OpenRaiser/Intern-Atlas huggingface dataset:
Can inferred provenance and its visualisation be used to detect erroneous annotation? A case study using UniProtKB
Venue: arXiv cs.CL 2013
Year: 2013

A constant influx of new data poses a challenge in keeping the annotation in biological databases current. Most biological databases contain significant quantities of textual annotation, which often contains the richest source of knowledge. Many databases reuse existing knowledge, during the curation process annotations are often propagated between entries. However, this is often not made explicit. Therefore, it can be hard, potentially impossible, for a reader to identify where an annotation originated from. Within this work we attempt to identify annotation provenance and track its subsequent propagation. Specifically, we exploit annotation reuse within the UniProt Knowledgebase (UniProtKB), at the level of individual sentences. We describe a visualisation approach for the provenance and propagation of sentences in UniProtKB which enables a large-scale statistical analysis. Initially levels of sentence reuse within UniProtKB were analysed, showing that reuse is heavily prevalent, which enables the tracking of provenance and propagation. By analysing sentences throughout UniProtKB, a number of interesting propagation patterns were identified, covering over 100, 000 sentences. Over 8000 sentences remain in the database after they have been removed from the entries where they originally occurred. Analysing a subset of these sentences suggest that approximately 30% are erroneous, whilst 35% appear to be inconsistent. These results suggest that being able to visualise sentence propagation and provenance can aid in the determination of the accuracy and quality of textual annotation. Source code and supplementary data are available from the authors website.
PACE: Pattern Accurate Computationally Efficient Bootstrapping for Timely Discovery of Cyber-Security Concepts
Venue: arXiv cs.IR 2013
Year: 2013

Public disclosure of important security information, such as knowledge of vulnerabilities or exploits, often occurs in blogs, tweets, mailing lists, and other online sources months before proper classification into structured databases. In order to facilitate timely discovery of such knowledge, we propose a novel semi-supervised learning algorithm, PACE, for identifying and classifying relevant entities in text sources. The main contribution of this paper is an enhancement of the traditional bootstrapping method for entity extraction by employing a time-memory trade-off that simultaneously circumvents a costly corpus search while strengthening pattern nomination, which should increase accuracy. An implementation in the cyber-security domain is discussed as well as challenges to Natural Language Processing imposed by the security domain.
Almost Optimal Channel Access in Multi-Hop Networks With Unknown Channel Variables
Venue: arXiv cs.NI 2013
Year: 2013

We consider distributed channel access in multi-hop cognitive radio networks. Previous works on opportunistic channel access using multi-armed bandits (MAB) mainly focus on single-hop networks that assume complete conflicts among all secondary users. In the multi-hop multi-channel network settings studied here, there is more general competition among different communication pairs. We formulate the problem as a linearly combinatorial MAB problem that involves a maximum weighted independent set (MWIS) problem with unknown weights which need to learn. Existing methods for MAB where each of $N$ nodes chooses from $M$ channels have exponential time and space complexity $O(M^N)$, and poor theoretical guarantee on throughput performance. We propose a distributed channel access algorithm that can achieve $1/ρ$ of the optimum averaged throughput where each node has communication complexity $O(r^2+D)$ and space complexity $O(m)$ in the learning process, and time complexity $O(D m^{ρ^r})$ in strategy decision process for an arbitrary wireless network. Here $ρ=1+ε$ is the approximation ratio to MWIS for a local $r$-hop network with $m<N$ nodes,and $D$ is the number of mini-rounds inside each round of strategy decision. For randomly located networks with an average degree $d$, the time complexity is $O(d^{ρ^r})$.
Matching Demand with Supply in the Smart Grid using Agent-Based Multiunit Auction
Venue: arXiv cs.AI 2013
Year: 2013

Recent work has suggested reducing electricity generation cost by cutting the peak to average ratio (PAR) without reducing the total amount of the loads. However, most of these proposals rely on consumer's willingness to act. In this paper, we propose an approach to cut PAR explicitly from the supply side. The resulting cut loads are then distributed among consumers by the means of a multiunit auction which is done by an intelligent agent on behalf of the consumer. This approach is also in line with the future vision of the smart grid to have the demand side matched with the supply side. Experiments suggest that our approach reduces overall system cost and gives benefit to both consumers and the energy provider.
The Mapping of Simulated Climate-Dependent Building Innovations
Venue: arXiv cs.CE 2013
Year: 2013

Performances of building energy innovations are most of the time dependent on the external climate conditions. This means a high performance of a specific innovation in a certain part of Europe, does not imply the same performances in other regions. The mapping of simulated building performances at the EU scale could prevent the waste of potential good ideas by identifying the best region for a specific innovation. This paper presents a methodology for obtaining maps of performances of building innovations that are virtually spread over whole Europe. It is concluded that these maps are useful for finding regions at the EU where innovations have the highest expected performances.
Diversification Based Static Index Pruning - Application to Temporal Collections
Venue: arXiv cs.IR 2013
Year: 2013

Nowadays, web archives preserve the history of large portions of the web. As medias are shifting from printed to digital editions, accessing these huge information sources is drawing increasingly more attention from national and international institutions, as well as from the research community. These collections are intrinsically big, leading to index files that do not fit into the memory and an increase query response time. Decreasing the index size is a direct way to decrease this query response time. Static index pruning methods reduce the size of indexes by removing a part of the postings. In the context of web archives, it is necessary to remove postings while preserving the temporal diversity of the archive. None of the existing pruning approaches take (temporal) diversification into account. In this paper, we propose a diversification-based static index pruning method. It differs from the existing pruning approaches by integrating diversification within the pruning context. We aim at pruning the index while preserving retrieval effectiveness and diversity by pruning while maximizing a given IR evaluation metric like DCG. We show how to apply this approach in the context of web archives. Finally, we show on two collections that search effectiveness in temporal collections after pruning can be improved using our approach rather than diversity oblivious approaches.
A Unified Framework for Multi-Sensor HDR Video Reconstruction
Venue: arXiv cs.CV 2013
Year: 2013

One of the most successful approaches to modern high quality HDR-video capture is to use camera setups with multiple sensors imaging the scene through a common optical system. However, such systems pose several challenges for HDR reconstruction algorithms. Previous reconstruction techniques have considered debayering, denoising, resampling (align- ment) and exposure fusion as separate problems. In contrast, in this paper we present a unifying approach, performing HDR assembly directly from raw sensor data. Our framework includes a camera noise model adapted to HDR video and an algorithm for spatially adaptive HDR reconstruction based on fitting of local polynomial approximations to observed sensor data. The method is easy to implement and allows reconstruction to an arbitrary resolution and output mapping. We present an implementation in CUDA and show real-time performance for an experimental 4 Mpixel multi-sensor HDR video system. We further show that our algorithm has clear advantages over existing methods, both in terms of flexibility and reconstruction quality.
The Fractal Dimension of SAT Formulas
Venue: arXiv cs.AI 2013
Year: 2013

Modern SAT solvers have experienced a remarkable progress on solving industrial instances. Most of the techniques have been developed after an intensive experimental testing process. Recently, there have been some attempts to analyze the structure of these formulas in terms of complex networks, with the long-term aim of explaining the success of these SAT solving techniques, and possibly improving them. We study the fractal dimension of SAT formulas, and show that most industrial families of formulas are self-similar, with a small fractal dimension. We also show that this dimension is not affected by the addition of learnt clauses. We explore how the dimension of a formula, together with other graph properties can be used to characterize SAT instances. Finally, we give empirical evidence that these graph properties can be used in state-of-the-art portfolios.
1-Visibility Representations of 1-Planar Graphs
Venue: arXiv cs.CG 2013
Year: 2013

A visibility representation is a classical drawing style of planar graphs. It displays the vertices of a graph as horizontal vertex-segments, and each edge is represented by a vertical edge-segment touching the segments of its end vertices; beyond that segments do not intersect. We generalize visibility to 1-visibility, where each edge- (vertex-) segment crosses at most one vertex- (edge-) segment. In other words, a vertex is crossed by at most one edge, and vice-versa. We show that 1-visibility properly extends 1-planarity and develop a linear time algorithm to compute a 1-visibility representation of an embedded 1-planar graph on O(n^2) area. A graph is 1-planar if it can be drawn in the plane such that each edge is crossed at most once. Concerning density, both 1-visible and 1-planar graphs of size $n$ have at most 4n-8 edges. However, for every n >= 7 there are 1-visible graphs with 4n-8 edge which are not 1-planar.
Detect adverse drug reactions for drug Pioglitazone
Venue: arXiv cs.CE 2013
Year: 2013

In this study we propose a novel method to successfully detect the ADRs using feature matrix and feature selection. A feature matrix, which characterizes the medical events before patients take drugs or after patients take drugs, is created from THIN database. The feature selection method of Student's t-test is used to detect the significant features from thousands of medical events. The significant ADRs, which are corresponding to significant features, are detected. Experiments are performed on the drug Pioglitazone. Compared to other computerized methods, our proposed method achieves good performance.
Satisfiability Games for Branching-Time Logics
Venue: arXiv cs.LO 2013
Year: 2013

The satisfiability problem for branching-time temporal logics like CTL*, CTL and CTL+ has important applications in program specification and verification. Their computational complexities are known: CTL* and CTL+ are complete for doubly exponential time, CTL is complete for single exponential time. Some decision procedures for these logics are known; they use tree automata, tableaux or axiom systems. In this paper we present a uniform game-theoretic framework for the satisfiability problem of these branching-time temporal logics. We define satisfiability games for the full branching-time temporal logic CTL* using a high-level definition of winning condition that captures the essence of well-foundedness of least fixpoint unfoldings. These winning conditions form formal languages of ω-words. We analyse which kinds of deterministic ω-automata are needed in which case in order to recognise these languages. We then obtain a reduction to the problem of solving parity or Büchi games. The worst-case complexity of the obtained algorithms matches the known lower bounds for these logics. This approach provides a uniform, yet complexity-theoretically optimal treatment of satisfiability for branching-time temporal logics. It separates the use of temporal logic machinery from the use of automata thus preserving a syntactical relationship between the input formula and the object that represents satisfiability, i.e. a winning strategy in a parity or Büchi game. The games presented here work on a Fischer-Ladner closure of the input formula only. Last but not least, the games presented here come with an attempt at providing tool support for the satisfiability problem of complex branching-time logics like CTL* and CTL+.
On Locally Decodable Source Coding
Venue: arXiv cs.IT 2013
Year: 2013

Locally decodable channel codes form a special class of error-correcting codes with the property that the decoder is able to reconstruct any bit of the input message from querying only a few bits of a noisy codeword. It is well known that such codes require significantly more redundancy (in particular have vanishing rate) compared to their non-local counterparts. In this paper, we define a dual problem, i.e. locally decodable source codes (LDSC). We consider both almost lossless (block error) and lossy (bit error) cases. In almost lossless case, we show that optimal compression (to entropy) is possible with O(log n) queries to compressed string by the decompressor. We also show the following converse bounds: 1) linear LDSC cannot achieve any rate below one, with a bounded number of queries, 2) rate of any source coding with linear decoder (not necessarily local) in one, 3) for 2 queries, any code construction cannot have a rate below one. In lossy case, we show that any rate above rate distortion is achievable with a bounded number of queries. We also show that, rate distortion is achievable with any scaling number of queries. We provide an achievability bound in the finite block-length regime and compare it with the existing bounds in succinct data structures literature.
Ensemble of Distributed Learners for Online Classification of Dynamic Data Streams
Venue: arXiv cs.LG 2013
Year: 2013

We present an efficient distributed online learning scheme to classify data captured from distributed, heterogeneous, and dynamic data sources. Our scheme consists of multiple distributed local learners, that analyze different streams of data that are correlated to a common event that needs to be classified. Each learner uses a local classifier to make a local prediction. The local predictions are then collected by each learner and combined using a weighted majority rule to output the final prediction. We propose a novel online ensemble learning algorithm to update the aggregation rule in order to adapt to the underlying data dynamics. We rigorously determine a bound for the worst case misclassification probability of our algorithm which depends on the misclassification probabilities of the best static aggregation rule, and of the best local classifier. Importantly, the worst case misclassification probability of our algorithm tends asymptotically to 0 if the misclassification probability of the best static aggregation rule or the misclassification probability of the best local classifier tend to 0. Then we extend our algorithm to address challenges specific to the distributed implementation and we prove new bounds that apply to these settings. Finally, we test our scheme by performing an evaluation study on several data sets. When applied to data sets widely used by the literature dealing with dynamic data streams and concept drift, our scheme exhibits performance gains ranging from 34% to 71% with respect to state of the art solutions.
R-Score: Reputation-based Scoring of Research Groups
Venue: arXiv cs.DL 2013
Year: 2013

To manage the problem of having a higher demand for resources than availability of funds, research funding agencies usually rank the major research groups in their area of knowledge. This ranking relies on a careful analysis of the research groups in terms of their size, number of PhDs graduated, research results and their impact, among other variables. While research results are not the only variable to consider, they are frequently given special attention because of the notoriety they confer to the researchers and the programs they are affiliated with. In here we introduce a new metric for quantifying publication output, called R-Score for reputation-based score, which can be used in support to the ranking of research groups or programs. The novelty is that the metric depends solely on the listings of the publications of the members of a group, with no dependency on citation counts. R-Score has some interesting properties: (a) it does not require access to the contents of published material, (b) it can be curated to produce highly accurate results, and (c) it can be naturally used to compare publication output of research groups (e.g., graduate programs) inside a same country, geographical area, or across the world. An experiment comparing the publication output of 25 CS graduate programs from Brazil suggests that R-Score can be quite useful for providing early insights into the publication patterns of the various research groups one wants to compare.
Approximated Symbolic Computations over Hybrid Automata
Venue: arXiv cs.SY 2013
Year: 2013

Hybrid automata are a natural framework for modeling and analyzing systems which exhibit a mixed discrete continuous behaviour. However, the standard operational semantics defined over such models implicitly assume perfect knowledge of the real systems and infinite precision measurements. Such assumptions are not only unrealistic, but often lead to the construction of misleading models. For these reasons we believe that it is necessary to introduce more flexible semantics able to manage with noise, partial information, and finite precision instruments. In particular, in this paper we integrate in a single framework based on approximated semantics different over and under-approximation techniques for hybrid automata. Our framework allows to both compare, mix, and generalize such techniques obtaining different approximated reachability algorithms.
HyLTL: a temporal logic for model checking hybrid systems
Venue: arXiv cs.LO 2013
Year: 2013

The model-checking problem for hybrid systems is a well known challenge in the scientific community. Most of the existing approaches and tools are limited to safety properties only, or operates by transforming the hybrid system to be verified into a discrete one, thus loosing information on the continuous dynamics of the system. In this paper we present a logic for specifying complex properties of hybrid systems called HyLTL, and we show how it is possible to solve the model checking problem by translating the formula into an equivalent hybrid automaton. In this way the problem is reduced to a reachability problem on hybrid automata that can be solved by using existing tools.
Adaptive Backoff Algorithm for IEEE 802.11 DCF under MPR Wireless Channels
Venue: arXiv cs.NI 2013
Year: 2013

As a result of the recent advances in physical (PHY) layer communication techniques, it is possible to receive multiple packets at the receiver concurrently. This capability of a receiver to decode multiple simultaneous transmissions is known as multi-packet reception (MPR). In this paper, we propose a simple Medium Access Control (MAC) protocol for an MPR wireless channel, where we modify the backoff procedure as a function of number of ongoing transmissions in the channel. Our protocol is backward compatible with the IEEE 802.11 DCF protocol. The performance analysis of the proposed protocol is carried out using extensive simulations and it is compared with some of the existing MPR MAC protocols. The proposed mechanism improves the throughput and delay performance of the IEEE 802.11 DCF.
Five Families of Three-Weight Ternary Cyclic Codes and Their Duals
Venue: arXiv cs.IT 2013
Year: 2013

As a subclass of linear codes, cyclic codes have applications in consumer electronics, data storage systems, and communication systems as they have efficient encoding and decoding algorithms. In this paper, five families of three-weight ternary cyclic codes whose duals have two zeros are presented. The weight distributions of the five families of cyclic codes are settled. The duals of two families of the cyclic codes are optimal.
Dynamic Reasoning Systems
Venue: arXiv cs.AI 2013
Year: 2013

A {\it dynamic reasoning system} (DRS) is an adaptation of a conventional formal logical system that explicitly portrays reasoning as a temporal activity, with each extralogical input to the system and each inference rule application being viewed as occurring at a distinct time step. Every DRS incorporates some well-defined logic together with a controller that serves to guide the reasoning process in response to user inputs. Logics are generic, whereas controllers are application-specific. Every controller does, nonetheless, provide an algorithm for nonmonotonic belief revision. The general notion of a DRS comprises a framework within which one can formulate the logic and algorithms for a given application and prove that the algorithms are correct, i.e., that they serve to (i) derive all salient information and (ii) preserve the consistency of the belief set. This paper illustrates the idea with ordinary first-order predicate calculus, suitably modified for the present purpose, and two examples. The latter example revisits some classic nonmonotonic reasoning puzzles (Opus the Penguin, Nixon Diamond) and shows how these can be resolved in the context of a DRS, using an expanded version of first-order logic that incorporates typed predicate symbols. All concepts are rigorously defined and effectively computable, thereby providing the foundation for a future software implementation.
Second-Order Algebraic Theories
Venue: arXiv cs.LO 2013
Year: 2013

Fiore and Hur recently introduced a conservative extension of universal algebra and equational logic from first to second order. Second-order universal algebra and second-order equational logic respectively provide a model theory and a formal deductive system for languages with variable binding and parameterised metavariables. This work completes the foundations of the subject from the viewpoint of categorical algebra. Specifically, the paper introduces the notion of second-order algebraic theory and develops its basic theory. Two categorical equivalences are established: at the syntactic level, that of second-order equational presentations and second-order algebraic theories; at the semantic level, that of second-order algebras and second-order functorial models. Our development includes a mathematical definition of syntactic translation between second-order equational presentations. This gives the first formalisation of notions such as encodings and transforms in the context of languages with variable binding.