OpenRaiser/Intern-Atlas huggingface dataset:
Merlin: A Language for Provisioning Network Resources
Venue: arXiv cs.NI 2014
Year: 2014

This paper presents Merlin, a new framework for managing resources in software-defined networks. With Merlin, administrators express high-level policies using programs in a declarative language. The language includes logical predicates to identify sets of packets, regular expressions to encode forwarding paths, and arithmetic formulas to specify bandwidth constraints. The Merlin compiler uses a combination of advanced techniques to translate these policies into code that can be executed on network elements including a constraint solver that allocates bandwidth using parameterizable heuristics. To facilitate dynamic adaptation, Merlin provides mechanisms for delegating control of sub-policies and for verifying that modifications made to sub-policies do not violate global constraints. Experiments demonstrate the expressiveness and scalability of Merlin on real-world topologies and applications. Overall, Merlin simplifies network administration by providing high-level abstractions for specifying network policies and scalable infrastructure for enforcing them.
Improving Performance of Self-Organising Maps with Distance Metric Learning Method
Venue: arXiv cs.LG 2014
Year: 2014

Self-Organising Maps (SOM) are Artificial Neural Networks used in Pattern Recognition tasks. Their major advantage over other architectures is human readability of a model. However, they often gain poorer accuracy. Mostly used metric in SOM is the Euclidean distance, which is not the best approach to some problems. In this paper, we study an impact of the metric change on the SOM's performance in classification problems. In order to change the metric of the SOM we applied a distance metric learning method, so-called 'Large Margin Nearest Neighbour'. It computes the Mahalanobis matrix, which assures small distance between nearest neighbour points from the same class and separation of points belonging to different classes by large margin. Results are presented on several real data sets, containing for example recognition of written digits, spoken letters or faces.
On Quantum Codes Obtained From Cyclic Codes Over F_2+vF_2+v^2F_2
Venue: arXiv cs.IT 2014
Year: 2014

A new Gray map which is both an isometry and a weight preserving map from R=F_2+vF_2+v^2F_2 to (F_2)^3 is defined. A construction for quantum error correcting codes from cyclic codes over finite ring R=F_2+vF_2+v^2F_2, v^3=v is given. The parameters of quantum codes which are obtained from cyclic codes over R are determined.
Differential Dual-Hop Relaying under User Mobility
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies dual-hop amplify-and-forward relaying system employing differential encoding and decoding over time-varying Rayleigh fading channels. First, the convectional "two-symbol" differential detection (CDD) is theoretically analysed in terms of the bit-error-rate (BER). The obtained analysis clearly shows that performance of two-symbol differential detection severely degrades in fast-fading channels and reaches an irreducible error floor at high signal-to-noise ratio region. To overcome the error floor experienced with fast-fading, a practical suboptimal "multiple-symbol" detection (MSD) is designed and its performance is theoretically analysed. The analysis of CDD and MSD are verified and illustrated with simulation results under different fading scenarios. Specifically, the obtained results show that the proposed MSD can significantly improve the system performance in fast-fading channels.
Curved Trajectory Detection : A Novel Neurocognitive Perception Approach for Autonomous Smart Robots
Venue: arXiv cs.RO 2014
Year: 2014

Braitenberg vehicles could be mentioned as the seminal elements for cognitive studies in robotics fields especially neurorobotics to invent more smart robots. Motion detection of dynamic objects could be taken as one of the most inspiring abilities into account which can lead to evolve more intelligent Braitenberg vehicles. In this paper, a new neuronal circuit is established in order to detect curved movements of the objects wandering around Braitenberg vehicles. Modular structure of the novel circuit provides the opportunity to expand the model into huge sensory-biosystems. Furthermore, robust performance of the circuit against epileptic seizures is beholden to simultaneous utilization of excitatory and inhibitory stimuli in the circuit construction. Also, straight movements, as special case of curved movements could be tracked. PIONEER, with due attention to its suitable neurosensors, is used as a Braitenberg vehicle for empirical evaluations. Simulated results and practical experiments are applied to this vehicle in order to verify new achievements of the curved trajectory detector.
Fuzzy Model on Human Emotions Recognition
Venue: arXiv cs.AI 2014
Year: 2014

This paper discusses a fuzzy model for multi-level human emotions recognition by computer systems through keyboard keystrokes, mouse and touchscreen interactions. This model can also be used to detect the other possible emotions at the time of recognition. Accuracy measurements of human emotions by the fuzzy model are discussed through two methods; the first is accuracy analysis and the second is false positive rate analysis. This fuzzy model detects more emotions, but on the other hand, for some of emotions, a lower accuracy was obtained with the comparison with the non-fuzzy human emotions detection methods. This system was trained and tested by Support Vector Machine (SVM) to recognize the users' emotions. Overall, this model represents a closer similarity between human brain detection of emotions and computer systems.
Joint Beamforming Design for Multi-User Wireless Information and Power Transfer
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we propose a joint beamforming algorithm for a multiuser wireless information and power transfer (MU-WIPT) system that is compatible with the conventional multiuser multiple input multiple output (MU-MIMO) system. The proposed joint beamforming vectors are initialized using the well established MU-MIMO zero-forcing beamforming (ZFBF) and are further updated to maximize the total harvested energy of energy harvesting (EH) users and guarantee the signal to interference plus noise ratio (SINR) constraints of the co-scheduled information decoding (ID) users. When ID and EH users are simultaneously served by joint beamforming vectors, the harvested energy can be increased at the cost of an SINR loss for ID users. To characterize the SINR loss, the target SINR ratio,u, is introduced as the target SINR (i.e., SINR constraint) normalized by the received SINR achievable with ZFBF. Based on that ratio, the sum rate and harvested energy obtained from the proposed algorithm are analyzed under perfect/imperfect channel state information at the transmitter (CSIT). Through simulations and numerical results, we validate the derived analyses and demonstrate the EH and ID performance compared to both state of the art and conventional schemes.
Energy Efficiency and Spectral Efficiency Tradeoff in Device-to-Device (D2D) Communications
Venue: arXiv cs.GT 2014
Year: 2014

In this letter, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device (D2D) communications underlaying cellular networks with uplink channel reuse. The resource allocation problem is modeled as a noncooperative game, in which each user equipment (UE) is self-interested and wants to maximize its own EE. Given the SE requirement and maximum transmission power constraints, a distributed energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. The relationships between the EE and SE tradeoff of the proposed algorithm and system parameters are analyzed and verified through computer simulations.
A Statistical Modelling and Analysis of PHEVs' Power Demand in Smart Grids
Venue: arXiv cs.CE 2014
Year: 2014

Electric vehicles (EVs) and particularly plug-in hybrid electric vehicles (PHEVs) are foreseen to become popular in the near future. Not only are they much more environmentally friendly than conventional internal combustion engine (ICE) vehicles, their fuel can also be catered from diverse energy sources and resources. However, they add significant load on the power grid as they become widespread. The characteristics of this extra load follow the patterns of people's driving behaviours. In particular, random parameters such as arrival time and driven distance of the vehicles determine their expected demand profile from the power grid. In this paper, we first present a model for uncoordinated charging power demand of PHEVs based on a stochastic process and accordingly we characterize the EV's expected daily power demand profile. Next, we adopt different distributions for the EV's charging time following some available empirical research data in the literature. Simulation results show that the EV's expected daily power demand profiles obtained under the uniform, Gaussian with positive support and Rician distributions for charging time are identical when the first and second order statistics of these distributions are the same. This gives us useful insights into the long-term planning for upgrading power systems' infrastructure to accommodate PHEVs. In addition, the results from this modelling can be incorporated into designing demand response (DR) algorithms and evaluating the available DR techniques more accurately.
Les noms propres se traduisent-ils ? Étude d'un corpus multilingue
Venue: arXiv cs.CL 2014
Year: 2014

In this paper, we tackle the problem of the translation of proper names. We introduce our hypothesis according to which proper names can be translated more often than most people seem to think. Then, we describe the construction of a parallel multilingual corpus used to illustrate our point. We eventually evaluate both the advantages and limits of this corpus in our study.
Estimating Traffic and Anomaly Maps via Network Tomography
Venue: arXiv cs.NI 2014
Year: 2014

Mapping origin-destination (OD) network traffic is pivotal for network management and proactive security tasks. However, lack of sufficient flow-level measurements as well as potential anomalies pose major challenges towards this goal. Leveraging the spatiotemporal correlation of nominal traffic, and the sparse nature of anomalies, this paper brings forth a novel framework to map out nominal and anomalous traffic, which treats jointly important network monitoring tasks including traffic estimation, anomaly detection, and traffic interpolation. To this end, a convex program is first formulated with nuclear and $\ell_1$-norm regularization to effect sparsity and low rank for the nominal and anomalous traffic with only the link counts and a {\it small} subset of OD-flow counts. Analysis and simulations confirm that the proposed estimator can {\em exactly} recover sufficiently low-dimensional nominal traffic and sporadic anomalies so long as the routing paths are sufficiently "spread-out" across the network, and an adequate amount of flow counts are randomly sampled. The results offer valuable insights about data acquisition strategies and network scenaria giving rise to accurate traffic estimation. For practical networks where the aforementioned conditions are possibly violated, the inherent spatiotemporal traffic patterns are taken into account by adopting a Bayesian approach along with a bilinear characterization of the nuclear and $\ell_1$ norms. The resultant nonconvex program involves quadratic regularizers with correlation matrices, learned systematically from (cyclo)stationary historical data. Alternating-minimization based algorithms with provable convergence are also developed to procure the estimates. Insightful tests with synthetic and real Internet data corroborate the effectiveness of the novel schemes.
Future Influence Ranking of Scientific Literature
Venue: arXiv cs.SI 2014
Year: 2014

Researchers or students entering a emerging research area are particularly interested in what newly published papers will be most cited and which young researchers will become influential in the future, so that they can catch the most recent advances and find valuable research directions. However, predicting the future importance of scientific articles and authors is challenging due to the dynamic nature of literature networks and evolving research topics. Different from most previous studies aiming to rank the current importance of literatures and authors, we focus on \emph{ranking the future popularity of new publications and young researchers} by proposing a unified ranking model to combine various available information. Specifically, we first propose to extract two kinds of text features, words and words co-occurrence to characterize innovative papers and authors. Then, instead of using static and un-weighted graphs, we construct time-aware weighted graphs to distinguish the various importance of links established at different time. Finally, by leveraging both the constructed text features and graphs, we propose a mutual reinforcement ranking framework called \emph{MRFRank} to rank the future importance of papers and authors simultaneously. Experimental results on the ArnetMiner dataset show that the proposed approach significantly outperforms the baselines on the metric \emph{recommendation intensity}.
Sensitivity Analysis of Minimum Spanning Trees in Sub-Inverse-Ackermann Time
Venue: arXiv cs.DS 2014
Year: 2014

We present a deterministic algorithm for computing the sensitivity of a minimum spanning tree (MST) or shortest path tree in $O(m\logα(m,n))$ time, where $α$ is the inverse-Ackermann function. This improves upon a long standing bound of $O(mα(m,n))$ established by Tarjan. Our algorithms are based on an efficient split-findmin data structure, which maintains a collection of sequences of weighted elements that may be split into smaller subsequences. As far as we are aware, our split-findmin algorithm is the first with superlinear but sub-inverse-Ackermann complexity. We also give a reduction from MST sensitivity to the MST problem itself. Together with the randomized linear time MST algorithm of Karger, Klein, and Tarjan, this gives another randomized linear time MST sensitivity algoritm.
The Convex Configurations of "Sei Shonagon Chie no Ita" and Other Dissection Puzzles
Venue: arXiv cs.CG 2014
Year: 2014

The tangram and Sei Shonagon Chie no Ita are popular dissection puzzles consisting of seven pieces. Each puzzle can be formed by identifying edges from sixteen identical right isosceles triangles. It is known that the tangram can form 13 convex polygons. We show that Sei Shonagon Chie no Ita can form 16 convex polygons, propose a new puzzle that can form 19, no 7 piece puzzle can form 20, and 11 pieces are necessary and sufficient to form all 20 polygons formable by 16 identical isosceles right triangles. Finally, we examine the number of convex polygons formable by different quantities of these triangles.
Regression-Based Image Alignment for General Object Categories
Venue: arXiv cs.CV 2014
Year: 2014

Gradient-descent methods have exhibited fast and reliable performance for image alignment in the facial domain, but have largely been ignored by the broader vision community. They require the image function be smooth and (numerically) differentiable -- properties that hold for pixel-based representations obeying natural image statistics, but not for more general classes of non-linear feature transforms. We show that transforms such as Dense SIFT can be incorporated into a Lucas Kanade alignment framework by predicting descent directions via regression. This enables robust matching of instances from general object categories whilst maintaining desirable properties of Lucas Kanade such as the capacity to handle high-dimensional warp parametrizations and a fast rate of convergence. We present alignment results on a number of objects from ImageNet, and an extension of the method to unsupervised joint alignment of objects from a corpus of images.
Inter-Rater Agreement Study on Readability Assessment in Bengali
Venue: arXiv cs.CL 2014
Year: 2014

An inter-rater agreement study is performed for readability assessment in Bengali. A 1-7 rating scale was used to indicate different levels of readability. We obtained moderate to fair agreement among seven independent annotators on 30 text passages written by four eminent Bengali authors. As a by product of our study, we obtained a readability-annotated ground truth dataset in Bengali. .
Performance Analysis of VOIP Traffic Over Integrating Wireless LAN and WAN Using Different Codecs
Venue: arXiv cs.NI 2014
Year: 2014

A simulation model is presented to analyze and evaluate the performance of VoIP based integrated wireless LAN/WAN with taking into account various voice encoding schemes. The network model was simulated using OPNET Modeler software. Different parameters that indicate the QoS like MOS, jitter, end to end delay, traffic send and traffic received are calculated and analyzed in Wireless LAN/WAN scenarios. Depending on this evaluation, Selection codecs G.729A consider the best choice for VoIP.
On the Enumeration of Minimal Dominating Sets and Related Notions
Venue: arXiv cs.DM 2014
Year: 2014

A dominating set $D$ in a graph is a subset of its vertex set such that each vertex is either in $D$ or has a neighbour in $D$. In this paper, we are interested in the enumeration of (inclusion-wise) minimal dominating sets in graphs, called the Dom-Enum problem. It is well known that this problem can be polynomially reduced to the Trans-Enum problem in hypergraphs, i.e., the problem of enumerating all minimal transversals in a hypergraph. Firstly we show that the Trans-Enum problem can be polynomially reduced to the Dom-Enum problem. As a consequence there exists an output-polynomial time algorithm for the Trans-Enum problem if and only if there exists one for the Dom-Enum problem. Secondly, we study the Dom-Enum problem in some graph classes. We give an output-polynomial time algorithm for the Dom-Enum problem in split graphs, and introduce the completion of a graph to obtain an output-polynomial time algorithm for the Dom-Enum problem in $P_6$-free chordal graphs, a proper superclass of split graphs. Finally, we investigate the complexity of the enumeration of (inclusion-wise) minimal connected dominating sets and minimal total dominating sets of graphs. We show that there exists an output-polynomial time algorithm for the Dom-Enum problem (or equivalently Trans-Enum problem) if and only if there exists one for the following enumeration problems: minimal total dominating sets, minimal total dominating sets in split graphs, minimal connected dominating sets in split graphs, minimal dominating sets in co-bipartite graphs.
MIMTool: A Tool for Drawing Molecular Interaction Maps
Venue: arXiv cs.CE 2014
Year: 2014

Background: To understand protein function, it is important to study protein- protein interaction networks. These networks can be represented in network diagrams called protein interaction maps that can lead to better understanding by visualization. We address the problem of drawing of protein interactions in Kohn's Molecular Interaction Map (MIM) notation. Even though there are some existing tools for graphical visualization of protein interactions in general, there is no tool that can draw protein interactions with MIM notation with full support. Results: MIMTool was developed for drawing protein interaction maps in Kohn's MIM notation. MIMTool was developed using the Qt toolkit libraries and introduces several unique features such as full interactivity, object dragging, ability to export files in MIMML, SBML and line drawing with automatic bending and crossover minimization, which are not available in other diagram editors. MIMTool also has a unique orthogonal edge drawing method that is both easy and more flexible than other orthogonal drawing methods present in other interaction drawing tools. Conclusions: MIMTool facilitates faster drawing, updating and exchanging of MIMs. Among its several features, it also includes a semi-automatic drawing algorithm that makes use of shortest path algorithm for constructing lines with small number of bends and crossings. MIMTool contributes a much needed software tool that was missing and will facilitate wider adoption of Kohn's MIM notation.
inPHAP: Interactive visualization of genotype and phased haplotype data
Venue: arXiv cs.CE 2014
Year: 2014

Background: To understand individual genomes it is necessary to look at the variations that lead to changes in phenotype and possibly to disease. However, genotype information alone is often not sufficient and additional knowledge regarding the phase of the variation is needed to make correct interpretations. Interactive visualizations, that allow the user to explore the data in various ways, can be of great assistance in the process of making well informed decisions. But, currently there is a lack for visualizations that are able to deal with phased haplotype data. Results: We present inPHAP, an interactive visualization tool for genotype and phased haplotype data. inPHAP features a variety of interaction possibilities such as zooming, sorting, filtering and aggregation of rows in order to explore patterns hidden in large genetic data sets. As a proof of concept, we apply inPHAP to the phased haplotype data set of Phase 1 of the 1000 Genomes Project. Thereby, inPHAP's ability to show genetic variations on the population as well as on the individuals level is demonstrated for several disease related loci. Conclusions: As of today, inPHAP is the only visual analytical tool that allows the user to explore unphased and phased haplotype data interactively. Due to its highly scalable design, inPHAP can be applied to large datasets with up to 100 GB of data, enabling users to visualize even large scale input data. inPHAP closes the gap between common visualization tools for unphased genotype data and introduces several new features, such as the visualization of phased data.
eXamine: Exploring annotated modules in networks
Venue: arXiv cs.CE 2014
Year: 2014

Background: Biological networks have a growing importance for the interpretation of high-throughput omics data. Integrative network analysis makes use of statistical and combinatorial methods to extract smaller subnetwork modules, and performs enrichment analysis to annotate the modules with ontology terms or other available knowledge. This process results in an annotated module, which retains the original network structure and includes enrichment information as a set system. A major bottleneck is a lack of tools that allow exploring both network structure of extracted modules and its annotations. Results: Thispaperpresentsavisualanalysisapproachthattargetssmallmoduleswithmanyset-based annotations, and which displays the annotations as contours on top of a node-link diagram. We introduce an extension of self-organizing maps to lay out nodes, links, and contours in a unified way. An implementation of this approach is freely available as the Cytoscape app eXamine. Conclusions: eXamine accurately conveys small and annotated modules consisting of several dozens of proteins and annotations. We demonstrate that eXamine facilitates the interpretation of integrative network analysis results in a guided case study. This study has resulted in a novel biological insight regarding the virally-encoded G-protein coupled receptor US28.