OpenRaiser/Intern-Atlas huggingface dataset:
A Study of the Matter of SPH Application to Saturated Soil Problems
Venue: arXiv cs.CE 2015
Year: 2015

We present an application of SPH to saturated soilproblems. Herein, the standard SPH formulation was improved to model saturated soil. It is shown that the proposed formulation could yield several advantages such as: it takes into account the pore-water pressure in an accurate manner, it automatically satisfies the dynamics boundary conditions between submerged soil and water, and it reduced the computational cost. Discussions on the use of the standard and the new SPH formulations are also given through some numerical tests. Furthermore, some techniques to obtained correct SPH solution are also proposed and discussed. To the end, this paper suggests that the proposed SPH formulation should be considered as the basic formulation for further developments of SPH for soil-water couple problems
Context Models For Web Search Personalization
Venue: arXiv cs.IR 2015
Year: 2015

We present our solution to the Yandex Personalized Web Search Challenge. The aim of this challenge was to use the historical search logs to personalize top-N document rankings for a set of test users. We used over 100 features extracted from user- and query-depended contexts to train neural net and tree-based learning-to-rank and regression models. Our final submission, which was a blend of several different models, achieved an NDCG@10 of 0.80476 and placed 4'th amongst the 194 teams winning 3'rd prize.
Cost-Efficient Throughput Maximization in Multi-Carrier Cognitive Radio Systems
Venue: arXiv cs.IT 2015
Year: 2015

Cognitive radio (CR) systems allow opportunistic, secondary users (SUs) to access portions of the spectrum that are unused by the network's licensed primary users (PUs), provided that the induced interference does not compromise the primary users' performance guarantees. To account for interference constraints of this type, we consider a flexible spectrum access pricing scheme that charges secondary users based on the interference that they cause to the system's primary users (individually, globally, or both), and we examine how secondary users can maximize their achievable transmission rate in this setting. We show that the resulting non-cooperative game admits a unique Nash equilibrium under very mild assumptions on the pricing mechanism employed by the network operator, and under both static and ergodic (fast-fading) channel conditions. In addition, we derive a dynamic power allocation policy that converges to equilibrium within a few iterations (even for large numbers of users), and which relies only on local signal-to-interference-and-noise measurements; importantly, the proposed algorithm retains its convergence properties even in the ergodic channel regime, despite the inherent stochasticity thereof. Our theoretical analysis is complemented by extensive numerical simulations which illustrate the performance and scalability properties of the proposed pricing scheme under realistic network conditions.
Throwing Out the Baby with the Bathwater: The Undesirable Effects of National Research Assessment Exercises on Research
Venue: arXiv cs.DL 2015
Year: 2015

The evaluation of the quality of research at a national level has become increasingly common. The UK has been at the forefront of this trend having undertaken many assessments since 1986, the latest being the Research Excellence Framework in 2014. The argument of this paper is that, whatever the intended results in terms of evaluating and improving research, there have been many, presumably unintended, results that are highly undesirable for research and the university community more generally. We situate our analysis using Bourdieu's theory of cultural reproduction and then focus on the peculiarities of the 2008 RAE and the 2014 REF the rules of which allowed for, and indeed encouraged, significant game-playing on the part of striving universities. We conclude with practical recommendations to maintain the general intention of research assessment without the undesirable side-effects.
Incremental Knowledge Base Construction Using DeepDive
Venue: arXiv cs.DB 2015
Year: 2015

Populating a database with unstructured information is a long-standing problem in industry and research that encompasses problems of extraction, cleaning, and integration. Recent names used for this problem include dealing with dark data and knowledge base construction (KBC). In this work, we describe DeepDive, a system that combines database and machine learning ideas to help develop KBC systems, and we present techniques to make the KBC process more efficient. We observe that the KBC process is iterative, and we develop techniques to incrementally produce inference results for KBC systems. We propose two methods for incremental inference, based respectively on sampling and variational techniques. We also study the tradeoff space of these methods and develop a simple rule-based optimizer. DeepDive includes all of these contributions, and we evaluate DeepDive on five KBC systems, showing that it can speed up KBC inference tasks by up to two orders of magnitude with negligible impact on quality.
CHAOS: Accurate and Realtime Detection of Aging-Oriented Failure Using Entropy
Venue: arXiv cs.OH 2015
Year: 2015

Even well-designed software systems suffer from chronic performance degradation, also named "software aging", due to internal (e.g. software bugs) and external (e.g. resource exhaustion) impairments. These chronic problems often fly under the radar of software monitoring systems before causing severe impacts (e.g. system failure). Therefore it's a challenging issue how to timely detect these problems to prevent system crash. Although a large quantity of approaches have been proposed to solve this issue, the accuracy and effectiveness of these approaches are still far from satisfactory due to the insufficiency of aging indicators adopted by them. In this paper, we present a novel entropy-based aging indicator, Multidimensional Multi-scale Entropy (MMSE). MMSE employs the complexity embedded in runtime performance metrics to indicate software aging and leverages multi-scale and multi-dimension integration to tolerate system fluctuations. Via theoretical proof and experimental evaluation, we demonstrate that MMSE satisfies Stability, Monotonicity and Integration which we conjecture that an ideal aging indicator should have. Based upon MMSE, we develop three failure detection approaches encapsulated in a proof-of-concept named CHAOS. The experimental evaluations in a Video on Demand (VoD) system and in a real-world production system, AntVision, show that CHAOS can detect the failure-prone state in an extraordinarily high accuracy and a near 0 Ahead-Time-To-Failure (ATTF). Compared to previous approaches, CHAOS improves the detection accuracy by about 5 times and reduces the ATTF even by 3 orders of magnitude. In addition, CHAOS is light-weight enough to satisfy the realtime requirement.
Best Signal Quality in Cellular Networks: Asymptotic Properties and Applications to Mobility Management in Small Cell Networks
Venue: arXiv cs.IT 2015
Year: 2015

The quickly increasing data traffic and the user demand for a full coverage of mobile services anywhere and anytime are leading mobile networking into a future of small cell networks. However, due to the high-density and randomness of small cell networks, there are several technical challenges. In this paper, we investigate two critical issues: \emph{best signal quality} and \emph{mobility management}. Under the assumptions that base stations are uniformly distributed in a ring shaped region and that shadowings are lognormal, independent and identically distributed, we prove that when the number of sites in the ring tends to infinity, then (i) the maximum signal strength received at the center of the ring tends in distribution to a Gumbel distribution when properly renormalized, and (ii) it is asymptotically independent of the interference. Using these properties, we derive the distribution of the best signal quality. Furthermore, an optimized random cell scanning scheme is proposed, based on the evaluation of the optimal number of sites to be scanned for maximizing the user data throughput.
Open System Categorical Quantum Semantics in Natural Language Processing
Venue: arXiv cs.CL 2015
Year: 2015

Originally inspired by categorical quantum mechanics (Abramsky and Coecke, LiCS'04), the categorical compositional distributional model of natural language meaning of Coecke, Sadrzadeh and Clark provides a conceptually motivated procedure to compute the meaning of a sentence, given its grammatical structure within a Lambek pregroup and a vectorial representation of the meaning of its parts. The predictions of this first model have outperformed that of other models in mainstream empirical language processing tasks on large scale data. Moreover, just like CQM allows for varying the model in which we interpret quantum axioms, one can also vary the model in which we interpret word meaning. In this paper we show that further developments in categorical quantum mechanics are relevant to natural language processing too. Firstly, Selinger's CPM-construction allows for explicitly taking into account lexical ambiguity and distinguishing between the two inherently different notions of homonymy and polysemy. In terms of the model in which we interpret word meaning, this means a passage from the vector space model to density matrices. Despite this change of model, standard empirical methods for comparing meanings can be easily adopted, which we demonstrate by a small-scale experiment on real-world data. This experiment moreover provides preliminary evidence of the validity of our proposed new model for word meaning. Secondly, commutative classical structures as well as their non-commutative counterparts that arise in the image of the CPM-construction allow for encoding relative pronouns, verbs and adjectives, and finally, iteration of the CPM-construction, something that has no counterpart in the quantum realm, enables one to accommodate both entailment and ambiguity.
A multiset model of multi-species evolution to solve big deceptive problems
Venue: arXiv cs.NE 2015
Year: 2015

This chapter presents SMuGA, an integration of symbiogenesis with the Multiset Genetic Algorithm (MuGA). The symbiogenetic approach used here is based on the host-parasite model with the novelty of varying the length of parasites along the evolutionary process. Additionally, it models collaborations between multiple parasites and a single host. To improve efficiency, we introduced proxy evaluation of parasites, which saves fitness function calls and exponentially reduces the symbiotic collaborations produced. Another novel feature consists of breaking the evolutionary cycle into two phases: a symbiotic phase and a phase of independent evolution of both hosts and parasites. SMuGA was tested in optimization of a variety of deceptive functions, with results one order of magnitude better than state of the art symbiotic algorithms. This allowed to optimize deceptive problems with large sizes, and showed a linear scaling in the number of iterations to attain the optimum.
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification
Venue: arXiv cs.CV 2015
Year: 2015

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structure. In this paper, we propose an automatic feature discovery framework for extracting discriminative class-specific features and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific features which are suitable for representing samples from the same class while are poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian lung images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, show the significance of DFDL model in a variety problems over state-of-the-art methods
Consensus with Linear Objective Maps
Venue: arXiv cs.SY 2015
Year: 2015

A consensus system is a linear multi-agent system in which agents communicate to reach a so-called consensus state, defined as the average of the initial states of the agents. Consider a more generalized situation in which each agent is given a positive weight and the consensus state is defined as the weighted average of the initial conditions. We characterize in this paper the weighted averages that can be evaluated in a decentralized way by agents communicating over a directed graph. Specifically, we introduce a linear function, called the objective map, that defines the desired final state as a function of the initial states of the agents. We then provide a complete answer to the question of whether there is a decentralized consensus dynamics over a given digraph which converges to the final state specified by an objective map. In particular, we characterize not only the set of objective maps that are feasible for a given digraph, but also the consensus dynamics that implements the objective map. In addition, we present a decentralized algorithm to design the consensus dynamics.
Optimization of Quality of Experience through File Duplication in Video Sharing Servers
Venue: arXiv cs.NI 2015
Year: 2015

Consumers of short videos on Internet can have a bad Quality of Experience QoE due to the long distance between the consumers and the servers that hosting the videos. We propose an optimization of the file allocation in telecommunication operators content sharing servers to improve the QoE through files duplication, thus bringing the files closer to the consumers. This optimization allows the network operator to set the level of QoE and to have control over the users access cost by setting a number of parameters. Two optimization methods are given and are followed by a comparison of their efficiency. Also, the hosting costs versus the gain of optimization are analytically discussed.
Hash Chain Links Resynchronization Methods in Video Streaming Security Performance Comparison
Venue: arXiv cs.CR 2015
Year: 2015

Hash chains provide a secure and light way of security to data authentication including two aspects: Data Integrity and Data Origin Authentication. The real challenge of using the hash chains is how it could recover the synchronization state and continue keeping the hash link in case of packet loss? Based on the packet loss tolerance and some accepted delay of video delivery which are representing the permitted tolerance for heavy loaded applications, we propose different mechanisms for such synchronization recovery. Each mechanism is suitable to use according to the video use case and the low capabilities of end devices. This paper proposes comparative results between them based on the status of each one and its overhead. Then, we propose a hybrid technique based Redundancy Code (RC). This hybrid algorithm is simulated and compared analytically against the other techniques (SHHC, TSP, MLHC and TSS). Moreover, a global performance evaluation in terms of delay and overhead is conducted for all techniques.
Is There WiFi Yet? How Aggressive WiFi Probe Requests Deteriorate Energy and Throughput
Venue: arXiv cs.NI 2015
Year: 2015

WiFi offloading has emerged as a key component of cellular operator strategy to meet the data needs of rich, mobile devices. As such, mobile devices tend to aggressively seek out WiFi in order to provide improved user Quality of Experience (QoE) and cellular capacity relief. For home and work environments, aggressive WiFi scans can significantly improve the speed on which mobile nodes join the WiFi network. Unfortunately, the same aggressive behavior that excels in the home environment incurs considerable side effects across crowded wireless environments. In this paper, we show through empirical studies at both large (stadium) and small (laboratory) scales how aggressive WiFi scans can have significant implications for energy and throughput, both for the mobile nodes scanning and other nearby mobile nodes. We close with several thoughts on the disjoint incentives for properly balancing WiFi discovery speed and ultra-dense network interactions.
Exploiting Multimodal Biometrics in E-Privacy Scheme for Electronic Health Records
Venue: arXiv cs.CR 2015
Year: 2015

Existing approaches to protect the privacy of Electronic Health Records are either insufficient for existing medical laws or they are too restrictive in their usage. For example, smart card-based encryption systems require the patient to be always present to authorize access to medical records. Questionnaires were administered by 50 medical practitioners to identify and categorize different Electronic Health Records attributes. The system was implemented using multi biometrics of patients to access patient record in pre-hospital care.The software development tools employed were JAVA and MySQL database. The system provides applicable security when patients records are shared either with other practitioners, employers, organizations or research institutes. The result of the system evaluation shows that the average response time of 6 seconds and 11.1 seconds for fingerprint and iris respectively after ten different simulations. The system protects privacy and confidentiality by limiting the amount of data exposed to users.The system also enables emergency medical technicians to gain easy and reliable access to necessary attributes of patients Electronic Health Records while still maintaining the privacy and confidentiality of the data using the patients fingerprint and iris.
A Predictive Framework for Cyber Security Analytics using Attack Graphs
Venue: arXiv cs.CR 2015
Year: 2015

Security metrics serve as a powerful tool for organizations to understand the effectiveness of protecting computer networks. However majority of these measurement techniques don't adequately help corporations to make informed risk management decisions. In this paper we present a stochastic security framework for obtaining quantitative measures of security by taking into account the dynamic attributes associated with vulnerabilities that can change over time. Our model is novel as existing research in attack graph analysis do not consider the temporal aspects associated with the vulnerabilities, such as the availability of exploits and patches which can affect the overall network security based on how the vulnerabilities are interconnected and leveraged to compromise the system. In order to have a more realistic representation of how the security state of the network would vary over time, a nonhomogeneous model is developed which incorporates a time dependent covariate, namely the vulnerability age. The daily transition-probability matrices are estimated using Frei's Vulnerability Lifecycle model. We also leverage the trusted CVSS metric domain to analyze how the total exploitability and impact measures evolve over a time period for a given network.
Towards a Complexity-through-Realisability Theory
Venue: arXiv cs.LO 2015
Year: 2015

We explain how recent developments in the fields of realisability models for linear logic -- or geometry of interaction -- and implicit computational complexity can lead to a new approach of implicit computational complexity. This semantic-based approach should apply uniformly to various computational paradigms, and enable the use of new mathematical methods and tools to attack problem in computational complexity. This paper provides the background, motivations and perspectives of this complexity-through-realisability theory to be developed, and illustrates it with recent results.
A Falsification View of Success Typing
Venue: arXiv cs.PL 2015
Year: 2015

Dynamic languages are praised for their flexibility and expressiveness, but static analysis often yields many false positives and verification is cumbersome for lack of structure. Hence, unit testing is the prevalent incomplete method for validating programs in such languages. Falsification is an alternative approach that uncovers definite errors in programs. A falsifier computes a set of inputs that definitely crash a program. Success typing is a type-based approach to document programs in dynamic languages. We demonstrate that success typing is, in fact, an instance of falsification by mapping success (input) types into suitable logic formulae. Output types are represented by recursive types. We prove the correctness of our mapping (which establishes that success typing is falsification) and we report some experiences with a prototype implementation.
Visualizing Marden's theorem with Scilab
Venue: arXiv cs.MS 2015
Year: 2015

A theorem which is named after the American Mathematician Moris Marden states a very surprising and interesting fact concerning the relationship between the points of a triangle in the complex plane and the zeros of two complex polynomials related to this triangle: "Suppose the zeroes z1, z2, and z3 of a third-degree polynomial p(z) are non-collinear. There is a unique ellipse inscribed in the triangle with vertices z1, z2, z3 and tangent to the sides at their midpoints: the Steiner in-ellipse. The foci of that ellipse are the zeroes of the derivative p'(z)." (Wikipedia contributors, "Marden's theorem", http://en.wikipedia.org/wiki/Marden%27s_theorem). This document describes how Scilab, a popular and powerful open source alternative to MATLAB, can be used to visualize the above stated theorem for arbitrary complex numbers z1, z2, and z3 which are not collinear. It is further demonstrated how the equations of the Steiner ellipses of a triangle in the complex plane can be calculated and plotted by applying this theorem.
Close Approximations for Daublets and their Spectra
Venue: arXiv cs.NA 2015
Year: 2015

This paper offers a new regard on compactly supported wavelets derived from FIR filters. Although being continuous wavelets, analytical formulation are lacking for such wavelets. Close approximations for daublets (Daubechies wavelets) and their spectra are introduced here. The frequency detection properties of daublets are investigated through scalograms derived from these new analytical expressions. These near-daublets have been implemented on the Matlab wavelet toolbox and a few scalograms presented. This approach can be valuable for wavelet synthesis from hardware or for application involving continuous wavelet-based systems, such as wavelet OFDM.
Parameterized Complexity of Superstring Problems
Venue: arXiv cs.DS 2015
Year: 2015

In the Shortest Superstring problem we are given a set of strings $S=\{s_1, \ldots, s_n\}$ and integer $\ell$ and the question is to decide whether there is a superstring $s$ of length at most $\ell$ containing all strings of $S$ as substrings. We obtain several parameterized algorithms and complexity results for this problem. In particular, we give an algorithm which in time $2^{O(k)} \operatorname{poly}(n)$ finds a superstring of length at most $\ell$ containing at least $k$ strings of $S$. We complement this by the lower bound showing that such a parameterization does not admit a polynomial kernel up to some complexity assumption. We also obtain several results about "below guaranteed values" parameterization of the problem. We show that parameterization by compression admits a polynomial kernel while parameterization "below matching" is hard.