show that they give better performance on the phrase evaluation. Such representations of phrases could be interesting for many tasks in natural language processing.
On Systematic Testing for Execution-Time Analysis
Venue: arXiv cs.PL 2015
Year: 2015

Given a program and a time deadline, does the program finish before the deadline when executed on a given platform? With the requirement to produce a test case when such a violation can occur, we refer to this problem as the worst-case execution-time testing (WCETT) problem. In this paper, we present an approach for solving the WCETT problem for loop-free programs by timing the execution of a program on a small number of carefully calculated inputs. We then create a sequence of integer linear programs the solutions of which encode the best timing model consistent with the measurements. By solving the programs we can find the worst-case input as well as estimate execution time of any other input. Our solution is more accurate than previous approaches and, unlikely previous work, by increasing the number of measurements we can produce WCETT bounds up to any desired accuracy. Timing of a program depends on the properties of the platform it executes on. We further show how our approach can be used to quantify the timing repeatability of the underlying platform.
Enhanced Lasso Recovery on Graph
Venue: arXiv cs.LG 2015
Year: 2015

This work aims at recovering signals that are sparse on graphs. Compressed sensing offers techniques for signal recovery from a few linear measurements and graph Fourier analysis provides a signal representation on graph. In this paper, we leverage these two frameworks to introduce a new Lasso recovery algorithm on graphs. More precisely, we present a non-convex, non-smooth algorithm that outperforms the standard convex Lasso technique. We carry out numerical experiments on three benchmark graph datasets.
Measuring Emotional Contagion in Social Media
Venue: arXiv cs.SI 2015
Year: 2015

Social media are used as main discussion channels by millions of individuals every day. The content individuals produce in daily social-media-based micro-communications, and the emotions therein expressed, may impact the emotional states of others. A recent experiment performed on Facebook hypothesized that emotions spread online, even in absence of non-verbal cues typical of in-person interactions, and that individuals are more likely to adopt positive or negative emotions if these are over-expressed in their social network. Experiments of this type, however, raise ethical concerns, as they require massive-scale content manipulation with unknown consequences for the individuals therein involved. Here, we study the dynamics of emotional contagion using Twitter. Rather than manipulating content, we devise a null model that discounts some confounding factors (including the effect of emotional contagion). We measure the emotional valence of content the users are exposed to before posting their own tweets. We determine that on average a negative post follows an over-exposure to 4.34% more negative content than baseline, while positive posts occur after an average over-exposure to 4.50% more positive contents. We highlight the presence of a linear relationship between the average emotional valence of the stimuli users are exposed to, and that of the responses they produce. We also identify two different classes of individuals: highly and scarcely susceptible to emotional contagion. Highly susceptible users are significantly less inclined to adopt negative emotions than the scarcely susceptible ones, but equally likely to adopt positive emotions. In general, the likelihood of adopting positive emotions is much greater than that of negative emotions.
Multi-weighted Automata and MSO Logic
Venue: arXiv cs.LO 2015
Year: 2015

Weighted automata are non-deterministic automata where the transitions are equipped with weights. They can model quantitative aspects of systems like costs or energy consumption. The value of a run can be computed, for example, as the maximum, limit average, or discounted sum of transition weights. In multi-weighted automata, transitions carry several weights and can model, for example, the ratio between rewards and costs, or the efficiency of use of a primary resource under some upper bound constraint on a secondary resource. Here, we introduce a general model for multi-weighted automata as well as a multiweighted MSO logic. In our main results, we show that this multi-weighted MSO logic and multi-weighted automata are expressively equivalent both for finite and infinite words. The translation process is effective, leading to decidability results for our multi-weighted MSO logic.
moco: Fast Motion Correction for Calcium Imaging
Venue: arXiv cs.CV 2015
Year: 2015

Motion correction is the first in a pipeline of algorithms to analyze calcium imaging videos and extract biologically relevant information, for example the network structure of the neurons therein. Fast motion correction would be especially critical for closed-loop activity triggered stimulation experiments, where accurate detection and targeting of specific cells in necessary. Our algorithm uses a Fourier-transform approach, and its efficiency derives from a combination of judicious downsampling and the accelerated computation of many $L_2$ norms using dynamic programming and two-dimensional, fft-accelerated convolutions. Its accuracy is comparable to that of established community-used algorithms, and it is more stable to large translational motions. It is programmed in Java and is compatible with ImageJ.
Uplink Performance of Large Optimum-Combining Antenna Arrays in Power-Controlled Cellular Networks
Venue: arXiv cs.IT 2015
Year: 2015

The uplink of interference-limited cellular networks with base stations that have large numbers of antennas and use linear Minimum-Mean-Square Error (MMSE) processing with power control is analyzed. Simple approximations, which are exact in an asymptotic sense, are provided for the spectral efficiencies (b/s/Hz) of links in these systems. It is also found that when the number of base-station antennas is moderately large, and the number of mobiles in the entire network is large, correlations between the transmit powers of mobiles within a given cell do not significantly influence the spectral efficiency of the system. As a result, mobiles can perform simple power control (e.g. fractional power control) that does not depend on other users in the network, reducing system complexity and improving the analytical tractability of such systems.
Natural Gas Flow Solutions with Guarantees: A Monotone Operator Theory Approach
Venue: arXiv cs.SY 2015
Year: 2015

We consider balanced flows in a natural gas transmission network and discuss computationally hard problems such as establishing if solution of the underlying nonlinear gas flow equations exists, if it is unique, and finding the solution. Particular topologies, e.g. trees, are known to be easy to solve based on a variational description of the gas flow equations, but these approaches do not generalize. In this paper, we show that the gas flow problem can be solved efficiently using the tools of monotone operator theory, provided that we look for solution within certain monotonicity domains. We characterize a family of monotonicity domains, described in terms of Linear Matrix Inequalities (LMI) in the state variables, each containing at most one solution. We also develop an efficient algorithm to choose a particular monotonicity domain, for which the LMI based condition simplifies to a bound on the flows. Performance of the technique is illustrated on exemplary gas networks.
JExtract: An Eclipse Plug-in for Recommending Automated Extract Method Refactorings
Venue: arXiv cs.SE 2015
Year: 2015

Although Extract Method is a key refactoring for improving program comprehension, refactoring tools for such purpose are often underused. To address this shortcoming, we present JExtract, a recommendation system based on structural similarity that identifies Extract Method refactoring opportunities that are directly automated by IDE-based refactoring tools. Our evaluation suggests that JExtract is far more effective (w.r.t. recall and precision) to identify misplaced code in methods than JDeodorant, a state-of-the-art tool
Certified Computation of planar Morse-Smale Complexes
Venue: arXiv cs.CG 2015
Year: 2015

The Morse-Smale complex is an important tool for global topological analysis in various problems of computational geometry and topology. Algorithms for Morse-Smale complexes have been presented in case of piecewise linear manifolds. However, previous research in this field is incomplete in the case of smooth functions. In the current paper we address the following question: Given an arbitrarily complex Morse-Smale system on a planar domain, is it possible to compute its certified (topologically correct) Morse-Smale complex? Towards this, we develop an algorithm using interval arithmetic to compute certified critical points and separatrices forming the Morse-Smale complexes of smooth functions on bounded planar domain. Our algorithm can also compute geometrically close Morse-Smale complexes.
3D Reconstruction from Full-view Fisheye Camera
Venue: arXiv cs.CV 2015
Year: 2015

In this report, we proposed a 3D reconstruction method for the full-view fisheye camera. The camera we used is Ricoh Theta, which captures spherical images and has a wide field of view (FOV). The conventional stereo apporach based on perspective camera model cannot be directly applied and instead we used a spherical camera model to depict the relation between 3D point and its corresponding observation in the image. We implemented a system that can reconstruct the 3D scene using captures from two or more cameras. A GUI is also created to allow users to control the view perspective and obtain a better intuition of how the scene is rebuilt. Experiments showed that our reconstruction results well preserved the structure of the scene in the real world.
Restricted isometry property of random subdictionaries
Venue: arXiv cs.IT 2015
Year: 2015

We study statistical restricted isometry, a property closely related to sparse signal recovery, of deterministic sensing matrices of size $m \times N$. A matrix is said to have a statistical restricted isometry property (StRIP) of order $k$ if most submatrices with $k$ columns define a near-isometric map of ${\mathbb R}^k$ into ${\mathbb R}^m$. As our main result, we establish sufficient conditions for the StRIP property of a matrix in terms of the mutual coherence and mean square coherence. We show that for many existing deterministic families of sampling matrices, $m=O(k)$ rows suffice for $k$-StRIP, which is an improvement over the known estimates of either $m = Θ(k \log N)$ or $m = Θ(k\log k)$. We also give examples of matrix families that are shown to have the StRIP property using our sufficient conditions.
An $O(n^{0.4732})$ upper bound on the complexity of the GKS communication game
Venue: arXiv cs.CC 2015
Year: 2015

We give an $5\cdot n^{\log_{30}5}$ upper bund on the complexity of the communication game introduced by G. Gilmer, M. Koucký and M. Saks \cite{saks} to study the Sensitivity Conjecture \cite{linial}, improving on their $\sqrt{999\over 1000}\sqrt{n}$ bound. We also determine the exact complexity of the game up to $n\le 9$.
A non-parametric k-nearest neighbour entropy estimator
Venue: arXiv cs.IT 2015
Year: 2015

A non-parametric k-nearest neighbour based entropy estimator is proposed. It improves on the classical Kozachenko-Leonenko estimator by considering non-uniform probability densities in the region of k-nearest neighbours around each sample point. It aims at improving the classical estimators in three situations: first, when the dimensionality of the random variable is large; second, when near-functional relationships leading to high correlation between components of the random variable are present; and third, when the marginal variances of random variable components vary significantly with respect to each other. Heuristics on the error of the proposed and classical estimators are presented. Finally, the proposed estimator is tested for a variety of distributions in successively increasing dimensions and in the presence of a near-functional relationship. Its performance is compared with a classical estimator and shown to be a significant improvement.
PAC-Bayes Iterated Logarithm Bounds for Martingale Mixtures
Venue: arXiv cs.LG 2015
Year: 2015

We give tight concentration bounds for mixtures of martingales that are simultaneously uniform over (a) mixture distributions, in a PAC-Bayes sense; and (b) all finite times. These bounds are proved in terms of the martingale variance, extending classical Bernstein inequalities, and sharpening and simplifying prior work.
3D Geometric Analysis of Tubular Objects based on Surface Normal Accumulation
Venue: arXiv cs.GR 2015
Year: 2015

This paper proposes a simple and efficient method for the reconstruction and extraction of geometric parameters from 3D tubular objects. Our method constructs an image that accumulates surface normal information, then peaks within this image are located by tracking. Finally, the positions of these are optimized to lie precisely on the tubular shape centerline. This method is very versatile, and is able to process various input data types like full or partial mesh acquired from 3D laser scans, 3D height map or discrete volumetric images. The proposed algorithm is simple to implement, contains few parameters and can be computed in linear time with respect to the number of surface faces. Since the extracted tube centerline is accurate, we are able to decompose the tube into rectilinear parts and torus-like parts. This is done with a new linear time 3D torus detection algorithm, which follows the same principle of a previous work on 2D arc circle recognition. Detailed experiments show the versatility, accuracy and robustness of our new method.