OpenRaiser/Intern-Atlas huggingface dataset:
Maximum Likelihood based Multihop Localization in Wireless Sensor Networks
Venue: arXiv cs.NI 2015
Year: 2015

For data sets retrieved from wireless sensors to be insightful, it is often of paramount importance that the data be accurate and also location stamped. This paper describes a maximum-likelihood based multihop localization algorithm called kHopLoc for use in wireless sensor networks that is strong in both isotropic and anisotropic network deployment regions. During an initial training phase, a Monte Carlo simulation is utilized to produce multihop connection density functions. Then, sensor node locations are estimated by maximizing local likelihood functions of the hop counts to anchor nodes. Compared to other multihop localization algorithms, the proposed kHopLoc algorithm achieves higher accuracy in varying network configurations and connection link-models.
Is a global virtual currency with universal acceptance feasible ?
Venue: arXiv cs.CY 2015
Year: 2015

As digital goods and services become an integral part of modern day society, the demand for a standardized and ubiquitous form of digital currency increases. And it is not just about digital goods; the adoption of electronic and mobile commerce has not reached its expected level at all parts of the globe as expected. One of the main reasons behind that is the lack of a universal digital as well as virtual currency. Many countries in the world have failed to realize the potential of e-commerce, let alone m-commerce, because of rigid financial regulations and apparent disorientation & gap between monetary stakeholders across borders and continents. Digital currency which is internet-based, non-banks issued and circulated within a certain range of networks has brought a significant impact on the development of e-commerce. The research and analysis of this paper would focus on the feasibility of the operation of a digital currency and its economic implications.
A Survey on Hough Transform, Theory, Techniques and Applications
Venue: arXiv cs.CV 2015
Year: 2015

For more than half a century, the Hough transform is ever-expanding for new frontiers. Thousands of research papers and numerous applications have evolved over the decades. Carrying out an all-inclusive survey is hardly possible and enormously space-demanding. What we care about here is emphasizing some of the most crucial milestones of the transform. We describe its variations elaborating on the basic ones such as the line and circle Hough transforms. The high demand for storage and computation time is clarified with different solution approaches. Since most uses of the transform take place on binary images, we have been concerned with the work done directly on gray or color images. The myriad applications of the standard transform and its variations have been classified highlighting the up-to-date and the unconventional ones. Due to its merits such as noise-immunity and expandability, the transform has an excellent history, and a bright future as well.
Collective decision efficiency and optimal voting mechanisms: A comprehensive overview for multi-classifier models
Venue: arXiv cs.GT 2015
Year: 2015

A new game-theoretic approach for combining multiple classifiers is proposed. A short introduction in Game Theory and coalitions illustrate the way any collective decision scheme can be viewed as a competitive game of coalitions that are formed naturally when players state their preferences. The winning conditions and the voting power of each player are studied under the scope of voting power indices, as well and the collective competence of the group. Coalitions and power indices are presented in relation to the Condorcet criterion of optimality in voting systems, and weighted Borda count models are asserted as a way to implement them in practice. A special case of coalition games, the weighted majority games (WMG) are presented as a restricted realization in dichotomy choice situations. As a result, the weighted majority rules (WMR), an extended version of the simple majority rules, are asserted as the theoretically optimal and complete solution to this type of coalition gaming. Subsequently, a generalized version of WMRs is suggested as the means to design a voting system that is optimal in the sense of both the correct classification criterion and the Condorcet efficiency criterion. In the scope of Pattern Recognition, a generalized risk-based approach is proposed as the framework upon which any classifier combination scheme can be applied. A new fully adaptive version of WMRs is proposed as a statistically invariant way of adjusting the design process of the optimal WMR to the arbitrary non-symmetrical properties of the underlying feature space. SVM theory is associated with properties and conclusions that emerge from the game-theoretic approach of the classification in general, while the theoretical and practical implications of employing SVM experts in WMR combination schemes are briefly discussed. Finally, a summary of the most important issues for further research is presented.
The Silver Lining Around Fearful Living
Venue: arXiv cs.AI 2015
Year: 2015

This paper discusses in layperson's terms human and computational studies of the impact of threat and fear on exploration and creativity. A first study showed that both killifish from a lake with predators and from a lake without predators explore a new environment to the same degree and plotting number of new spaces covered over time generates a hump-shaped curve. However, for the fish from the lake with predators the curve is shifted to the right; they take longer. This pattern was replicated by a computer model of exploratory behavior varying only one parameter, the fear parameter. A second study showed that stories inspired by threatening photographs were rated as more creative than stories inspired by non-threatening photographs. Various explanations for the findings are discussed.
FRAME: Fast and Realistic Attacker Modeling and Evaluation for Temporal Logical Correlation in Static Noise
Venue: arXiv cs.OH 2015
Year: 2015

We propose a method called Fast and Realistic Attacker Modeling and Evaluation (FRAME) that can reduce pessimism in static noise analysis by exploiting temporal logical correlation of attackers and using novel techniques termed envelopes and $σ$ functions. Unlike conventional pruning-based approaches, FRAME efficiently considers all relevant attackers, thereby producing more realistic results. FRAME was tested with complex industrial design and successfully reduced the pessimism of conventional techniques by 30.4% on average, with little computational overhead.
Improving Term Frequency Normalization for Multi-topical Documents, and Application to Language Modeling Approaches
Venue: arXiv cs.IR 2015
Year: 2015

Term frequency normalization is a serious issue since lengths of documents are various. Generally, documents become long due to two different reasons - verbosity and multi-topicality. First, verbosity means that the same topic is repeatedly mentioned by terms related to the topic, so that term frequency is more increased than the well-summarized one. Second, multi-topicality indicates that a document has a broad discussion of multi-topics, rather than single topic. Although these document characteristics should be differently handled, all previous methods of term frequency normalization have ignored these differences and have used a simplified length-driven approach which decreases the term frequency by only the length of a document, causing an unreasonable penalization. To attack this problem, we propose a novel TF normalization method which is a type of partially-axiomatic approach. We first formulate two formal constraints that the retrieval model should satisfy for documents having verbose and multi-topicality characteristic, respectively. Then, we modify language modeling approaches to better satisfy these two constraints, and derive novel smoothing methods. Experimental results show that the proposed method increases significantly the precision for keyword queries, and substantially improves MAP (Mean Average Precision) for verbose queries.
Model Checking C Programs with Loops via k-Induction and Invariants
Venue: arXiv cs.LO 2015
Year: 2015

We present a novel proof by induction algorithm, which combines k-induction with invariants to model check C programs with bounded and unbounded loops. The k-induction algorithm consists of three cases: in the base case, we aim to find a counterexample with up to k loop unwindings; in the forward condition, we check whether loops have been fully unrolled and that the safety property P holds in all states reachable within k unwindings; and in the inductive step, we check that whenever P holds for k unwindings, it also holds after the next unwinding of the system. For each step of the k-induction algorithm, we infer invariants using affine constraints (i.e., polyhedral) to specify pre- and post-conditions. The algorithm was implemented in two different ways, with and without invariants using polyhedral, and the results were compared. Experimental results show that both forms can handle a wide variety of safety properties; however, the k-induction algorithm adopting polyhedral solves more verification tasks, which demonstrate an improvement of the induction algorithm effectiveness.
Context-free Algorithms
Venue: arXiv cs.FL 2015
Year: 2015

Algorithms on grammars/transducers with context-free derivations: hypergraph reachability, shortest path, and inside-outside pruning of 'relatively useless' arcs that are unused by any near-shortest paths.
First Women, Second Sex: Gender Bias in Wikipedia
Venue: arXiv cs.SI 2015
Year: 2015

Contributing to history has never been as easy as it is today. Anyone with access to the Web is able to play a part on Wikipedia, an open and free encyclopedia. Wikipedia, available in many languages, is one of the most visited websites in the world and arguably one of the primary sources of knowledge on the Web. However, not everyone is contributing to Wikipedia from a diversity point of view; several groups are severely underrepresented. One of those groups is women, who make up approximately 16% of the current contributor community, meaning that most of the content is written by men. In addition, although there are specific guidelines of verifiability, notability, and neutral point of view that must be adhered by Wikipedia content, these guidelines are supervised and enforced by men. In this paper, we propose that gender bias is not about participation and representation only, but also about characterization of women. We approach the analysis of gender bias by defining a methodology for comparing the characterizations of men and women in biographies in three aspects: meta-data, language, and network structure. Our results show that, indeed, there are differences in characterization and structure. Some of these differences are reflected from the off-line world documented by Wikipedia, but other differences can be attributed to gender bias in Wikipedia content. We contextualize these differences in feminist theory and discuss their implications for Wikipedia policy.
Random Preferential Attachment Hypergraphs
Venue: arXiv cs.SI 2015
Year: 2015

The random graph model has recently been extended to a random preferential attachment graph model, in order to enable the study of general asymptotic properties in network types that are better represented by the preferential attachment evolution model than by the ordinary (uniform) evolution lodel. Analogously, this paper extends the random {\em hypergraph} model to a random {\em preferential attachment hypergraph} model. We then analyze the degree distribution of random preferential attachment hypergraphs and show that they possess heavy tail degree distribution properties similar to those of random preferential attachment graphs. However, our results show that the exponent of the degree distribution is sensitive to whether one considers the structure as a hypergraph or as a graph.
A Social Spider Algorithm for Global Optimization
Venue: arXiv cs.NE 2015
Year: 2015

The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Metaheuristics based on evolutionary computation and swarm intelligence are outstanding examples of nature-inspired solution techniques. Inspired by the social spiders, we propose a novel Social Spider Algorithm to solve global optimization problems. This algorithm is mainly based on the foraging strategy of social spiders, utilizing the vibrations on the spider web to determine the positions of preys. Different from the previously proposed swarm intelligence algorithms, we introduce a new social animal foraging strategy model to solve optimization problems. In addition, we perform preliminary parameter sensitivity analysis for our proposed algorithm, developing guidelines for choosing the parameter values. The Social Spider Algorithm is evaluated by a series of widely-used benchmark functions, and our proposed algorithm has superior performance compared with other state-of-the-art metaheuristics.
Nonparametric Simultaneous Sparse Recovery: an Application to Source Localization
Venue: arXiv cs.IT 2015
Year: 2015

We consider multichannel sparse recovery problem where the objective is to find good recovery of jointly sparse unknown signal vectors from the given multiple measurement vectors which are different linear combinations of the same known elementary vectors. Many popular greedy or convex algorithms perform poorly under non-Gaussian heavy-tailed noise conditions or in the face of outliers. In this paper, we propose the usage of mixed $\ell_{p,q}$ norms on data fidelity (residual matrix) term and the conventional $\ell_{0,2}$-norm constraint on the signal matrix to promote row-sparsity. We devise a greedy pursuit algorithm based on simultaneous normalized iterative hard thresholding (SNIHT) algorithm. Simulation studies highlight the effectiveness of the proposed approaches to cope with different noise environments (i.i.d., row i.i.d, etc) and outliers. Usefulness of the methods are illustrated in source localization application with sensor arrays.
Fourier Codes and Hartley Codes
Venue: arXiv cs.IT 2015
Year: 2015

Real-valued block codes are introduced, which are derived from Discrete Fourier Transforms (DFT) and Discrete Hartley Transforms (DHT). These algebraic structures are built from the eigensequences of the transforms. Generator and parity check matrices were computed for codes up to block length N=24. They can be viewed as lattices codes so the main parameters (dimension, minimal norm, area of the Voronoi region, density, and centre density) are computed. Particularly, Hamming-Hartley and Golay-Hartley block codes are presented. These codes may possibly help an efficient computation of a DHT/DFT.
Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks
Venue: arXiv cs.CV 2015
Year: 2015

Pattern recognition methods using neuroimaging data for the diagnosis of Alzheimer's disease have been the subject of extensive research in recent years. In this paper, we use deep learning methods, and in particular sparse autoencoders and 3D convolutional neural networks, to build an algorithm that can predict the disease status of a patient, based on an MRI scan of the brain. We report on experiments using the ADNI data set involving 2,265 historical scans. We demonstrate that 3D convolutional neural networks outperform several other classifiers reported in the literature and produce state-of-art results.
Efficient model-based reinforcement learning for approximate online optimal
Venue: arXiv cs.SY 2015
Year: 2015

In this paper the infinite horizon optimal regulation problem is solved online for a deterministic control-affine nonlinear dynamical system using the state following (StaF) kernel method to approximate the value function. Unlike traditional methods that aim to approximate a function over a large compact set, the StaF kernel method aims to approximate a function in a small neighborhood of a state that travels within a compact set. Simulation results demonstrate that stability and approximate optimality of the control system can be achieved with significantly fewer basis functions than may be required for global approximation methods.
Fuzzy finite element solution of uncertain neutron diffusion equation for imprecisely defined homogeneous triangular bare reactor
Venue: arXiv cs.CE 2015
Year: 2015

Scattering of neutron collision inside a reactor depends upon geometry of the reactor, diffusion coefficient and absorption coefficient etc. In general these parameters are not crisp and hence we may get uncertain neutron diffusion equation. In this paper we have investigated the above problem for a bare triangular homogeneous reactor. Here the uncertain governing differential equation is modelled by a modified fuzzy finite element method using newly proposed interval arithmetic. Obtained eigenvalues by the proposed method are studied in detail. Further the eigenvalues are compared with the classical finite element method in special cases and various uncertain results have been discussed.
Counterexample Explanation by Learning Small Strategies in Markov Decision Processes
Venue: arXiv cs.LO 2015
Year: 2015

While for deterministic systems, a counterexample to a property can simply be an error trace, counterexamples in probabilistic systems are necessarily more complex. For instance, a set of erroneous traces with a sufficient cumulative probability mass can be used. Since these are too large objects to understand and manipulate, compact representations such as subchains have been considered. In the case of probabilistic systems with non-determinism, the situation is even more complex. While a subchain for a given strategy (or scheduler, resolving non-determinism) is a straightforward choice, we take a different approach. Instead, we focus on the strategy - which can be a counterexample to violation of or a witness of satisfaction of a property - itself, and extract the most important decisions it makes, and present its succinct representation. The key tools we employ to achieve this are (1) introducing a concept of importance of a state w.r.t. the strategy, and (2) learning using decision trees. There are three main consequent advantages of our approach. Firstly, it exploits the quantitative information on states, stressing the more important decisions. Secondly, it leads to a greater variability and degree of freedom in representing the strategies. Thirdly, the representation uses a self-explanatory data structure. In summary, our approach produces more succinct and more explainable strategies, as opposed to e.g. binary decision diagrams. Finally, our experimental results show that we can extract several rules describing the strategy even for very large systems that do not fit in memory, and based on the rules explain the erroneous behaviour.
An Integrated Semantic Web Service Discovery and Composition Framework
Venue: arXiv cs.AI 2015
Year: 2015

In this paper we present a theoretical analysis of graph-based service composition in terms of its dependency with service discovery. Driven by this analysis we define a composition framework by means of integration with fine-grained I/O service discovery that enables the generation of a graph-based composition which contains the set of services that are semantically relevant for an input-output request. The proposed framework also includes an optimal composition search algorithm to extract the best composition from the graph minimising the length and the number of services, and different graph optimisations to improve the scalability of the system. A practical implementation used for the empirical analysis is also provided. This analysis proves the scalability and flexibility of our proposal and provides insights on how integrated composition systems can be designed in order to achieve good performance in real scenarios for the Web.
A numbers-on-foreheads game
Venue: arXiv cs.GT 2015
Year: 2015

Is there a joint distribution of $n$ random variables over the natural numbers, such that they always form an increasing sequence and whenever you take two subsets of the set of random variables of the same cardinality, their distribution is almost the same? We show that the answer is yes, but that the random variables will have to take values as large as $2^{2^{\dots ^{2^{Θ\left(\frac{1}ε\right)}}}}$, where $ε\leq ε_n$ measures how different the two distributions can be, the tower contains $n-2$ $2$'s and the constants in the $Θ$ notation are allowed to depend on $n$. This result has an important consequence in game theory: It shows that even though you can define extensive form games that cannot be implemented on players who can tell the time, you can have implementations that approximate the game arbitrarily well.
Massive M2M Access with Reliability Guarantees in LTE Systems
Venue: arXiv cs.IT 2015
Year: 2015

Machine-to-Machine (M2M) communications are one of the major drivers of the cellular network evolution towards 5G systems. One of the key challenges is on how to provide reliability guarantees to each accessing device in a situation in which there is a massive number of almost-simultaneous arrivals from a large set of M2M devices. The existing solutions take a reactive approach in dealing with massive arrivals, such as non-selective barring when a massive arrival event occurs, which implies that the devices cannot get individual reliability guarantees. In this paper we propose a proactive approach, based on a standard operation of the cellular access. The access procedure is divided into two phases, an estimation phase and a serving phase. In the estimation phase the number of arrivals is estimated and this information is used to tune the amount of resources allocated in the serving phase. Our results show that the proactive approach is instrumental in delivering high access reliability to the M2M devices.
OMP2MPI: Automatic MPI code generation from OpenMP programs
Venue: arXiv cs.DC 2015
Year: 2015

In this paper, we present OMP2MPI a tool that generates automatically MPI source code from OpenMP. With this transformation the original program can be adapted to be able to exploit a larger number of processors by surpassing the limits of the node level on large HPC clusters. The transformation can also be useful to adapt the source code to execute in distributed memory many-cores with message passing support. In addition, the resulting MPI code can be used as an starting point that still can be further optimized by software engineers. The transformation process is focused on detecting OpenMP parallel loops and distributing them in a master/worker pattern. A set of micro-benchmarks have been used to verify the correctness of the the transformation and to measure the resulting performance. Surprisingly not only the automatically generated code is correct by construction, but also it often performs faster even when executed with MPI.
On the shape of the general error locator polynomial for cyclic codes
Venue: arXiv cs.IT 2015
Year: 2015

A general result on the explicit form of the general error locator polynomial for all cyclic codes is given, along with several results for infinite classes of cyclic codes with $t=2$ and $t=3$. From these, a theoretically justification of the sparsity of the general error locator polynomial is obtained for all cyclic codes with $t\leq 3$ and $n<63$, except for three cases where the sparsity is proved by a computer check. Moreover, we discuss some consequences of our results to the understanding of the complexity of bounded-distance decoding of cyclic codes.