OpenRaiser/Intern-Atlas huggingface dataset:
Toward a deeper understanding of Visualization through keyword analysis
Venue: arXiv cs.DL 2014
Year: 2014

We present the results of a comprehensive analysis of visualization paper keywords supplied for 4366 papers submitted to five main visualization conferences. We describe main keywords, topic areas, and 10-year historic trends from two datasets: (1) the standardized PCS taxonomy keywords in use for paper submissions for IEEE InfoVis, IEEE Vis-SciVis, IEEE VAST, EuroVis, and IEEE PacificVis since 2009 and (2) the author-chosen keywords for papers published in the IEEE Visualization conference series (now called IEEE VIS) since 2004. Our analysis of research topics in visualization can serve as a starting point to (a) help create a common vocabulary to improve communication among different visualization sub-groups, (b) facilitate the process of understanding differences and commonalities of the various research sub-fields in visualization, (c) provide an understanding of emerging new research trends, (d) facilitate the crucial step of finding the right reviewers for research submissions, and (e) it can eventually lead to a comprehensive taxonomy of visualization research. One additional tangible outcome of our work is an application that allows visualization researchers to easily browse the 2600+ keywords used for IEEE VIS papers during the past 10 years, aiming at more informed and, hence, more effective keyword selections for future visualization publications.
2D View Aggregation for Lymph Node Detection Using a Shallow Hierarchy of Linear Classifiers
Venue: arXiv cs.CV 2014
Year: 2014

Enlarged lymph nodes (LNs) can provide important information for cancer diagnosis, staging, and measuring treatment reactions, making automated detection a highly sought goal. In this paper, we propose a new algorithm representation of decomposing the LN detection problem into a set of 2D object detection subtasks on sampled CT slices, largely alleviating the curse of dimensionality issue. Our 2D detection can be effectively formulated as linear classification on a single image feature type of Histogram of Oriented Gradients (HOG), covering a moderate field-of-view of 45 by 45 voxels. We exploit both simple pooling and sparse linear fusion schemes to aggregate these 2D detection scores for the final 3D LN detection. In this manner, detection is more tractable and does not need to perform perfectly at instance level (as weak hypotheses) since our aggregation process will robustly harness collective information for LN detection. Two datasets (90 patients with 389 mediastinal LNs and 86 patients with 595 abdominal LNs) are used for validation. Cross-validation demonstrates 78.0% sensitivity at 6 false positives/volume (FP/vol.) (86.1% at 10 FP/vol.) and 73.1% sensitivity at 6 FP/vol. (87.2% at 10 FP/vol.), for the mediastinal and abdominal datasets respectively. Our results compare favorably to previous state-of-the-art methods.
Distributed Diffusion-Based LMS for Node-Specific Adaptive Parameter Estimation
Venue: arXiv cs.CY 2014
Year: 2014

A distributed adaptive algorithm is proposed to solve a node-specific parameter estimation problem where nodes are interested in estimating parameters of local interest, parameters of common interest to a subset of nodes and parameters of global interest to the whole network. To address the different node-specific parameter estimation problems, this novel algorithm relies on a diffusion-based implementation of different Least Mean Squares (LMS) algorithms, each associated with the estimation of a specific set of local, common or global parameters. Coupled with the estimation of the different sets of parameters, the implementation of each LMS algorithm is only undertaken by the nodes of the network interested in a specific set of local, common or global parameters. The study of convergence in the mean sense reveals that the proposed algorithm is asymptotically unbiased. Moreover, a spatial-temporal energy conservation relation is provided to evaluate the steady-state performance at each node in the mean-square sense. Finally, the theoretical results and the effectiveness of the proposed technique are validated through computer simulations in the context of cooperative spectrum sensing in Cognitive Radio networks.
Bounded, minimal, and short representations of unit interval and unit circular-arc graphs
Venue: arXiv cs.DM 2014
Year: 2014

We consider the unrestricted, minimal, and bounded representation problems for unit interval (UIG) and unit circular-arc (UCA) graphs. In the unrestricted version, a proper circular-arc (PCA) model $\cal M$ is given and the goal is to obtain an equivalent UCA model $\cal U$. We show a linear time algorithm with negative certification that can also be implemented to run in logspace. In the bounded version, $\cal M$ is given together with some lower and upper bounds that the beginning points of $\cal U$ must satisfy. We develop a linear space $O(n^2)$ time algorithm for this problem. Finally, in the minimal version, the circumference of the circle and the length of the arcs in $\cal U$ must be simultaneously as minimum as possible. We prove that every UCA graph admits such a minimal model, and give a polynomial time algorithm to find it. We also consider the minimal representation problem for UIG graphs. As a bad result, we show that the previous linear time algorithm fails to provide a minimal model for some input graphs. We fix this algorithm but, unfortunately, it runs in linear space $O(n^2)$ time. Finally, we apply the minimal representation algorithms so as to find the minimum powers of paths and cycles that contain a given UIG and UCA models, respectively.
Online networks and subjective well-being
Venue: arXiv cs.CY 2014
Year: 2014

We argue that the use of online networks may threaten subjective well-being in several ways, due to the inherent attributes of Internet-mediated interaction and through its effects on social trust and sociability. We test our hypotheses on a representative sample of the Italian population. We find a significantly negative correlation between online networking and well-being. This result is partially confirmed after accounting for endogeneity. We explore the direct and indirect effects of the use of social networking sites (SNS) on well-being in a SEM analysis. We find that online networking plays a positive role in subjective well-being through its impact on physical interactions, whereas SNS use is associated with lower social trust. The overall effect of networking on individual welfare is significantly negative.
Turkish Presidential Elections TRT Publicity Speech Facial Expression Analysis
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, facial expressions of the three Turkish presidential candidates Demirtas, Erdogan and Ihsanoglu (in alphabetical order) are analyzed during the publicity speeches featured at TRT (Turkish Radio and Television) on 03.08.2014. FaceReader is used for the analysis where 3D modeling of the face is achieved using the active appearance models (AAM). Over 500 landmark points are tracked and analyzed for obtaining the facial expressions during the whole speech. All source videos and the data are publicly available for research purposes.
On BMD Target Tracking: Data Association and Data Fusion
Venue: arXiv cs.SY 2014
Year: 2014

In this paper we consider multitarget tracking with multiple sensors for BMD. In a previous paper multitarget tracking with a single sensor was considered [8]. A ballistic missile may be in several pieces, presenting multiple targets. Besides the ground based or ship sensor there is also the missile seeker. We consider algorithms for generating and maintaining the tracks needed for BMD. A cue of a BM from a non-organic tracking system may also be received. We consider whether the cue is already in the local track file or is a new track. The cue information can improve the existing local track.
Overhead Performance Tradeoffs - A Resource Allocation Perspective
Venue: arXiv cs.IT 2014
Year: 2014

A key aspect of many resource allocation problems is the need for the resource controller to compute a function, such as the max or arg max, of the competing users metrics. Information must be exchanged between the competing users and the resource controller in order for this function to be computed. In many practical resource controllers the competing users' metrics are communicated to the resource controller, which then computes the desired extremization function. However, in this paper it is shown that information rate savings can be obtained by recognizing that controller only needs to determine the result of this extremization function. If the extremization function is to be computed losslessly, the rate savings are shown in most cases to be at most 2 bits independent of the number of competing users. Motivated by the small savings in the lossless case, simple achievable schemes for both the lossy and interactive variants of this problem are considered. It is shown that both of these approaches have the potential to realize large rate savings, especially in the case where the number of competing users is large. For the lossy variant, it is shown that the proposed simple achievable schemes are in fact close to the fundamental limit given by the rate distortion function.
Actin automata: Phenomenology and localizations
Venue: arXiv cs.ET 2014
Year: 2014

Actin is a globular protein which forms long filaments in the eukaryotic cytoskeleton, whose roles in cell function include structural support, contractile activity to intracellular signalling. We model actin filaments as two chains of one-dimensional binary-state semi-totalistic automaton arrays to describe hypothetical signalling events therein. Each node of the actin automaton takes state `0' (resting) or `1' (excited) and updates its state in discrete time depending on its neighbour's states. We analyse the complete rule space of actin automata using integral characteristics of space-time configurations generated by these rules and compute state transition rules that support travelling and mobile localizations. Approaches towards selection of the localisation supporting rules using the global characteristics are outlined. We find that some properties of actin automata rules may be predicted using Shannon entropy, activity and incoherence of excitation between the polymer chains. We also show that it is possible to infer whether a given rule supports travelling or stationary localizations by looking at ratios of excited neighbours are essential for generations of the localizations. We conclude by applying biomolecular hypotheses to this model and discuss the significance of our findings in context with cell signalling and emergent behaviour in cellular computation.
An Efficient Cell List Implementation for Monte Carlo Simulation on GPUs
Venue: arXiv cs.DC 2014
Year: 2014

Maximizing the performance potential of the modern day GPU architecture requires judicious utilization of available parallel resources. Although dramatic reductions can often be obtained through straightforward mappings, further performance improvements often require algorithmic redesigns to more closely exploit the target architecture. In this paper, we focus on efficient molecular simulations for the GPU and propose a novel cell list algorithm that better utilizes its parallel resources. Our goal is an efficient GPU implementation of large-scale Monte Carlo simulations for the grand canonical ensemble. This is a particularly challenging application because there is inherently less computation and parallelism than in similar applications with molecular dynamics. Consistent with the results of prior researchers, our simulation results show traditional cell list implementations for Monte Carlo simulations of molecular systems offer effectively no performance improvement for small systems [5, 14], even when porting to the GPU. However for larger systems, the cell list implementation offers significant gains in performance. Furthermore, our novel cell list approach results in better performance for all problem sizes when compared with other GPU implementations with or without cell lists.
Bivalent semantics, generalized compositionality and analytic classic-like tableaux for finite-valued logics
Venue: arXiv cs.LO 2014
Year: 2014

The paper is a contribution both to the theoretical foundations and to the actual construction of efficient automatizable proof procedures for non-classical logics. We focus here on the case of finite-valued logics, and exhibit: (i) a mechanism for producing a classic-like description of them in terms of an effective variety of bivalent semantics; (ii) a mechanism for extracting, from the bivalent semantics so obtained, uniform (classically-labeled) cut-free standard analytic tableaux with possibly branching invertible rules and paired with proof strategies designed to guarantee termination of the associated proof procedure; (iii) a mechanism to also provide, for the same logics, uniform cut-based tableau systems with linear rules. The latter tableau systems are shown to be adequate even when restricted to analytic cuts, and they are also shown to polynomially simulate truth-tables, a feature that is not enjoyed by the former standard type of tableau systems (not even in the 2-valued case). The results are based on useful generalizations of the notions of analyticity and compositionality, and illustrate a theory that applies to many other classes of non-classical logics.
Action Classification with Locality-constrained Linear Coding
Venue: arXiv cs.CV 2014
Year: 2014

We propose an action classification algorithm which uses Locality-constrained Linear Coding (LLC) to capture discriminative information of human body variations in each spatiotemporal subsequence of a video sequence. Our proposed method divides the input video into equally spaced overlapping spatiotemporal subsequences, each of which is decomposed into blocks and then cells. We use the Histogram of Oriented Gradient (HOG3D) feature to encode the information in each cell. We justify the use of LLC for encoding the block descriptor by demonstrating its superiority over Sparse Coding (SC). Our sequence descriptor is obtained via a logistic regression classifier with L2 regularization. We evaluate and compare our algorithm with ten state-of-the-art algorithms on five benchmark datasets. Experimental results show that, on average, our algorithm gives better accuracy than these ten algorithms.
Verifiable Member and Order Queries on a List in Zero-Knowledge
Venue: arXiv cs.CR 2014
Year: 2014

We introduce a formal model for order queries on lists in zero knowledge in the traditional authenticated data structure model. We call this model Privacy-Preserving Authenticated List (PPAL). In this model, the queries are performed on the list stored in the (untrusted) cloud where data integrity and privacy have to be maintained. To realize an efficient authenticated data structure, we first adapt consistent data query model. To this end we introduce a formal model called Zero-Knowledge List (ZKL) scheme which generalizes consistent membership queries in zero-knowledge to consistent membership and order queries on a totally ordered set in zero knowledge. We present a construction of ZKL based on zero-knowledge set and homomorphic integer commitment scheme. Then we discuss why this construction is not as efficient as desired in cloud applications and present an efficient construction of PPAL based on bilinear accumulators and bilinear maps which is provably secure and zero-knowledge.
Fairer citation-based metrics
Venue: arXiv cs.DL 2014
Year: 2014

I describe a simple modification which can be applied to any citation count-based index (e.g. Hirsch's h-index) quantifying a researcher's publication output. The key idea behind the proposed approach is that the merit for the citations of a paper should be distributed amongst its authors according to their relative contributions. In addition to producing inherently fairer metrics I show that the proposed modification has the potential to partially normalize for the unfair effects of honorary authorship and thus discourage this practice.
Static Analysis for Extracting Permission Checks of a Large Scale Framework: The Challenges And Solutions for Analyzing Android
Venue: arXiv cs.SE 2014
Year: 2014

A common security architecture is based on the protection of certain resources by permission checks (used e.g., in Android and Blackberry). It has some limitations, for instance, when applications are granted more permissions than they actually need, which facilitates all kinds of malicious usage (e.g., through code injection). The analysis of permission-based framework requires a precise mapping between API methods of the framework and the permissions they require. In this paper, we show that naive static analysis fails miserably when applied with off-the-shelf components on the Android framework. We then present an advanced class-hierarchy and field-sensitive set of analyses to extract this mapping. Those static analyses are capable of analyzing the Android framework. They use novel domain specific optimizations dedicated to Android.
Bird's-eye view on Noise-Based Logic
Venue: arXiv cs.ET 2014
Year: 2014

Noise-based logic is a practically deterministic logic scheme inspired by the randomness of neural spikes and uses a system of uncorrelated stochastic processes and their superposition to represent the logic state. We briefly discuss various questions such as (i) What does practical determinism mean? (ii) Is noise-based logic a Turing machine? (iii) Is there hope to beat (the dreams of) quantum computation by a classical physical noise-based processor, and what are the minimum hardware requirements for that? Finally, (iv) we address the problem of random number generators and show that the common belief that quantum number generators are superior to classical (thermal) noise-based generators is nothing but a myth.
Mahonian STAT on words
Venue: arXiv cs.DM 2014
Year: 2014

In 2000, Babson and Steingrímsson introduced the notion of what is now known as a permutation vincular pattern, and based on it they re-defined known Mahonian statistics and introduced new ones, proving or conjecturing their Mahonity. These conjectures were proved by Foata and Zeilberger in 2001, and by Foata and Randrianarivony in 2006. In 2010, Burstein refined some of these results by giving a bijection between permutations with a fixed value for the major index and those with the same value for STAT, where STAT is one of the statistics defined and proved to be Mahonian in the 2000 Babson and Steingrímsson's paper. Several other statistics are preserved as well by Burstein's bijection. At the Formal Power Series and Algebraic Combinatorics Conference (FPSAC) in 2010, Burstein asked whether his bijection has other interesting properties. In this paper, we not only show that Burstein's bijection preserves the Eulerian statistic ides, but also use this fact, along with the bijection itself, to prove Mahonity of the statistic STAT on words we introduce in this paper. The words statistic STAT introduced by us here addresses a natural question on existence of a Mahonian words analogue of STAT on permutations. While proving Mahonity of our STAT on words, we prove a more general joint equidistribution result involving two six-tuples of statistics on (dense) words, where Burstein's bijection plays an important role.
Energy Efficiency Optimization in Hardware-Constrained Large-Scale MIMO Systems
Venue: arXiv cs.IT 2014
Year: 2014

Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MIMO is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.
On Unconstrained Quasi-Submodular Function Optimization
Venue: arXiv cs.DS 2014
Year: 2014

With the extensive application of submodularity, its generalizations are constantly being proposed. However, most of them are tailored for special problems. In this paper, we focus on quasi-submodularity, a universal generalization, which satisfies weaker properties than submodularity but still enjoys favorable performance in optimization. Similar to the diminishing return property of submodularity, we first define a corresponding property called the {\em single sub-crossing}, then we propose two algorithms for unconstrained quasi-submodular function minimization and maximization, respectively. The proposed algorithms return the reduced lattices in $\mathcal{O}(n)$ iterations, and guarantee the objective function values are strictly monotonically increased or decreased after each iteration. Moreover, any local and global optima are definitely contained in the reduced lattices. Experimental results verify the effectiveness and efficiency of the proposed algorithms on lattice reduction.
Robust width: A characterization of uniformly stable and robust compressed sensing
Venue: arXiv cs.IT 2014
Year: 2014

Compressed sensing seeks to invert an underdetermined linear system by exploiting additional knowledge of the true solution. Over the last decade, several instances of compressed sensing have been studied for various applications, and for each instance, reconstruction guarantees are available provided the sensing operator satisfies certain sufficient conditions. In this paper, we completely characterize the sensing operators which allow uniformly stable and robust reconstruction by convex optimization for many of these instances. The characterized sensing operators satisfy a new property we call the robust width property, which simultaneously captures notions of widths from approximation theory and of restricted eigenvalues from statistical regression. We provide a geometric interpretation of this property, we discuss its relationship with the restricted isometry property, and we apply techniques from geometric functional analysis to find random matrices which satisfy the property with high probability.