OpenRaiser/Intern-Atlas huggingface dataset:
Semi-autonomous Intersection Collision Avoidance through Job-shop Scheduling
Venue: arXiv cs.SY 2015
Year: 2015

In this paper, we design a supervisor to prevent vehicle collisions at intersections. An intersection is modeled as an area containing multiple conflict points where vehicle paths cross in the future. At every time step, the supervisor determines whether there will be more than one vehicle in the vicinity of a conflict point at the same time. If there is, then an impending collision is detected, and the supervisor overrides the drivers to avoid collision. A major challenge in the design of a supervisor as opposed to an autonomous vehicle controller is to verify whether future collisions will occur based on the current drivers choices. This verification problem is particularly hard due to the large number of vehicles often involved in intersection collision, to the multitude of conflict points, and to the vehicles dynamics. In order to solve the verification problem, we translate the problem to a job-shop scheduling problem that yields equivalent answers. The job-shop scheduling problem can, in turn, be transformed into a mixed-integer linear program when the vehicle dynamics are first-order dynamics, and can thus be solved by using a commercial solver.
Mining Financial Statement Fraud: An Analysis of Some Experimental Issues
Venue: arXiv cs.CR 2015
Year: 2015

Financial statement fraud detection is an important problem with a number of design aspects to consider. Issues such as (i) problem representation, (ii) feature selection, and (iii) choice of performance metrics all influence the perceived performance of detection algorithms. Efficient implementation of financial fraud detection methods relies on a clear understanding of these issues. In this paper we present an analysis of the three key experimental issues associated with financial statement fraud detection, critiquing the prevailing ideas and providing new understandings.
Formalizing and Checking Thread Refinement for Data-Race-Free Execution Models (Extended Version)
Venue: arXiv cs.PL 2015
Year: 2015

When optimizing a thread in a concurrent program (either done manually or by the compiler), it must be guaranteed that the resulting thread is a refinement of the original thread. Most theories of valid optimizations are formulated in terms of valid syntactic transformations on the program code, or in terms of valid transformations on thread execution traces. We present a new theory formulated instead in terms of the state of threads at synchronization operations, and show that it provides several advantages: it supports more optimizations, and leads to more efficient and simpler procedures for refinement checking. We develop the theory for the SC-for-DRF execution model (using locks for synchronization), and show that its application in a compiler testing setting leads to large performance improvements.
Comparative Document Analysis for Large Text Corpora
Venue: arXiv cs.IR 2015
Year: 2015

This paper presents a novel research problem on joint discovery of commonalities and differences between two individual documents (or document sets), called Comparative Document Analysis (CDA). Given any pair of documents from a document collection, CDA aims to automatically identify sets of quality phrases to summarize the commonalities of both documents and highlight the distinctions of each with respect to the other informatively and concisely. Our solution uses a general graph-based framework to derive novel measures on phrase semantic commonality and pairwise distinction}, and guides the selection of sets of phrases by solving two joint optimization problems. We develop an iterative algorithm to integrate the maximization of phrase commonality or distinction measure with the learning of phrase-document semantic relevance in a mutually enhancing way. Experiments on text corpora from two different domains---scientific publications and news---demonstrate the effectiveness and robustness of the proposed method on comparing individual documents. Our case study on comparing news articles published at different dates shows the power of the proposed method on comparing document sets.
Seam Puckering Objective Evaluation Method for Sewing Process
Venue: arXiv cs.CV 2015
Year: 2015

The paper presents an automated method for the assessment and classification of puckering defects detected during the preproduction control stage of the sewing machine or product inspection. In this respect, we have presented the possible causes and remedies of the wrinkle nonconformities. Subjective factors related to the control environment and operators during the seams evaluation can be reduced using an automated system whose operation is based on image processing. Our implementation involves spectral image analysis using Fourier transform and an unsupervised neural network, the Kohonen Map, employed to classify material specimens, the input images, into five discrete degrees of quality, from grade 5 (best) to grade 1 (the worst).
Filter Bank Common Spatial Patterns in Mental Workload Estimation
Venue: arXiv cs.HC 2015
Year: 2015

EEG-based workload estimation technology provides a real time means of assessing mental workload. Such technology can effectively enhance the performance of the human-machine interaction and the learning process. When designing workload estimation algorithms, a crucial signal processing component is the feature extraction step. Despite several studies on this field, the spatial properties of the EEG signals were mostly neglected. Since EEG inherently has a poor spacial resolution, features extracted individually from each EEG channel may not be sufficiently efficient. This problem becomes more pronounced when we use low-cost but convenient EEG sensors with limited stability which is the case in practical scenarios. To address this issue, in this paper, we introduce a filter bank common spatial patterns algorithm combined with a feature selection method to extract spatio-spectral features discriminating different mental workload levels. To evaluate the proposed algorithm, we carry out a comparative analysis between two representative types of working memory tasks using data recorded from an Emotiv EPOC headset which is a mobile low-cost EEG recording device. The experimental results showed that the proposed spatial filtering algorithm outperformed the state-of-the algorithms in terms of the classification accuracy.
Forkable Regular Expressions
Venue: arXiv cs.FL 2015
Year: 2015

We consider forkable regular expressions, which enrich regular expressions with a fork operator, to establish a formal basis for static and dynamic analysis of the communication behavior of concurrent programs. We define a novel compositional semantics for forkable expressions, establish their fundamental properties, and define derivatives for them as a basis for the generation of automata, for matching, and for language containment tests. Forkable expressions may give rise to non-regular languages, in general, but we identify sufficient conditions on expressions that guarantee finiteness of the automata construction via derivatives.
Stable Matching with Incomplete Information in Structured Networks
Venue: arXiv cs.GT 2015
Year: 2015

In this paper, we investigate stable matching in structured networks. Consider case of matching in social networks where candidates are not fully connected. A candidate on one side of the market gets acquaintance with which one on the heterogeneous side depends on the structured network. We explore four well-used structures of networks and define the social circle by the distance between each candidate. When matching within social circle, we have equilibrium distinguishes from each other since each social network's topology differs. Equilibrium changes with the change on topology of each network and it always converges to the same stable outcome as complete information algorithm if there is no block to reach anyone in agent's social circle.
Results on the solutions of maximum weighted Renyi entropy problems
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, following standard arguments, the maximum Renyi entropy problem for the weighted case is analyzed. We verify that under some constrains on weight function, the Student-r and Student-t distributions maximize the weighted Renyi entropy. Furthermore, an extended version of the Hadamard inequality is derived.
Binary Rate Distortion With Side Information: The Asymmetric Correlation Channel Case
Venue: arXiv cs.IT 2015
Year: 2015

Advancing over up-to-date information theoretic results that assume symmetric correlation models, in this work we consider the problem of lossy binary source coding with side information, where the correlation is expressed by a generic binary asymmetric channel. Specifically, we present an in-depth analysis of rate distortion with side information available to both the encoder and decoder (conventional predictive), as well as the Wyner-Ziv problem for this particular setup. Prompted by our recent results for the Z-channel correlation case, we evaluate the rate loss between the Wyner-Ziv and the conventional predictive coding, as a function of the parameters of the binary asymmetric correlation channel.
Empirical Study on Deep Learning Models for Question Answering
Venue: arXiv cs.CL 2015
Year: 2015

In this paper we explore deep learning models with memory component or attention mechanism for question answering task. We combine and compare three models, Neural Machine Translation, Neural Turing Machine, and Memory Networks for a simulated QA data set. This paper is the first one that uses Neural Machine Translation and Neural Turing Machines for solving QA tasks. Our results suggest that the combination of attention and memory have potential to solve certain QA problem.
Direct-to-Reverberant Ratio Estimation on the ACE Corpus Using a Two-channel Beamformer
Venue: arXiv cs.SD 2015
Year: 2015

Direct-to-Reverberant Ratio (DRR) is an important measure for characterizing the properties of a room. The recently proposed DRR Estimation using a Null-Steered Beamformer (DENBE) algorithm was originally tested on simulated data where noise was artificially added to the speech after convolution with impulse responses simulated using the image-source method. This paper evaluates the performance of this algorithm on speech convolved with measured impulse responses and noise using the Acoustic Characterization of Environments (ACE) Evaluation corpus. The fullband DRR estimation performance of the DENBE algorithm exceeds that of the baselines in all Signal-to-Noise Ratios (SNRs) and noise types. In addition, estimation of the DRR in one third-octave ISO frequency bands is demonstrated.
Towards an Application-Aware Resource Scheduling with Carrier Aggregation in Cellular Systems
Venue: arXiv cs.NI 2015
Year: 2015

In this paper, we introduce an application-aware approach for resource block scheduling with carrier aggregation in Long Term Evolution Advanced (LTE-Advanced) cellular networks. In our approach, users are partitioned in different groups based on the carriers coverage area. In each group of users, users equipments (UE)s are assigned resource blocks (RB)s from all in band carriers. We use a utility proportional fairness (PF) approach in the utility percentage of the application running on the UE. Each user is guaranteed a minimum quality of service (QoS) with a priority criterion that is based on the type of application running on the UE. We prove that our scheduling policy exists and therefore the optimal solution is tractable. Simulation results are provided to compare the performance of the proposed RB scheduling approach with other scheduling policies.
Least costly energy management for series hybrid electric vehicles
Venue: arXiv cs.SY 2015
Year: 2015

Energy management of plug-in Hybrid Electric Vehicles (HEVs) has different challenges from non-plug-in HEVs, due to bigger batteries and grid recharging. Instead of tackling it to pursue energetic efficiency, an approach minimizing the driving cost incurred by the user - the combined costs of fuel, grid energy and battery degradation - is here proposed. A real-time approximation of the resulting optimal policy is then provided, as well as some analytic insight into its dependence on the system parameters. The advantages of the proposed formulation and the effectiveness of the real-time strategy are shown by means of a thorough simulation campaign.
Adaptive Reduced-Rank Minimum Symbol-Error-Rate Receive Processing for Large-Scale Multiple-Antenna Systems
Venue: arXiv cs.IT 2015
Year: 2015

In this work, we propose a novel adaptive reduced-rank receive processing strategy based on joint preprocessing, decimation and filtering (JPDF) for large-scale multiple-antenna systems. In this scheme, a reduced-rank framework is employed for linear receive processing and multiuser interference suppression based on the minimization of the symbol-error-rate (SER) cost function. We present a structure with multiple processing branches that performs a dimensionality reduction, where each branch contains a group of jointly optimized preprocessing and decimation units, followed by a linear receive filter. We then develop stochastic gradient (SG) algorithms to compute the parameters of the preprocessing and receive filters, along with a low-complexity decimation technique for both binary phase shift keying (BPSK) and $M$-ary quadrature amplitude modulation (QAM) symbols. In addition, an automatic parameter selection scheme is proposed to further improve the convergence performance of the proposed reduced-rank algorithms. Simulation results are presented for time-varying wireless environments and show that the proposed JPDF minimum-SER receive processing strategy and algorithms achieve a superior performance than existing methods with a reduced computational complexity.
Dignité - DIGital Network Information & Traces Extraction
Venue: arXiv cs.CR 2015
Year: 2015

Web-based criminality like counterfeiting uses web applications which are hosted on web servers. Those servers contain a lot of information which can be used to identify the owner and other connected persons like hosters, shipping partners, money mules and more. These pieces of information reveal insights on the owner or provider of a fraud website, thus we can call them traces. These traces can then be used by the police, law enforcement authorities or the legal representatives of the victim. In our project 2 we had identified a vast range of possible traces. We had also considered their information content and existing limitations. During our Bachelor thesis, we have selected several traces and started the implementation of the API with its underlying library. After the successful implementation of the selected traces, we have created a graphical user interface to allow the use of our solution without using a command-line interface. To do so, we have learned to use the Scala Programming Language and its integration with Java code. The graphical user interface of our example application is built using Scala Swing, the Scala adoption of the Swing Framework. The test cases are defined using ScalaTest with FlatSpec and Matchers and executed using the JUnit Runner.
Increasing Behavioral Complexity for Evolved Virtual Creatures with the ESP Method
Venue: arXiv cs.NE 2015
Year: 2015

Since their introduction in 1994 (Sims), evolved virtual creatures (EVCs) have employed the coevolution of morphology and control to produce high-impact work in multiple fields, including graphics, evolutionary computation, robotics, and artificial life. However, in contrast to fixed-morphology creatures, there has been no clear increase in the behavioral complexity of EVCs in those two decades. This paper describes a method for moving beyond this limit, making use of high-level human input in the form of a syllabus of intermediate learning tasks--along with mechanisms for preservation, reuse, and combination of previously learned tasks. This method--named ESP for its three components: encapsulation, syllabus, and pandemonium--is presented in two complementary versions: Fast ESP, which constrains later morphological changes to achieve linear growth in computation time as behavioral complexity is added, and General ESP, which allows this restriction to be removed when sufficient computational resources are available. Experiments demonstrate that the ESP method allows evolved virtual creatures to reach new levels of behavioral complexity in the co-evolution of morphology and control, approximately doubling the previous state of the art.
A Fast Randomized Method to Find Homotopy Classes for Socially-Aware Navigation
Venue: arXiv cs.RO 2015
Year: 2015

We introduce and show preliminary results of a fast randomized method that finds a set of K paths lying in distinct homotopy classes. We frame the path planning task as a graph search problem, where the navigation graph is based on a Voronoi diagram. The search is biased by a cost function derived from the social force model that is used to generate and select the paths. We compare our method to Yen's algorithm, and empirically show that our approach is faster to find a subset of homotopy classes. Furthermore our approach computes a set of more diverse paths with respect to the baseline while obtaining a negligible loss in path quality.
Time-frequency and time-scale analysis of deformed stationary processes, with application to non-stationary sound modeling
Venue: arXiv cs.IT 2015
Year: 2015

A class of random non-stationary signals termed timbre x dynamics is introduced and studied. These signals are obtained by non-linear transformations of sta-tionary random gaussian signals, in such a way that the transformation can be approximated by translations in an appropriate representation domain. In such situations, approximate maximum likelihood estimation techniques can be de-rived, which yield simultaneous estimation of the transformation and the power spectrum of the underlying stationary signal. This paper focuses on the case of modulation and time warping of station-ary signals, and proposes and studies estimation algorithms (based on time-frequency and time-scale representations respectively) for these quantities of interest. The proposed approach is validated on numerical simulations on synthetic signals, and examples on real life car engine sounds.
Computing the Ramsey Number R(4,3,3) using Abstraction and Symmetry breaking
Venue: arXiv cs.AI 2015
Year: 2015

The number $R(4,3,3)$ is often presented as the unknown Ramsey number with the best chances of being found "soon". Yet, its precise value has remained unknown for almost 50 years. This paper presents a methodology based on \emph{abstraction} and \emph{symmetry breaking} that applies to solve hard graph edge-coloring problems. The utility of this methodology is demonstrated by using it to compute the value $R(4,3,3)=30$. Along the way it is required to first compute the previously unknown set ${\cal R}(3,3,3;13)$ consisting of 78{,}892 Ramsey colorings.
Control with Probabilistic Signal Temporal Logic
Venue: arXiv cs.SY 2015
Year: 2015

Autonomous agents often operate in uncertain environments where their decisions are made based on beliefs over states of targets. We are interested in controller synthesis for complex tasks defined over belief spaces. Designing such controllers is challenging due to computational complexity and the lack of expressivity of existing specification languages. In this paper, we propose a probabilistic extension to signal temporal logic (STL) that expresses tasks over continuous belief spaces. We present an efficient synthesis algorithm to find a control input that maximises the probability of satisfying a given task. We validate our algorithm through simulations of an unmanned aerial vehicle deployed for surveillance and search missions.
Geometric journal impact factors correcting for individual highly cited articles
Venue: arXiv cs.DL 2015
Year: 2015

Journal impact factors (JIFs) are widely used and promoted but have important limitations. In particular, JIFs can be unduly influenced by individual highly cited articles and hence are inherently unstable. A logical way to reduce the impact of individual high citation counts is to use the geometric mean rather than the standard mean in JIF calculations. Based upon journal rankings 2004-2014 in 50 sub-categories within 5 broad categories, this study shows that journal rankings based on JIF variants tend to be more stable over time if the geometric mean is used rather than the standard mean. The same is true for JIF variants using Mendeley reader counts instead of citation counts. Thus, although the difference is not large, the geometric mean is recommended instead of the arithmetic mean for future JIF calculations. In addition, Mendeley readership-based JIF variants are as stable as those using Scopus citations, confirming the value of Mendeley readership as an academic impact indicator.
A Randomized Algorithm for Long Directed Cycle
Venue: arXiv cs.DS 2015
Year: 2015

Given a directed graph $G$ and a parameter $k$, the {\sc Long Directed Cycle (LDC)} problem asks whether $G$ contains a simple cycle on at least $k$ vertices, while the {\sc $k$-Path} problems asks whether $G$ contains a simple path on exactly $k$ vertices. Given a deterministic (randomized) algorithm for {\sc $k$-Path} as a black box, which runs in time $t(G,k)$, we prove that {\sc LDC} can be solved in deterministic time $O^*(\max\{t(G,2k),4^{k+o(k)}\})$ (randomized time $O^*(\max\{t(G,2k),4^k\})$). In particular, we get that {\sc LDC} can be solved in randomized time $O^*(4^k)$.
Upper Bounds of Interference Alignment Degree of Freedom
Venue: arXiv cs.IT 2015
Year: 2015

Interference alignment allows multiple users to share the same frequency and time resource in a wireless communications system. At present, two performance bounds, in terms of degree of freedom, have been proposed. One is for infinite-dimension extension and the other is for MIMO systems. This paper provides an understanding of the MIMO bound by examining its proofs and shows that it does not apply to a more practical case: MIMO-OFDM. Several approaches are proposed in searching for DoF bounds for systems such as finite-dimension time extension and MIMO-OFDM systems.
Combining Peer-to-Peer and Cloud Computing for Large Scale On-line Games
Venue: arXiv cs.DC 2015
Year: 2015

This thesis investigates the combination of Peer-to-Peer (P2P) and Cloud Computing to support Massively Multiplayer On- line Games (MMOGs). MMOGs are large-scale distributed applications where a large number of users concurrently share a real-time virtual environment. Commercial MMOG infrastructures are sized to support peak loads, incurring in high economical cost. Cloud Computing represents an attractive solution, as it lifts MMOG operators from the burden of buying and maintaining hardware, while offering the illusion of infinite machines. However, it requires balancing the tradeoff between resource provisioning and operational costs. P2P- based solutions present several advantages, including the inherent scalability, self-repairing, and natural load distribution capabilities. They require additional mechanisms to suit the requirements of a MMOG, such as backup solutions to cope with peer unreliability and heterogeneity. We propose mechanisms that integrate P2P and Cloud Computing combining their advantages. Our techniques allow operators to select the ideal tradeoff between performance and economical costs. Using realistic workloads, we show that hybrid infrastructures can reduce the economical effort of the operator, while offering a level of service comparable with centralized architectures.