OpenRaiser/Intern-Atlas huggingface dataset:
eAnt-Miner : An Ensemble Ant-Miner to Improve the ACO Classification
Venue: arXiv cs.NE 2014
Year: 2014

Ant Colony Optimization (ACO) has been applied in supervised learning in order to induce classification rules as well as decision trees, named Ant-Miners. Although these are competitive classifiers, the stability of these classifiers is an important concern that owes to their stochastic nature. In this paper, to address this issue, an acclaimed machine learning technique named, ensemble of classifiers is applied, where an ACO classifier is used as a base classifier to prepare the ensemble. The main trade-off is, the predictions in the new approach are determined by discovering a group of models as opposed to the single model classification. In essence, we prepare multiple models from the randomly replaced samples of training data from which, a unique model is prepared by aggregating the models to test the unseen data points. The main objective of this new approach is to increase the stability of the Ant-Miner results there by improving the performance of ACO classification. We found that the ensemble Ant-Miners significantly improved the stability by reducing the classification error on unseen data.
Quantum Edge Detection for Image Segmentation in Optical Environments
Venue: arXiv cs.CV 2014
Year: 2014

A quantum edge detector for image segmentation in optical environments is presented in this work. A Boolean version of the same detector is presented too. The quantum version of the new edge detector works with computational basis states, exclusively. This way, we can easily avoid the problem of quantum measurement retrieving the result of applying the new detector on the image. Besides, a new criterion and logic based on projections onto vertical axis of Bloch's Sphere exclusively are presented too. This approach will allow us: 1) a simpler development of logic quantum operations, where they will closer to those used in the classical logic operations, 2) building simple and robust classical-to-quantum and quantum-to-classical interfaces. Said so far is extended to quantum algorithms outside image processing too. In a special section on metric and simulations, a new metric based on the comparison between the classical and quantum versions algorithms for edge detection of images is presented. Notable differences between the results of classical and quantum versions of such algorithms (outside and inside of quantum computer, respectively) show the existence of implementation problems involved in the experiment, and that they have not been properly modeled for optical environments. However, although they are different, the quantum results are equally valid. The latter is clearly seen in the computer simulations
Performance Analysis of Cognitive Radio Systems with Imperfect Channel Sensing and Estimation
Venue: arXiv cs.IT 2014
Year: 2014

In cognitive radio systems, employing sensing-based spectrum access strategies, secondary users are required to perform channel sensing in order to detect the activities of primary users. In realistic scenarios, channel sensing occurs with possible errors due to miss-detections and false alarms. As another challenge, time-varying fading conditions in the channel between the secondary transmitter and the secondary receiver have to be learned via channel estimation. In this paper, performance of causal channel estimation methods in correlated cognitive radio channels under imperfect channel sensing results is analyzed, and achievable rates under both channel and sensing uncertainty are investigated. Initially, cognitive radio channel model with channel sensing error and channel estimation is described. Then, using pilot symbols, minimum mean square error (MMSE) and linear-MMSE (L-MMSE) estimation methods are employed at the secondary receiver to learn the channel fading coefficients. Expressions for the channel estimates and mean-squared errors (MSE) are determined, and their dependencies on channel sensing results, and pilot symbol period and energy are investigated. Since sensing uncertainty leads to uncertainty in the variance of the additive disturbance, channel estimation strategies and performance are interestingly shown to depend on the sensing reliability. It is further shown that the L-MMSE estimation method, which is in general suboptimal, performs very close to MMSE estimation. Furthermore, assuming the channel estimation errors and the interference introduced by the primary users as zero-mean and Gaussian distributed, achievable rate expressions of linear modulation schemes and Gaussian signaling are determined. Subsequently, the training period, and data and pilot symbol energy allocations are jointly optimized to maximize the achievable rates for both signaling schemes.
On Modeling the Costs of Censorship
Venue: arXiv cs.CR 2014
Year: 2014

We argue that the evaluation of censorship evasion tools should depend upon economic models of censorship. We illustrate our position with a simple model of the costs of censorship. We show how this model makes suggestions for how to evade censorship. In particular, from it, we develop evaluation criteria. We examine how our criteria compare to the traditional methods of evaluation employed in prior works.
A cirquent calculus system with clustering and ranking
Venue: arXiv cs.LO 2014
Year: 2014

Cirquent calculus is a new proof-theoretic and semantic approach introduced by G.Japaridze for the needs of his theory of computability logic. The earlier article "From formulas to cirquents in computability logic" by Japaridze generalized the concept of cirquents to the version with what are termed clusterng and ranking, and showed that, through cirquents with clustering and ranking, one can capture, refine and generalize the so called extended IF logic. Japaridze's treatment of extended IF logic, however, was purely semantical, and no deductive system was proposed. The present paper syntactically constructs a cirquent calculus system with clustering and ranking, sound and complete w.r.t. the propositional fragment of cirquent-based semantics. Such a system can be considered not only a conservative extension of classical propositional logic but also, when limited to cirquents with no more than 2 ranks, an axiomatization of purely propositional extended IF logic in its full generality.
Confluence for classical logic through the distinction between values and computations
Venue: arXiv cs.LO 2014
Year: 2014

We apply an idea originated in the theory of programming languages - monadic meta-language with a distinction between values and computations - in the design of a calculus of cut-elimination for classical logic. The cut-elimination calculus we obtain comprehends the call-by-name and call-by-value fragments of Curien-Herbelin's lambda-bar-mu-mu-tilde-calculus without losing confluence, and is based on a distinction of "modes" in the proof expressions and "mode" annotations in types. Modes resemble colors and polarities, but are quite different: we give meaning to them in terms of a monadic meta-language where the distinction between values and computations is fully explored. This meta-language is a refinement of the classical monadic language previously introduced by the authors, and is also developed in the paper.
Finite Block-length Analysis of the Incremental Redundancy HARQ
Venue: arXiv cs.IT 2014
Year: 2014

This letter studies the power-limited throughput of a communication system utilizing incremental redundancy (INR) hybrid automatic repeat request (HARQ). We use some recent results on the achievable rates of finite-length codes to analyze the system performance. With codewords of finite length, we derive closed-form expressions for the outage probabilities of INR HARQ and study the throughput in the cases with variable-length coding. Moreover, we evaluate the effect of feedback delay on the throughput and derive sufficient conditions for the usefulness of the HARQ protocols, in terms of power-limited throughput. The results show that, for a large range of HARQ feedback delays, the throughput is increased by finite-length coding INR HARQ, if the sub-codeword lengths are properly adapted.
Content-Aware User Clustering and Caching in Wireless Small Cell Networks
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, the problem of content-aware user clustering and content caching in wireless small cell networks is studied. In particular, a service delay minimization problem is formulated, aiming at optimally caching contents at the small cell base stations (SCBSs). To solve the optimization problem, we decouple it into two interrelated subproblems. First, a clustering algorithm is proposed grouping users with similar content popularity to associate similar users to the same SCBS, when possible. Second, a reinforcement learning algorithm is proposed to enable each SCBS to learn the popularity distribution of contents requested by its group of users and optimize its caching strategy accordingly. Simulation results show that by correlating the different popularity patterns of different users, the proposed scheme is able to minimize the service delay by 42% and 27%, while achieving a higher offloading gain of up to 280% and 90%, respectively, compared to random caching and unclustered learning schemes.
Word Sense Disambiguation using WSD specific Wordnet of Polysemy Words
Venue: arXiv cs.CL 2014
Year: 2014

This paper presents a new model of WordNet that is used to disambiguate the correct sense of polysemy word based on the clue words. The related words for each sense of a polysemy word as well as single sense word are referred to as the clue words. The conventional WordNet organizes nouns, verbs, adjectives and adverbs together into sets of synonyms called synsets each expressing a different concept. In contrast to the structure of WordNet, we developed a new model of WordNet that organizes the different senses of polysemy words as well as the single sense words based on the clue words. These clue words for each sense of a polysemy word as well as for single sense word are used to disambiguate the correct meaning of the polysemy word in the given context using knowledge based Word Sense Disambiguation (WSD) algorithms. The clue word can be a noun, verb, adjective or adverb.
A Generalized Reduced Linear Program for Markov Decision Processes
Venue: arXiv cs.SY 2014
Year: 2014

Markov decision processes (MDPs) with large number of states are of high practical interest. However, conventional algorithms to solve MDP are computationally infeasible in this scenario. Approximate dynamic programming (ADP) methods tackle this issue by computing approximate solutions. A widely applied ADP method is approximate linear program (ALP) which makes use of linear function approximation and offers theoretical performance guarantees. Nevertheless, the ALP is difficult to solve due to the presence of a large number of constraints and in practice, a reduced linear program (RLP) is solved instead. The RLP has a tractable number of constraints sampled from the original constraints of the ALP. Though the RLP is known to perform well in experiments the theoretical guarantees are available only for a specific RLP obtained under idealized assumptions. In this paper, we generalize the RLP to define a generalized reduced linear program (GRLP) which has a tractable number of constraints that are obtained as positive linear combinations of the original constraints of the ALP. The main contribution of this paper is the novel theoretical framework developed to obtain error bounds for any given GRLP. Central to our framework are two $\max$-norm contraction operators. Our result solves theoretically justifies linear approximation of constraints. We discuss the implication of our results in the contexts of ADP and reinforcement learning. We also demonstrate via an example in the domain of controlled queues that the experiments conform to the theory.
Finger-Stylus for Non Touch-Enable Systems
Venue: arXiv cs.HC 2014
Year: 2014

Since computer was invented, people are using many devices to interact with computer. Initially there were keyboard, mouse etc. but with the advancement of technology, new ways are being discovered that are quite usual and natural to the humans like stylus, touch-enable systems. In the current age of technology, user is expected to touch the machine interface to give input. Hand gesture is such a way to interact with machines where natural bare hand is used to communicate without touching machine interface. It gives a feeling to user that he is interacting in natural way to some human, not with traditional machines. This paper presents a technique where user needs not to touch the machine interface to draw on screen. Here hand finger draws shapes on monitor like stylus, without touching the monitor. This method can be used in many applications including games. The finger was used as an input device that acts like paint-brush or finger-stylus and is used to make shapes in front of the camera. Fingertip extraction and motion tracking were done in Matlab with real time constraints. This work is an early attempt to replace stylus with the natural finger without touching screen.
Semantifying Twitter: the influenceTracker ontology
Venue: arXiv cs.SI 2014
Year: 2014

In this paper, we propose an ontology schema towards semantification provision of Twitter social analytics. The ontology is deployed over a publicly available service that measures how influential a Twitter account is, by combining its social activity and interaction over Twittersphere. Apart from influential quantity and quality measures, the service provides a SPARQL endpoint where users can perform advance semantic queries through the RDFized Twitter entities (mentions, replies, hashtags, photos, URLs) over the semantic graph.
Spatial Sensing and Cognitive Radio Communication in the Presence of A $K$-User Interference Primary Network
Venue: arXiv cs.NI 2014
Year: 2014

We study the feasibility of cognitive radio (CR) communication in the presence of a $K$-user multi-input multi-output (MIMO) interference channel as the primary network. Assuming that the primary interference network has unused spatial degrees of freedom (DoFs), we first investigate the sufficient condition on the number of antennas at the secondary transmitter under which the secondary system can communicate while causing no interference to the primary receivers. We show that, to maximize the benefit, the secondary transmitter should have at least the same number of antennas as the spatial DoFs of the primary system. We then derive the secondary precoding and decoding matrices to have zero interference leakage into the primary network while the signal-to-interference plus noise ratio (SINR) at the secondary receiver is maximized. As the success of the secondary communication depends on the availability of unused DoFs, we then propose a fast sensing method based on the eigenvalue analysis of the received signal covariance matrix to determine the availability of unused DoFs or equivalently spatial holes. Since the proposed fast sensing method cannot identify the indices of inactive primary streams, we also provide a fine sensing method based on the generalized likelihood ratio test (GLRT) to decide the absence of individual primary streams. Simulation results show that the proposed CR sensing and transmission scheme can, in practice, provide a significant throughput while causing no interference to the primary receivers, and that the sensing detects the spatial holes of the primary network with high detection probability.
An Approach to Reducing Annotation Costs for BioNLP
Venue: arXiv cs.CL 2014
Year: 2014

There is a broad range of BioNLP tasks for which active learning (AL) can significantly reduce annotation costs and a specific AL algorithm we have developed is particularly effective in reducing annotation costs for these tasks. We have previously developed an AL algorithm called ClosestInitPA that works best with tasks that have the following characteristics: redundancy in training material, burdensome annotation costs, Support Vector Machines (SVMs) work well for the task, and imbalanced datasets (i.e. when set up as a binary classification problem, one class is substantially rarer than the other). Many BioNLP tasks have these characteristics and thus our AL algorithm is a natural approach to apply to BioNLP tasks.
Causal Erasure Channels
Venue: arXiv cs.IT 2014
Year: 2014

We consider the communication problem over binary causal adversarial erasure channels. Such a channel maps $n$ input bits to $n$ output symbols in $\{0,1,\wedge\}$, where $\wedge$ denotes erasure. The channel is causal if, for every $i$, the channel adversarially decides whether to erase the $i$th bit of its input based on inputs $1,...,i$, before it observes bits $i+1$ to $n$. Such a channel is $p$-bounded if it can erase at most a $p$ fraction of the input bits over the whole transmission duration. Causal channels provide a natural model for channels that obey basic physical restrictions but are otherwise unpredictable or highly variable. For a given erasure rate $p$, our goal is to understand the optimal rate (the capacity) at which a randomized (stochastic) encoder/decoder can transmit reliably across all causal $p$-bounded erasure channels. In this paper, we introduce the causal erasure model and provide new upper bounds and lower bounds on the achievable rate. Our bounds separate the achievable rate in the causal erasures setting from the rates achievable in two related models: random erasure channels (strictly weaker) and fully adversarial erasure channels (strictly stronger). Specifically, we show: - A strict separation between random and causal erasures for all constant erasure rates $p\in(0,1)$. - A strict separation between causal and fully adversarial erasures for $p\in(0,ϕ)$ where $ϕ\approx 0.348$. - For $p\in[ϕ,1/2)$, we show codes for causal erasures that have higher rate than the best known constructions for fully adversarial channels. Our results contrast with existing results on correcting causal bit-flip errors (as opposed to erasures) [Dey et. al 2008, 2009], [Haviv-Langberg 2011]. For the separations we provide, the analogous separations for bit-flip models are either not known at all or much weaker.
A New Course on Creativity in an Engineering Program: Foundations and Issues
Venue: arXiv cs.CY 2014
Year: 2014

The importance of innovation in the world's economy, now undeniable, draws great attention to the need to improve organizations' creative potential. In the last 60 years, hundreds of books have been written on the subject and hundreds of webpages display information on how to be more creative and achieve innovation. Several North American and European universities offer graduated programs in creativity. However, building an effective and validated creativity training program is not without challenges. Because of the nature of their work, engineers are often asked to be innovative. Without aiming for a degree in creativity, could future engineers benefit from training programs in creativity? This article presents the conceptual framework and pedagogical elements of a new course in creativity for engineering students.
Concurrent Tracking of Inliers and Outliers
Venue: arXiv cs.CV 2014
Year: 2014

In object tracking, outlier is one of primary factors which degrade performance of image-based tracking algorithms. In this respect, therefore, most of the existing methods simply discard detected outliers and pay little or no attention to employing them as an important source of information for motion estimation. We consider outliers as important as inliers for object tracking and propose a motion estimation algorithm based on concurrent tracking of inliers and outliers. Our tracker makes use of pyramidal implementation of the Lucas-Kanade tracker to estimate motion flows of inliers and outliers and final target motion is estimated robustly based on both of these information. Experimental results from challenging benchmark video sequences confirm enhanced tracking performance, showing highly stable target tracking under severe occlusion compared with state-of-the-art algorithms. The proposed algorithm runs at more than 100 frames per second even without using a hardware accelerator, which makes the proposed method more practical and portable.
Polynomial Template Generation using Sum-of-Squares Programming
Venue: arXiv cs.LO 2014
Year: 2014

Template abstract domains allow to express more interesting properties than classical abstract domains. However, template generation is a challenging problem when one uses template abstract domains for program analysis. In this paper, we relate template generation with the program properties that we want to prove. We focus on one-loop programs with nested conditional branches. We formally define the notion of well-representative template basis with respect to such programs and a given property. The definition relies on the fact that template abstract domains produce inductive invariants. We show that these invariants can be obtained by solving certain systems of functional inequalities. Then, such systems can be strengthened using a hierarchy of sum-of-squares (SOS) problems when we consider programs written in polynomial arithmetic. Each step of the SOS hierarchy can possibly provide a solution which in turn yields an invariant together with a certificate that the desired property holds. The interest of this approach is illustrated on nontrivial program examples in polynomial arithmetic.
Polarity detection movie reviews in hindi language
Venue: arXiv cs.CL 2014
Year: 2014

Nowadays peoples are actively involved in giving comments and reviews on social networking websites and other websites like shopping websites, news websites etc. large number of people everyday share their opinion on the web, results is a large number of user data is collected .users also find it trivial task to read all the reviews and then reached into the decision. It would be better if these reviews are classified into some category so that the user finds it easier to read. Opinion Mining or Sentiment Analysis is a natural language processing task that mines information from various text forms such as reviews, news, and blogs and classify them on the basis of their polarity as positive, negative or neutral. But, from the last few years, user content in Hindi language is also increasing at a rapid rate on the Web. So it is very important to perform opinion mining in Hindi language as well. In this paper a Hindi language opinion mining system is proposed. The system classifies the reviews as positive, negative and neutral for Hindi language. Negation is also handled in the proposed system. Experimental results using reviews of movies show the effectiveness of the system
The distributed Language Hello White Paper
Venue: arXiv cs.PL 2014
Year: 2014

Hello is a general-purpose, object-oriented, protocol-agnostic distributed programming language. This paper explains the ideas that guided design of Hello. It shows the spirit of Hello using two brief expressive programs and provides a summary of language features. In addition, it explores historical parallels between the binary programming of early computers and the distributed programming of modern networks.
Dispute Resolution Using Argumentation-Based Mediation
Venue: arXiv cs.AI 2014
Year: 2014

Mediation is a process, in which both parties agree to resolve their dispute by negotiating over alternative solutions presented by a mediator. In order to construct such solutions, mediation brings more information and knowledge, and, if possible, resources to the negotiation table. The contribution of this paper is the automated mediation machinery which does that. It presents an argumentation-based mediation approach that extends the logic-based approach to argumentation-based negotiation involving BDI agents. The paper describes the mediation algorithm. For comparison it illustrates the method with a case study used in an earlier work. It demonstrates how the computational mediator can deal with realistic situations in which the negotiating agents would otherwise fail due to lack of knowledge and/or resources.