OpenRaiser/Intern-Atlas huggingface dataset:
Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games
Venue: arXiv cs.CY 2015
Year: 2015

In this work we explore cyberbullying and other toxic behavior in team competition online games. Using a dataset of over 10 million player reports on 1.46 million toxic players along with corresponding crowdsourced decisions, we test several hypotheses drawn from theories explaining toxic behavior. Besides providing large-scale, empirical based understanding of toxic behavior, our work can be used as a basis for building systems to detect, prevent, and counter-act toxic behavior.
Optimal Detection in Training Assisted SIMO Systems with Phase Noise Impairments
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, the problem of optimal maximum likelihood detection in a single user single-input multiple-output (SIMO) channel with phase noise at the receiver is considered. The optimal detection rules under training are derived for two operation modes, namely when the phase increments are fully correlated among the $M$ receiver antennas (synchronous operation) and when they are independent (non-synchronous operation). The phase noise increments are parameterized by a very general distribution, which includes the Wiener phase noise model as a special case. It is proven that phase noise creates a symbol-error-rate (SER) floor for both operation modes. In the synchronous operation this error floor is independent of $M$, while it goes to zero exponentially with $M$ in the non-synchronous operation.
Designing Installations for Verification of the Model of Active Queue Management Discipline RED in the GNS3
Venue: arXiv cs.NI 2015
Year: 2015

The problem of RED-module mathematical model results verification, based on GNS3 experimental stand, is discussed in this article. The experimental stand consists of virtual Cisco router, traffic generator D-ITG and traffic receiver. The process of construction of such stand is presented. Also, the interaction between experimental stand and a computer of investigation in order to obtain and analyze data from stand is revised. A stochastic model of the traffic management RED type module was built. Verification of the model was carried out on the NS-2 basis. However, we would like to conduct verification on a real router. As a result was the task of designing an experimental stand. It was decided to verify the clean RED algorithm based on Cisco router. For the construction of the stand software package GNS3 (Graphical Network Simulator) was chosen. Thus, the purpose of the study is to build on the GNS3 basis a virtual stand consisting of a Cisco router, a traffic generator and a receiver. A traffic generator D-ITG (Distributed Internet Traffic Generator) is used as.
RDF annotation of Second Life objects: Knowledge Representation meets Social Virtual reality
Venue: arXiv cs.AI 2015
Year: 2015

We have designed and implemented an application running inside Second Life that supports user annotation of graphical objects and graphical visualization of concept ontologies, thus providing a formal, machine-accessible description of objects. As a result, we offer a platform that combines the graphical knowledge representation that is expected from a MUVE artifact with the semantic structure given by the Resource Framework Description (RDF) representation of information.
Real-time Monocular Object SLAM
Venue: arXiv cs.RO 2015
Year: 2015

We present a real-time object-based SLAM system that leverages the largest object database to date. Our approach comprises two main components: 1) a monocular SLAM algorithm that exploits object rigidity constraints to improve the map and find its real scale, and 2) a novel object recognition algorithm based on bags of binary words, which provides live detections with a database of 500 3D objects. The two components work together and benefit each other: the SLAM algorithm accumulates information from the observations of the objects, anchors object features to especial map landmarks and sets constrains on the optimization. At the same time, objects partially or fully located within the map are used as a prior to guide the recognition algorithm, achieving higher recall. We evaluate our proposal on five real environments showing improvements on the accuracy of the map and efficiency with respect to other state-of-the-art techniques.
Observations of service identification from two enterprises
Venue: arXiv cs.SE 2015
Year: 2015

Service-oriented computing has created new requirements for information systems development processes and methods. The adoption of service-oriented development requires service identification methods matching the challenge in enterprises. A wide variety of service identification methods (SIM) have been proposed, but less attention has been paid to the actual requirements of the methods. This paper provides an ethnographical look at challenges in service identification based on data from 14 service identification sessions, providing insight into the practice of service identification. The findings identified two types of service identification sessions and the results can be used for selecting the appropriate SIM based on the type of the session.
Big Data Analytics for Dynamic Energy Management in Smart Grids
Venue: arXiv cs.DB 2015
Year: 2015

The smart electricity grid enables a two-way flow of power and data between suppliers and consumers in order to facilitate the power flow optimization in terms of economic efficiency, reliability and sustainability. This infrastructure permits the consumers and the micro-energy producers to take a more active role in the electricity market and the dynamic energy management (DEM). The most important challenge in a smart grid (SG) is how to take advantage of the users' participation in order to reduce the cost of power. However, effective DEM depends critically on load and renewable production forecasting. This calls for intelligent methods and solutions for the real-time exploitation of the large volumes of data generated by a vast amount of smart meters. Hence, robust data analytics, high performance computing, efficient data network management, and cloud computing techniques are critical towards the optimized operation of SGs. This research aims to highlight the big data issues and challenges faced by the DEM employed in SG networks. It also provides a brief description of the most commonly used data processing methods in the literature, and proposes a promising direction for future research in the field.
Using Model Checking to Generate Test Cases for Android Applications
Venue: arXiv cs.SE 2015
Year: 2015

The behavior of mobile devices is highly non deterministic and barely predictable due to the interaction of the user with its applications. In consequence, analyzing the correctness of applications running on a smartphone involves dealing with the complexity of its environment. In this paper, we propose the use of model-based testing to describe the potential behaviors of users interacting with mobile applications. These behaviors are modeled by composing specially-designed state machines. These composed state machines can be exhaustively explored using a model checking tool to automatically generate all possible user interactions. Each generated trace model checker can be interpreted as a test case to drive a runtime analysis of actual applications. We have implemented a tool that follows the proposed methodology to analyze Android devices using the model checker Spin as the exhaustive generator of test cases.
Ioco Theory for Probabilistic Automata
Venue: arXiv cs.LO 2015
Year: 2015

Model-based testing (MBT) is a well-known technology, which allows for automatic test case generation, execution and evaluation. To test non-functional properties, a number of test MBT frameworks have been developed to test systems with real-time, continuous behaviour, symbolic data and quantitative system aspects. Notably, a lot of these frameworks are based on Tretmans' classical input/output conformance (ioco) framework. However, a model-based test theory handling probabilistic behaviour does not exist yet. Probability plays a role in many different systems: unreliable communication channels, randomized algorithms and communication protocols, service level agreements pinning down up-time percentages, etc. Therefore, a probabilistic test theory is of great practical importance. We present the ingredients for a probabilistic variant of ioco and define the πoco relation, show that it conservatively extends ioco and define the concepts of test case, execution and evaluation.
Leveraging Twitter for Low-Resource Conversational Speech Language Modeling
Venue: arXiv cs.CL 2015
Year: 2015

In applications involving conversational speech, data sparsity is a limiting factor in building a better language model. We propose a simple, language-independent method to quickly harvest large amounts of data from Twitter to supplement a smaller training set that is more closely matched to the domain. The techniques lead to a significant reduction in perplexity on four low-resource languages even though the presence on Twitter of these languages is relatively small. We also find that the Twitter text is more useful for learning word classes than the in-domain text and that use of these word classes leads to further reductions in perplexity. Additionally, we introduce a method of using social and textual information to prioritize the download queue during the Twitter crawling. This maximizes the amount of useful data that can be collected, impacting both perplexity and vocabulary coverage.
Highly-cited papers in Library and Information Science (LIS): Authors, institutions, and network structures
Venue: arXiv cs.DL 2015
Year: 2015

As a follow-up to the highly-cited authors list published by Thomson Reuters in June 2014, we analyze the top-1% most frequently cited papers published between 2002 and 2012 included in the Web of Science (WoS) subject category "Information Science & Library Science." 798 authors contributed to 305 top-1% publications; these authors were employed at 275 institutions. The authors at Harvard University contributed the largest number of papers, when the addresses are whole-number counted. However, Leiden University leads the ranking, if fractional counting is used. Twenty-three of the 798 authors were also listed as most highly-cited authors by Thomson Reuters in June 2014 (http://highlycited.com/). Twelve of these 23 authors were involved in publishing four or more of the 305 papers under study. Analysis of co-authorship relations among the 798 highly-cited scientists shows that co-authorships are based on common interests in a specific topic. Three topics were important between 2002 and 2012: (1) collection and exploitation of information in clinical practices, (2) the use of internet in public communication and commerce, and (3) scientometrics.
Time-causal and time-recursive spatio-temporal receptive fields
Venue: arXiv cs.CV 2015
Year: 2015

We present an improved model and theory for time-causal and time-recursive spatio-temporal receptive fields, based on a combination of Gaussian receptive fields over the spatial domain and first-order integrators or equivalently truncated exponential filters coupled in cascade over the temporal domain. Compared to previous spatio-temporal scale-space formulations in terms of non-enhancement of local extrema or scale invariance, these receptive fields are based on different scale-space axiomatics over time by ensuring non-creation of new local extrema or zero-crossings with increasing temporal scale. Specifically, extensions are presented about (i) parameterizing the intermediate temporal scale levels, (ii) analysing the resulting temporal dynamics, (iii) transferring the theory to a discrete implementation, (iv) computing scale-normalized spatio-temporal derivative expressions for spatio-temporal feature detection and (v) computational modelling of receptive fields in the lateral geniculate nucleus (LGN) and the primary visual cortex (V1) in biological vision. We show that by distributing the intermediate temporal scale levels according to a logarithmic distribution, we obtain much faster temporal response properties (shorter temporal delays) compared to a uniform distribution. Specifically, these kernels converge very rapidly to a limit kernel possessing true self-similar scale-invariant properties over temporal scales, thereby allowing for true scale invariance over variations in the temporal scale, although the underlying temporal scale-space representation is based on a discretized temporal scale parameter. We show how scale-normalized temporal derivatives can be defined for these time-causal scale-space kernels and how the composed theory can be used for computing basic types of scale-normalized spatio-temporal derivative expressions in a computationally efficient manner.
Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping
Venue: arXiv cs.RO 2015
Year: 2015

Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes can represent a continuous-time trajectory, elegantly handle asynchronous and sparse measurements, and allow the robot to query the trajectory to recover its estimated position at any time of interest. A major drawback of this approach is that STEAM is formulated as a batch estimation problem. In this paper we provide the critical extensions necessary to transform the existing batch algorithm into an extremely efficient incremental algorithm. In particular, we are able to vastly speed up the solution time through efficient variable reordering and incremental sparse updates, which we believe will greatly increase the practicality of Gaussian process methods for robot mapping and localization. Finally, we demonstrate the approach and its advantages on both synthetic and real datasets.
Equational reasoning with context-free families of string diagrams
Venue: arXiv cs.LO 2015
Year: 2015

String diagrams provide an intuitive language for expressing networks of interacting processes graphically. A discrete representation of string diagrams, called string graphs, allows for mechanised equational reasoning by double-pushout rewriting. However, one often wishes to express not just single equations, but entire families of equations between diagrams of arbitrary size. To do this we define a class of context-free grammars, called B-ESG grammars, that are suitable for defining entire families of string graphs, and crucially, of string graph rewrite rules. We show that the language-membership and match-enumeration problems are decidable for these grammars, and hence that there is an algorithm for rewriting string graphs according to B-ESG rewrite patterns. We also show that it is possible to reason at the level of grammars by providing a simple method for transforming a grammar by string graph rewriting, and showing admissibility of the induced B-ESG rewrite pattern.
Real-time Tool for Affine Transformations of Two Dimensional IFS Fractals
Venue: arXiv cs.GR 2015
Year: 2015

This work introduces a novel tool for interactive, real-time transformations of two dimensional IFS fractals. We assign barycentric coordinates (relative to an arbitrary affine basis of $\mathbb{R}^2$) to the points that constitute the image of a fractal. The tool uses some of the nice properties of the barycentric coordinates, enabling any affine transformation of the basis, done by click-and-drag, to be immediately followed by the same affine transformation of the IFS fractal attractor. In order to have a better control over the fractal, as affine basis we use a kind of minimal simplex that contains the attractor. We give theoretical grounds of the tool and then the software application.
Sharpening Skills in Using Presentation Tools: Students' Experiences
Venue: arXiv cs.CY 2015
Year: 2015

Making use of Information and Communication Technology resources is deemed necessary for students. With this, they need to demonstrate their competence in using various technologies such as Prezi and PowerPoint to communicate effectively and efficiently. Hence, their experiences in using these presentation tools is important to assist them in their needs. In this study, all the fourth year Bachelor of Science in Technology Communication Management students who have used the PowerPoint and Prezi were the respondents. Survey instruments were given to determine the experiences of students of these technologies based on their familiarity, skills, and effectiveness in delivering the reports and presentations. It was found out that students were generally good in using these tools. On the other hand, following the basic rules to use these presentation tools effectively has to be reinforced in the classroom to enhance and enrich their learning in sharpening their skills on presentation tools.
Model Counting Modulo Theories
Venue: arXiv cs.CR 2015
Year: 2015

This thesis is concerned with the quantitative assessment of security in software. More specifically, it tackles the problem of efficient computation of channel capacity, the maximum amount of confidential information leaked by software, measured in Shannon entropy or Rényi's min-entropy. Most approaches to computing channel capacity are either efficient and return only (possibly very loose) upper bounds, or alternatively are inefficient but precise; few target realistic programs. In this thesis, we present a novel approach to the problem by reducing it to a model counting problem on first-order logic, which we name Model Counting Modulo Theories or #SMT for brevity. For quantitative security, our contribution is twofold. First, on the theoretical side we establish the connections between measuring confidentiality leaks and fundamental verification algorithms like Symbolic Execution, SMT solvers and DPLL. Second, exploiting these connections, we develop novel #SMT-based techniques to compute channel capacity, which achieve both accuracy and efficiency. These techniques are scalable to real-world programs, and illustrative case studies include C programs from Linux kernel, a Java program from a European project and anonymity protocols. For formal verification, our contribution is also twofold. First, we introduce and study a new research problem, namely #SMT, which has other potential applications beyond computing channel capacity, such as returning multiple-counterexamples for Bounded Model Checking or automated test generation. Second, we propose an alternative approach for Bounded Model Checking using classical Symbolic Execution, which can be parallelised to leverage modern multi-core and distributed architecture.
Towards A Theory Of Quantum Computability
Venue: arXiv cs.LO 2015
Year: 2015

We propose a definition of quantum computable functions as mappings between superpositions of natural numbers to probability distributions of natural numbers. Each function is obtained as a limit of an infinite computation of a quantum Turing machine. The class of quantum computable functions is recursively enumerable, thus opening the door to a quantum computability theory which may follow some of the classical developments.
Regularized system identification using orthonormal basis functions
Venue: arXiv cs.SY 2015
Year: 2015

Most of existing results on regularized system identification focus on regularized impulse response estimation. Since the impulse response model is a special case of orthonormal basis functions, it is interesting to consider if it is possible to tackle the regularized system identification using more compact orthonormal basis functions. In this paper, we explore two possibilities. First, we construct reproducing kernel Hilbert space of impulse responses by orthonormal basis functions and then use the induced reproducing kernel for the regularized impulse response estimation. Second, we extend the regularization method from impulse response estimation to the more general orthonormal basis functions estimation. For both cases, the poles of the basis functions are treated as hyperparameters and estimated by empirical Bayes method. Then we further show that the former is a special case of the latter, and more specifically, the former is equivalent to ridge regression of the coefficients of the orthonormal basis functions.
The Hardness of Subgraph Isomorphism
Venue: arXiv cs.DS 2015
Year: 2015

Subgraph Isomorphism is a very basic graph problem, where given two graphs $G$ and $H$ one is to check whether $G$ is a subgraph of $H$. Despite its simple definition, the Subgraph Isomorphism problem turns out to be very broad, as it generalizes problems such as Clique, $r$-Coloring, Hamiltonicity, Set Packing and Bandwidth. However, for all of the mentioned problems $2^{\mathcal{O}(n)}$ time algorithms exist, so a natural and frequently asked question in the past was whether there exists a $2^{\mathcal{O}(n)}$ time algorithm for Subgraph Isomorphism. In the monograph of Fomin and Kratsch [Springer'10] this question is highlighted as an open problem, among few others. Our main result is a reduction from 3-SAT, producing a subexponential number of sublinear instances of the Subgraph Isomorphism problem. In particular, our reduction implies a $2^{Ω(n \sqrt{\log n})}$ lower bound for Subgraph Isomorphism under the Exponential Time Hypothesis. This shows that there exist classes of graphs that are strictly harder to embed than cliques or Hamiltonian cycles. The core of our reduction consists of two steps. First, we preprocess and pack variables and clauses of a 3-SAT formula into groups of logarithmic size. However, the grouping is not arbitrary, since as a result we obtain only a limited interaction between the groups. In the second step, we overcome the technical hardness of encoding evaluations as permutations by a simple, yet fruitful scheme of guessing the sizes of preimages of an arbitrary mapping, reducing the case of arbitrary mapping to bijections. In fact, when applying this step to a recent independent result of Fomin et al.[arXiv:1502.05447 (2015)], who showed hardness of Graph Homomorphism, we can transfer their hardness result to Subgraph Isomorphism, implying a nearly tight lower bound of $2^{Ω(n \log n / \log \log n)}$.
Cellular Automata are Generic
Venue: arXiv cs.LO 2015
Year: 2015

Any algorithm (in the sense of Gurevich's abstract-state-machine axiomatization of classical algorithms) operating over any arbitrary unordered domain can be simulated by a dynamic cellular automaton, that is, by a pattern-directed cellular automaton with unconstrained topology and with the power to create new cells. The advantage is that the latter is closer to physical reality. The overhead of our simulation is quadratic.
Global Value Numbering: A Precise and Efficient Algorithm
Venue: arXiv cs.PL 2015
Year: 2015

Global Value Numbering (GVN) is an important static analysis to detect equivalent expressions in a program. We present an iterative data-flow analysis GVN algorithm in SSA for the purpose of detecting total redundancies. The central challenge is defining a join operation to detect equivalences at a join point in polynomial time such that later occurrences of redundant expressions could be detected. For this purpose, we introduce the novel concept of value $ϕ$-function. We claim the algorithm is precise and takes only polynomial time.