OpenRaiser/Intern-Atlas huggingface dataset:
Convergence between Categorical Representations of Reeb Space and Mapper
Venue: arXiv cs.CG 2016
Year: 2016

The Reeb space, which generalizes the notion of a Reeb graph, is one of the few tools in topological data analysis and visualization suitable for the study of multivariate scientific datasets. First introduced by Edelsbrunner et al., it compresses the components of the level sets of a multivariate mapping and obtains a summary representation of their relationships. A related construction called mapper, and a special case of the mapper construction called the Joint Contour Net have been shown to be effective in visual analytics. Mapper and JCN are intuitively regarded as discrete approximations of the Reeb space, however without formal proofs or approximation guarantees. An open question has been proposed by Dey et al. as to whether the mapper construction converges to the Reeb space in the limit. In this paper, we are interested in developing the theoretical understanding of the relationship between the Reeb space and its discrete approximations to support its use in practical data analysis. Using tools from category theory, we formally prove the convergence between the Reeb space and mapper in terms of an interleaving distance between their categorical representations. Given a sequence of refined discretizations, we prove that these approximations converge to the Reeb space in the interleaving distance; this also helps to quantify the approximation quality of the discretization at a fixed resolution.
Telepresence Interaction by Touching Live Video Images
Venue: arXiv cs.HC 2016
Year: 2016

This paper presents a telepresence interaction framework based on touchscreen and telepresence-robot technologies. The core of the framework is a new user interface, Touchable live video Image based User Interface, called TIUI. The TIUI allows a remote operator to not just drive the telepresence robot but operate and interact with real objects by touching their live video images on a pad with finger touch gestures. We implemented a telepresence interaction system which is composed of a telepresence robot and tele-interactive objects located in a local space, the TIUI of a pad located in a remote space, and the wireless networks connecting the two spaces. Our system can be a perfect embodiment of a remote operator to do most of daily living tasks, such as opening a door, drawing a curtain, pushing a wheelchair, and other like tasks. The evaluation and demonstration results show the effectiveness and promising applications of our system.
Data-driven Sequential Monte Carlo in Probabilistic Programming
Venue: arXiv cs.AI 2016
Year: 2016

Most of Markov Chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) algorithms in existing probabilistic programming systems suboptimally use only model priors as proposal distributions. In this work, we describe an approach for training a discriminative model, namely a neural network, in order to approximate the optimal proposal by using posterior estimates from previous runs of inference. We show an example that incorporates a data-driven proposal for use in a non-parametric model in the Anglican probabilistic programming system. Our results show that data-driven proposals can significantly improve inference performance so that considerably fewer particles are necessary to perform a good posterior estimation.
Assessing Levels of Attention using Low Cost Eye Tracking
Venue: arXiv cs.HC 2016
Year: 2016

The emergence of mobile eye trackers embedded in next generation smartphones or VR displays will make it possible to trace not only what objects we look at but also the level of attention in a given situation. Exploring whether we can quantify the engagement of a user interacting with a laptop, we apply mobile eye tracking in an in-depth study over 2 weeks with nearly 10.000 observations to assess pupil size changes, related to attentional aspects of alertness, orientation and conflict resolution. Visually presenting conflicting cues and targets we hypothesize that it's feasible to measure the allocated effort when responding to confusing stimuli. Although such experiments are normally carried out in a lab, we are able to differentiate between sustained alertness and complex decision making even with low cost eye tracking "in the wild". From a quantified self perspective of individual behavioral adaptation, the correlations between the pupil size and the task dependent reaction time and error rates may longer term provide a foundation for modifying smartphone content and interaction to the users perceived level of attention.
Probabilistic Programming with Gaussian Process Memoization
Venue: arXiv cs.LG 2016
Year: 2016

Gaussian Processes (GPs) are widely used tools in statistics, machine learning, robotics, computer vision, and scientific computation. However, despite their popularity, they can be difficult to apply; all but the simplest classification or regression applications require specification and inference over complex covariance functions that do not admit simple analytical posteriors. This paper shows how to embed Gaussian processes in any higher-order probabilistic programming language, using an idiom based on memoization, and demonstrates its utility by implementing and extending classic and state-of-the-art GP applications. The interface to Gaussian processes, called gpmem, takes an arbitrary real-valued computational process as input and returns a statistical emulator that automatically improve as the original process is invoked and its input-output behavior is recorded. The flexibility of gpmem is illustrated via three applications: (i) robust GP regression with hierarchical hyper-parameter learning, (ii) discovering symbolic expressions from time-series data by fully Bayesian structure learning over kernels generated by a stochastic grammar, and (iii) a bandit formulation of Bayesian optimization with automatic inference and action selection. All applications share a single 50-line Python library and require fewer than 20 lines of probabilistic code each.
Lattices from codes over $\mathbb{Z}_q$: Generalization of Constructions $D$, $D'$ and $\overline{D}$
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we extend the lattice Constructions $D$, $D'$ and $\overline{D}$ $($this latter is also known as Forney's code formula$)$ from codes over $\mathbb{F}_p$ to linear codes over $\mathbb{Z}_q$, where $q \in \mathbb{N}$. We define an operation in $\mathbb{Z}_q^n$ called zero-one addition, which coincides with the Schur product when restricted to $\mathbb{Z}_2^n$ and show that the extended Construction $\overline{D}$ produces a lattice if and only if the nested codes are closed under this addition. A generalization to the real case of the recently developed Construction $A'$ is also derived and we show that this construction produces a lattice if and only if the corresponding code over $\mathbb{Z}_q[X]/X^a$ is closed under a shifted zero-one addition. One of the motivations for this work is the recent use of $q$-ary lattices in cryptography.
Multiclass Classification of Cervical Cancer Tissues by Hidden Markov Model
Venue: arXiv cs.CV 2016
Year: 2016

In this paper, we report a hidden Markov model based multiclass classification of cervical cancer tissues. This model has been validated directly over time series generated by the medium refractive index fluctuations extracted from differential interference contrast images of healthy and different stages of cancer tissues. The method shows promising results for multiclass classification with higher accuracy.
Self-triggered Pursuit of a Single Evader with Uncertain Information
Venue: arXiv cs.SY 2016
Year: 2016

This paper studies a pursuit-evasion problem involving a single pursuer and a single evader, where we are interested in developing a pursuit strategy that doesn't require continuous, or even periodic, information about the position of the evader. We propose a self-triggered control strategy that allows the pursuer to sample the evader's position autonomously, while satisfying desired performance metric of evader capture. The work in this paper builds on the previously proposed self-triggered pursuit strategy which guarantees capture of the evader in finite time with a finite number of evader samples. However, this algorithm relied on the unrealistic assumption that the evader's exact position was available to the pursuer. Instead, we extend our previous framework to develop an algorithm which allows for uncertainties in sampling the information about the evader, and derive tolerable upper-bounds on the error such that the pursuer can guarantee capture of the evader. In addition, we outline the advantages of retaining the evader's history in improving the current estimate of the true location of the evader that can be used to capture the evader with even less samples. Our approach is in sharp contrast to the existing works in literature and our results ensure capture without sacrificing any performance in terms of guaranteed time-to-capture, as compared to classic algorithms that assume continuous availability of information.
Multistage SFM: A Coarse-to-Fine Approach for 3D Reconstruction
Venue: arXiv cs.CV 2016
Year: 2016

Several methods have been proposed for large-scale 3D reconstruction from large, unorganized image collections. A large reconstruction problem is typically divided into multiple components which are reconstructed independently using structure from motion (SFM) and later merged together. Incremental SFM methods are most popular for the basic structure recovery of a single component. They are robust and effective but are strictly sequential in nature. We present a multistage approach for SFM reconstruction of a single component that breaks the sequential nature of the incremental SFM methods. Our approach begins with quickly building a coarse 3D model using only a fraction of features from given images. The coarse model is then enriched by localizing remaining images and matching and triangulating remaining features in subsequent stages. These stages are made efficient and highly parallel by leveraging the geometry of the coarse model. Our method produces similar quality models as compared to incremental SFM methods while being notably fast and parallel.
Security Constraints in Temporal Role-Based Access-Controlled Workflows (Extended Version)
Venue: arXiv cs.CR 2016
Year: 2016

Workflows and role-based access control models need to be suitably merged, in order to allow users to perform processes in a correct way, according to the given data access policies and the temporal constraints. Given a mapping between workflow models and simple temporal networks with uncertainty, we discuss a mapping between role temporalities and simple temporal networks, and how to connect the two resulting networks to make explicit who can do what, when. If the connected network is still executable, we show how to compute the set of authorized users for each task. Finally, we define security constraints (to prevent users from doing unauthorized actions) and security constraint propagation rules (to propagate security constraints at runtime). We also provide an algorithm to check whether a set of propagation rules is safe, and we extend an existing execution algorithm to take into account these new security aspects.
On the Way to Future's High Energy Particle Physics Transport Code
Venue: arXiv cs.DC 2016
Year: 2016

High Energy Physics (HEP) needs a huge amount of computing resources. In addition data acquisition, transfer, and analysis require a well developed infrastructure too. In order to prove new physics disciplines it is required to higher the luminosity of the accelerator facilities, which produce more-and-more data in the experimental detectors. Both testing new theories and detector R&D are based on complex simulations. Today have already reach that level, the Monte Carlo detector simulation takes much more time than real data collection. This is why speed up of the calculations and simulations became important in the HEP community. The Geant Vector Prototype (GeantV) project aims to optimize the most-used particle transport code applying parallel computing and to exploit the capabilities of the modern CPU and GPU architectures as well. With the maximized concurrency at multiple levels the GeantV is intended to be the successor of the Geant4 particle transport code that has been used since two decades successfully. Here we present our latest result on the GeantV tests performances, comparing CPU/GPU based vectorized GeantV geometrical code to the Geant4 version.
Synchronization of Multi-Agent Systems With Heterogeneous Controllers
Venue: arXiv cs.SY 2016
Year: 2016

This paper studies the synchronization of a multi-agent system where the agents are coupled through heterogeneous controller gains. Synchronization refers to the situation where all the agents in a group have a common velocity direction. We generalize existing results and show that by using heterogeneous controller gains, the final velocity direction at which the system of agents synchronize can be controlled. The effect of heterogeneous gains on the reachable set of this final velocity direction is further analyzed. We also show that for realistic systems, a limited control force to stabilize the agents to the synchronized condition can be achieved by confining these heterogeneous controller gains to an upper bound. Simulations are given to support the theoretical findings.
Mixed-Criticality Scheduling with I/O
Venue: arXiv cs.OS 2016
Year: 2016

This paper addresses the problem of scheduling tasks with different criticality levels in the presence of I/O requests. In mixed-criticality scheduling, higher criticality tasks are given precedence over those of lower criticality when it is impossible to guarantee the schedulability of all tasks. While mixed-criticality scheduling has gained attention in recent years, most approaches typically assume a periodic task model. This assumption does not always hold in practice, especially for real-time and embedded systems that perform I/O. For example, many tasks block on I/O requests until devices signal their completion via interrupts; both the arrival of interrupts and the waking of blocked tasks can be aperiodic. In our prior work, we developed a scheduling technique in the Quest real-time operating system, which integrates the time-budgeted management of I/O operations with Sporadic Server scheduling of tasks. This paper extends our previous scheduling approach with support for mixed-criticality tasks and I/O requests on the same processing core. Results show the effective schedulability of different task sets in the presence of I/O requests is superior in our approach compared to traditional methods that manage I/O using techniques such as Sporadic Servers.
Mining Parametric Temporal Logic Properties in Model Based Design for Cyber-Physical Systems
Venue: arXiv cs.LO 2016
Year: 2016

One of the advantages of adopting a Model Based Development (MBD) process is that it enables testing and verification at early stages of development. However, it is often desirable to not only verify/falsify certain formal system specifications, but also to automatically explore the properties that the system satisfies. In this work, we present a framework that enables property exploration for Cyber-Physical Systems. Namely, given a parametric specification with multiple parameters, our solution can automatically infer the ranges of parameters for which the property does not hold on the system. In this paper, we consider parametric specifications in Metric or Signal Temporal Logic (MTL or STL). Using robust semantics for MTL, the parameter mining problem can be converted into a Pareto optimization problem for which we can provide an approximate solution by utilizing stochastic optimization methods. We include algorithms for the exploration and visualization of multi-parametric specifications. The framework is demonstrated on an industrial size, high-fidelity engine model as well as examples from related literature.
Toward a 6/5 Bound for the Minimum Cost 2-Edge Connected Spanning Subgraph Problem
Venue: arXiv cs.DM 2016
Year: 2016

Given a complete graph $K_{n}=(V, E)$ with non-negative edge costs $c\in {\mathbb R}^{E}$, the problem $2EC$ is that of finding a 2-edge connected spanning multi-subgraph of $K_{n}$ of minimum cost. The integrality gap $α\text{2EC}$ of the linear programming relaxation $\text{2EC}^{\text{LP}}$ for $2EC$ has been conjectured to be $\frac{6}{5}$, although currently we only know that $\frac{6}{5}\leqα\text{2EC}\leq\frac{3}{2}$. In this paper, we explore the idea of using the structure of solutions for $\text{2EC}^{\text{LP}}$ and the concept of convex combination to obtain improved bounds for $α\text{2EC}$. We focus our efforts on a family $J$ of half-integer solutions that appear to give the largest integrality gap for $\text{2EC}^{\text{LP}}$. We successfully show that the conjecture $α\text{2EC} = \frac{6}{5}$ is true for any cost functions optimized by some $x^{*}\in J$.
Reduction of Nondeterministic Tree Automata
Venue: arXiv cs.FL 2016
Year: 2016

We present an efficient algorithm to reduce the size of nondeterministic tree automata, while retaining their language. It is based on new transition pruning techniques, and quotienting of the state space w.r.t. suitable equivalences. It uses criteria based on combinations of downward and upward simulation preorder on trees, and the more general downward and upward language inclusions. Since tree-language inclusion is EXPTIME-complete, we describe methods to compute good approximations in polynomial time. We implemented our algorithm as a module of the well-known libvata tree automata library, and tested its performance on a given collection of tree automata from various applications of libvata in regular model checking and shape analysis, as well as on various classes of randomly generated tree automata. Our algorithm yields substantially smaller and sparser automata than all previously known reduction techniques, and it is still fast enough to handle large instances.
A Notation for Markov Decision Processes
Venue: arXiv cs.AI 2016
Year: 2016

This paper specifies a notation for Markov decision processes.
Deterministic and Ensemble-Based Spatially-Coupled Product Codes
Venue: arXiv cs.IT 2016
Year: 2016

Several authors have proposed spatially-coupled (or convolutional-like) variants of product codes (PCs). In this paper, we focus on a parametrized family of generalized PCs that recovers some of these codes (e.g., staircase and block-wise braided codes) as special cases and study the iterative decoding performance over the binary erasure channel. Even though our code construction is deterministic (and not based on a randomized ensemble), we show that it is still possible to rigorously derive the density evolution (DE) equations that govern the asymptotic performance. The obtained DE equations are then compared to those for a related spatially-coupled PC ensemble. In particular, we show that there exists a family of (deterministic) braided codes that follows the same DE equation as the ensemble, for any spatial length and coupling width.
On the calculation of the minimax-converse of the channel coding problem
Venue: arXiv cs.IT 2016
Year: 2016

A minimax-converse has been suggested for the general channel coding problem by Polyanskiy etal. This converse comes in two flavors. The first flavor is generally used for the analysis of the coding problem with non-vanishing error probability and provides an upper bound on the rate given the error probability. The second flavor fixes the rate and provides a lower bound on the error probability. Both converses are given as a min-max optimization problem of an appropriate binary hypothesis testing problem. The properties of the first converse were studies by Polyanskiy and a saddle point was proved. In this paper we study the properties of the second form and prove that it also admits a saddle point. Moreover, an algorithm for the computation of the saddle point, and hence the bound, is developed. In the DMC case, the algorithm runs in a polynomial time.
Geometric Memory Management
Venue: arXiv cs.DS 2016
Year: 2016

In this report we discuss the concepts of geometric memory align- ment, geometric memory allocation and geometric memory mapping. We introduce block trees as an efficient data structure for representing geo- metrically aligned block allocation states. We introduce niche maps as an efficient means to find the right place to allocate a chunk of a given size whilst maintaining good packing and avoiding fragmentation. We intro- duce ledging as a process to deal with chunk sizes that are not a power of two. We discuss using block trees for memory mapping in the context of virtual memory management. We show how ledging can also be applied at the level of virtual memory in order to create fixed size virtual mem- ory spaces. Finally we discuss implementation of both geometric memory allocation as well as geometric memory mapping in hardware.
Overview of Full-Dimension MIMO in LTE-Advanced Pro
Venue: arXiv cs.IT 2016
Year: 2016

Multiple-input multiple-output (MIMO) systems with a large number of basestation antennas, often called massive MIMO, have received much attention in academia and industry as a means to improve the spectral efficiency, energy efficiency, and processing complexity of next generation cellular system. Mobile communication industry has initiated a feasibility study of massive MIMO systems to meet the increasing demand of future wireless systems. Field trials of the proof-of-concept systems have demonstrated the potential gain of the Full-Dimension MIMO (FD-MIMO), an official name for the MIMO enhancement in 3rd generation partnership project (3GPP). 3GPP initiated standardization activity for the seamless integration of this technology into current 4G LTE systems. In this article, we provide an overview of the FD-MIMO system, with emphasis on the discussion and debate conducted on the standardization process of Release 13. We present key features for FD-MIMO systems, a summary of the major issues for the standardization and practical system design, and performance evaluations for typical FD-MIMO scenarios.
Sentiment/Subjectivity Analysis Survey for Languages other than English
Venue: arXiv cs.CL 2016
Year: 2016

Subjective and sentiment analysis have gained considerable attention recently. Most of the resources and systems built so far are done for English. The need for designing systems for other languages is increasing. This paper surveys different ways used for building systems for subjective and sentiment analysis for languages other than English. There are three different types of systems used for building these systems. The first (and the best) one is the language specific systems. The second type of systems involves reusing or transferring sentiment resources from English to the target language. The third type of methods is based on using language independent methods. The paper presents a separate section devoted to Arabic sentiment analysis.
Improving Performance of IEEE 802.11 by a Dynamic Control Backoff Algorithm Under Unsaturated Traffic Loads
Venue: arXiv cs.NI 2016
Year: 2016

The IEEE 802.11 backoff algorithm is very important for controlling system throughput over contentionbased wireless networks. For this reason, there are many studies on wireless network performance focus on developing backoff algorithms. However, most existing models are based on saturated traffic loads, which are not a real representation of actual network conditions. In this paper, a dynamic control backoff time algorithm is proposed to enhance both delay and throughput performance of the IEEE 802.11 distributed coordination function. This algorithm considers the distinction between high and low traffic loads in order to deal with unsaturated traffic load conditions. In particular, the equilibrium point analysis model is used to represent the algorithm under various traffic load conditions. Results of extensive simulation experiments illustrate that the proposed algorithm yields better performance throughput and a better average transmission packet delay than related algorithms.