OpenRaiser/Intern-Atlas huggingface dataset:
Ang Social Network sa Facebook ng mga Taga-Batangas at ng mga Taga-Laguna: Isang Paghahambing
Venue: arXiv cs.SI 2015
Year: 2015

Online social networking (OSN) has become of great influence to Filipinos, where Facebook, Twitter, LinkedIn, Google+, and Instagram are among the popular ones. Their popularity, coupled with their intuitive and interactive use, allow one's personal information such as gender, age, address, relationship status, and list of friends to become publicly available. The accessibility of information from these sites allow, with the aid of computers, for the study of a wide population's characteristics even in a provincial scale. Aside from being neighbouring locales, the respective residents of Laguna and Batangas both derive their livelihoods from two lakes, Laguna de Bay and Taal Lake. Both residents experience similar problems, such as that, among many others, of fish kill. The goal of this research is to find out similarities in their respective online populations, particularly that of Facebook's. With the use of computational dynamic social network analysis (CDSNA), we found out that the two communities are similar, among others, as follows: o Both populations are dominated by single young female o Homophily was observed when choosing a friend in terms of age (i.e., friendships were created more often between people whose ages do not differ by at most five years); and o Heterophily was observed when choosing friends in terms of gender (i.e., more friendships were created between a male and a female than between both people of the same gender). This paper also presents the differences in the structure of the two social networks, such as degrees of separation and preferential attachment.
Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices
Venue: arXiv cs.CV 2015
Year: 2015

Data encoded as symmetric positive definite (SPD) matrices frequently arise in many areas of computer vision and machine learning. While these matrices form an open subset of the Euclidean space of symmetric matrices, viewing them through the lens of non-Euclidean Riemannian geometry often turns out to be better suited in capturing several desirable data properties. However, formulating classical machine learning algorithms within such a geometry is often non-trivial and computationally expensive. Inspired by the great success of dictionary learning and sparse coding for vector-valued data, our goal in this paper is to represent data in the form of SPD matrices as sparse conic combinations of SPD atoms from a learned dictionary via a Riemannian geometric approach. To that end, we formulate a novel Riemannian optimization objective for dictionary learning and sparse coding in which the representation loss is characterized via the affine invariant Riemannian metric. We also present a computationally simple algorithm for optimizing our model. Experiments on several computer vision datasets demonstrate superior classification and retrieval performance using our approach when compared to sparse coding via alternative non-Riemannian formulations.
A horizontally-scalable multiprocessing platform based on Node.js
Venue: arXiv cs.DC 2015
Year: 2015

This paper presents a scalable web-based platform called Node Scala which allows to split and handle requests on a parallel distributed system according to pre-defined use cases. We applied this platform to a client application that visualizes climate data stored in a NoSQL database MongoDB. The design of Node Scala leads to efficient usage of available computing resources in addition to allowing the system to scale simply by adding new workers. Performance evaluation of Node Scala demonstrated a gain of up to 74 % compared to the state-of-the-art techniques.
On the Connectedness of Clash-free Timetables
Venue: arXiv cs.DM 2015
Year: 2015

We investigate the connectedness of clash-free timetables with respect to the Kempe-exchange operation. This investigation is related to the connectedness of the search space of timetabling problem instances, which is a desirable property, for example for two-step algorithms using the Kempe-exchange during the optimization step. The theoretical framework for our investigations is based on the study of reconfiguration graphs, which model the search space of timetabling problems. We contribute to this framework by including timeslot availability requirements in the analysis and we derive improved conditions for the connectedness of clash-free timetables in this setting. We apply the theoretical insights to establish the connectedness of clash-free timetables for a number of benchmark instances.
A Closed-Form Formulation of HRBF-Based Surface Reconstruction
Venue: arXiv cs.GR 2015
Year: 2015

The Hermite radial basis functions (HRBFs) implicits have been used to reconstruct surfaces from scattered Hermite data points. In this work, we propose a closed-form formulation to construct HRBF-based implicits by a quasi-solution approximating the exact solution. A scheme is developed to automatically adjust the support sizes of basis functions to hold the error bound of a quasi-solution. Our method can generate an implicit function from positions and normals of scattered points without taking any global operation. Working together with an adaptive sampling algorithm, the HRBF-based implicits can also reconstruct surfaces from point clouds with non-uniformity and noises. Robust and efficient reconstruction has been observed in our experimental tests on real data captured from a variety of scenes.
First-order integer programming for MAP problems
Venue: arXiv cs.AI 2015
Year: 2015

Finding the most probable (MAP) model in SRL frameworks such as Markov logic and Problog can, in principle, be solved by encoding the problem as a `grounded-out' mixed integer program (MIP). However, useful first-order structure disappears in this process motivating the development of first-order MIP approaches. Here we present mfoilp, one such approach. Since the syntax and semantics of mfoilp is essentially the same as existing approaches we focus here mainly on implementation and algorithmic issues. We start with the (conceptually) simple problem of using a logic program to generate a MIP instance before considering more ambitious exploitation of first-order representations.
Genoogle: an indexed and parallelized search engine for similar DNA sequences
Venue: arXiv cs.DC 2015
Year: 2015

The search for similar genetic sequences is one of the main bioinformatics tasks. The genetic sequences data banks are growing exponentially and the searching techniques that use linear time are not capable to do the search in the required time anymore. Another problem is that the clock speed of the modern processors are not growing as it did before, instead, the processing capacity is growing with the addiction of more processing cores and the techniques which does not use parallel computing does not have benefits from these extra cores. This work aims to use data indexing techniques to reduce the searching process computation cost united with the parallelization of the searching techniques to use the computational capacity of the multi core processors. To verify the viability of using these two techniques simultaneously, a software which uses parallelization techniques with inverted indexes was developed. Experiments were executed to analyze the performance gain when parallelism is utilized, the search time gain, and also the quality of the results when it compared with others searching tools. The results of these experiments were promising, the parallelism gain overcame the expected speedup, the searching time was 20 times faster than the parallelized NCBI BLAST, and the searching results showed a good quality when compared with this tool. The software source code is available at https://github.com/felipealbrecht/Genoogle .
On cyclic self-orthogonal codes over Zpm
Venue: arXiv cs.IT 2015
Year: 2015

The purpose of this paper is to study the cyclic self orthogonal codes over $\mathbb{Z}_{p^m}$. After providing the generator polynomial of cyclic self orthogonal codes over $\mathbb{Z}_{p^m}$, we give the necessary and sufficient condition for the existence of non-trivial self orthogonal codes over $\mathbb{Z}_{p^m}$ . We have also provided the number of such codes of length $n$ over $\mathbb{Z}_{p^m}$ for any $ (p,n) = 1 $.
A new boosting algorithm based on dual averaging scheme
Venue: arXiv cs.LG 2015
Year: 2015

The fields of machine learning and mathematical optimization increasingly intertwined. The special topic on supervised learning and convex optimization examines this interplay. The training part of most supervised learning algorithms can usually be reduced to an optimization problem that minimizes a loss between model predictions and training data. While most optimization techniques focus on accuracy and speed of convergence, the qualities of good optimization algorithm from the machine learning perspective can be quite different since machine learning is more than fitting the data. Better optimization algorithms that minimize the training loss can possibly give very poor generalization performance. In this paper, we examine a particular kind of machine learning algorithm, boosting, whose training process can be viewed as functional coordinate descent on the exponential loss. We study the relation between optimization techniques and machine learning by implementing a new boosting algorithm. DABoost, based on dual-averaging scheme and study its generalization performance. We show that DABoost, although slower in reducing the training error, in general enjoys a better generalization error than AdaBoost.
Face Alignment Assisted by Head Pose Estimation
Venue: arXiv cs.CV 2015
Year: 2015

In this paper we propose a supervised initialization scheme for cascaded face alignment based on explicit head pose estimation. We first investigate the failure cases of most state of the art face alignment approaches and observe that these failures often share one common global property, i.e. the head pose variation is usually large. Inspired by this, we propose a deep convolutional network model for reliable and accurate head pose estimation. Instead of using a mean face shape, or randomly selected shapes for cascaded face alignment initialisation, we propose two schemes for generating initialisation: the first one relies on projecting a mean 3D face shape (represented by 3D facial landmarks) onto 2D image under the estimated head pose; the second one searches nearest neighbour shapes from the training set according to head pose distance. By doing so, the initialisation gets closer to the actual shape, which enhances the possibility of convergence and in turn improves the face alignment performance. We demonstrate the proposed method on the benchmark 300W dataset and show very competitive performance in both head pose estimation and face alignment.
Optimal Multi-Robot Path Planning on Graphs: Structure and Computational Complexity
Venue: arXiv cs.RO 2015
Year: 2015

We study the problem of optimal multi-robot path planning on graphs (MPP) over four distinct minimization objectives: the total arrival time, the makespan (last arrival time), the total distance, and the maximum (single-robot traveled) distance. On the structure side, we show that each pair of these four objectives induces a Pareto front and cannot always be optimized simultaneously. Then, through reductions from 3-SAT, we further establish that computation over each objective is an NP-hard task, providing evidence that solving MPP optimally is generally intractable. Nevertheless, in a related paper, we design complete algorithms and efficient heuristics for optimizing all four objectives, capable of solving MPP optimally or near-optimally for hundreds of robots in challenging setups.
Evaluation of the citation matching algorithms of CWTS and iFQ in comparison to Web of Science
Venue: arXiv cs.DL 2015
Year: 2015

The results of bibliometric studies provided by bibliometric research groups, e.g. the Centre for Science and Technology Studies (CWTS) and the Institute for Research Information and Quality Assurance (iFQ), are often used in the process of research assessment. Their databases use Web of Science (WoS) citation data, which they match according to their own matching algorithms - in the case of CWTS for standard usage in their studies and in the case of iFQ on an experimental basis. Since the problem of non-matched citations in WoS persists because of inaccuracies in the references or inaccuracies introduced in the data extraction process, it is important to ascertain how well these inaccuracies are rectified in these citation matching algorithms. This paper evaluates the algorithms of CWTS and iFQ in comparison to WoS in a quantitative and a qualitative analysis. The analysis builds upon the methodology and the manually verified corpus of a previous study. The algorithm of CWTS performs best, closely followed by that of iFQ. The WoS algorithm still performs quite well (F1 score: 96.41 percent), but shows deficits in matching references containing inaccuracies. An additional problem is posed by incorrectly provided cited reference information in source articles by WoS.
Deciding Circular-Arc Graph Isomorphism in Parameterized Logspace
Venue: arXiv cs.DS 2015
Year: 2015

We compute a canonical circular-arc representation for a given circular-arc (CA) graph which implies solving the isomorphism and recognition problem for this class. To accomplish this we split the class of CA graphs into uniform and non-uniform ones and employ a generalized version of the argument given by Köbler et al (2013) that has been used to show that the subclass of Helly CA graphs can be canonized in logspace. For uniform CA graphs our approach works in logspace and in addition to that Helly CA graphs are a strict subset of uniform CA graphs. Thus our result is a generalization of the canonization result for Helly CA graphs. In the non-uniform case a specific set of ambiguous vertices arises. By choosing the parameter to be the cardinality of this set the obstacle can be solved by brute force. This leads to an O(k + log n) space algorithm to compute a canonical representation for non-uniform and therefore all CA graphs.
Ordered Decompositional DAG Kernels Enhancements
Venue: arXiv cs.LG 2015
Year: 2015

In this paper, we show how the Ordered Decomposition DAGs (ODD) kernel framework, a framework that allows the definition of graph kernels from tree kernels, allows to easily define new state-of-the-art graph kernels. Here we consider a fast graph kernel based on the Subtree kernel (ST), and we propose various enhancements to increase its expressiveness. The proposed DAG kernel has the same worst-case complexity as the one based on ST, but an improved expressivity due to an augmented set of features. Moreover, we propose a novel weighting scheme for the features, which can be applied to other kernels of the ODD framework. These improvements allow the proposed kernels to improve on the classification performances of the ST-based kernel for several real-world datasets, reaching state-of-the-art performances.
What are essential concepts about networks?
Venue: arXiv cs.SI 2015
Year: 2015

Networks have become increasingly relevant to everyday life as human society has become increasingly connected. Attaining a basic understanding of networks has thus become a necessary form of literacy for people (and for youths in particular). At the NetSci 2014 conference, we initiated a year-long process to develop an educational resource that concisely summarizes essential concepts about networks that can be used by anyone of school age or older. The process involved several brainstorming sessions on one key question: "What should every person living in the 21st century know about networks by the time he/she finishes secondary education?" Different sessions reached diverse participants, which included professional researchers in network science, educators, and high-school students. The generated ideas were connected by the students to construct a concept network. We examined community structure in the concept network to group ideas into a set of important themes, which we refined through discussion into seven essential concepts. The students played a major role in this development process by providing insights and perspectives that were often unrecognized by researchers and educators. The final result, "Network Literacy: Essential Concepts and Core Ideas", is now available as a booklet in several different languages from http://tinyurl.com/networkliteracy .
Selfish Routing on Dynamic Flows
Venue: arXiv cs.GT 2015
Year: 2015

Selfish routing on dynamic flows over time is used to model scenarios that vary with time in which individual agents act in their best interest. In this paper we provide a survey of a particular dynamic model, the deterministic queuing model, and discuss how the model can be adjusted and applied to different real-life scenarios. We then examine how these adjustments affect the computability, optimality, and existence of selfish routings.
Twist your logic with TouIST
Venue: arXiv cs.CY 2015
Year: 2015

SAT provers are powerful tools for solving real-sized logic problems, but using them requires solid programming knowledge and may be seen w.r.t.\ logic like assembly language w.r.t.\ programming. Something like a high level language was missing to ease various users to take benefit of these tools. {\sc \texttt {TouIST}}\ aims at filling this gap. It is devoted to propositional logic and its main features are 1) to offer a high-level logic langage for expressing succintly complex formulas (e.g.\ formulas describing Sudoku rules, planification problems,\ldots) and 2) to find models to these formulas by using the adequate powerful prover, which the user has no need to know about. It consists in a friendly interface that offers several syntactic facilities and which is connected with some sufficiently powerful provers allowing to automatically solve big instances of difficult problems (such as time-tables or Sudokus). It can interact with various provers: pure SAT solver but also SMT provers (SAT modulo theories - like linear theory of reals, etc) and thus may also be used by beginners for experiencing with pure propositional problems up to graduate students or even researchers for solving planification problems involving big sets of fluents and numerical constraints on them.
Presentation of Classical Propositional Tableaux on Program Design Premises
Venue: arXiv cs.CY 2015
Year: 2015

We propose a presentation of classical propositional tableaux elaborated by application of methods that are noteworthy in program design, namely program derivation with separation of concerns. We start by deriving from a straightforward specification an algorithm given as a set of recursive equations for computing all models of a finite set of formulae. Thereafter we discuss the employment of data structures, mainly with regard to an easily traceable manual execution of the algorithm. This leads to the kinds of trees given usually as constituting the tableaux. The whole development strives at avoiding gaps, both of logical and motivational nature.
RAESON: A Tool for Reasoning Tasks Driven by Interactive Visualization of Logical Structure
Venue: arXiv cs.CY 2015
Year: 2015

The paper presents a software tool for analysis and interactive engagement in various logical reasoning tasks. A first feature of the program consists in providing an interface for working with logic-specific repositories of formal knowledge. A second feature provides the means to intuitively visualize and interactively generate the underlying logical structure that propels customary logical reasoning tasks. Starting from this we argue that both aspects have didactic potential and can be integrated in teaching activities to provide an engaging learning experience.
Teaching natural deduction in the right order with Natural Deduction Planner
Venue: arXiv cs.CY 2015
Year: 2015

We describe a strategy-based approach to teaching natural deduction using a notation that emphasises the order in which deductions are constructed, together with a {\LaTeX} package and Java app to aid in the production of teaching resources and classroom demonstrations. Our approach is aimed at students with little exposure to mathematical method and has been developed while teaching undergraduate classes for philosophy students over the last ten years.
Dynamic Sleep Control in Green Relay-Assisted Networks for Energy Saving and QoS Improving
Venue: arXiv cs.NI 2015
Year: 2015

We study the relay station (RS) sleep control mechanism targeting on reducing energy consumption while improving users' quality of service (QoS) in green relay-assisted cellular networks, where the base station (BS) is powered by grid power and the RSs are powered by renewable energy. By adopting green RSs, the grid power consumption of the BS is greatly reduced. But due to the uncertainty and stochastic characteristics of the renewable energy, power supply for RSs is not always sufficient. Thus the harvested energy needs to be scheduled appropriately to cater to the dynamic traffic so as to minimize the energy saving in the long term. An optimization problem is formulated to find the optimal sleep ratio of RSs to match the time variation of energy harvesting and traffic arrival. To fully use the renewable energy, green-RS-first principle is adopted in the user association process. The optimal RS sleeping policy is obtained through dynamic programming (DP) approach, which divides the original optimization problem into per-stage subproblems. A reduced DP algorithm and a greedy algorithm are further proposed to greatly reduce the computation complexity. By simulations, the reduced DP algorithm outperforms the greedy algorithm in achieving satisfactory energy saving and QoS performance.
New Variational Method of Grid Generation with Prescribed Jacobian Determinant and Prescribed Curl
Venue: arXiv cs.CG 2015
Year: 2015

Adaptive grid generation is an active research topic for numer- ical solution of differential equations. In this paper, we propose a variational method which generates transformations with prescribed Jacobian determinant and curl. Then we use this transformation to achieve adaptive grid generation task, and show the importance of curl in a transformation.
Uplink Downlink Rate Balancing and throughput scaling in FDD Massive MIMO Systems
Venue: arXiv cs.IT 2015
Year: 2015

In this work we extend the concept of uplink-downlink rate balancing to frequency division duplex (FDD) massive MIMO systems. We consider a base station with large number antennas serving many single antenna users. We first show that any unused capacity in the uplink can be traded off for higher throughput in the downlink in a system that uses either dirty paper (DP) coding or linear zero-forcing (ZF) precoding. We then also study the scaling of the system throughput with the number of antennas in cases of linear Beamforming (BF) Precoding, ZF Precoding, and DP coding. We show that the downlink throughput is proportional to the logarithm of the number of antennas. While, this logarithmic scaling is lower than the linear scaling of the rate in the uplink, it can still bring significant throughput gains. For example, we demonstrate through analysis and simulation that increasing the number of antennas from 4 to 128 will increase the throughput by more than a factor of 5. We also show that a logarithmic scaling of downlink throughput as a function of the number of receive antennas can be achieved even when the number of transmit antennas only increases logarithmically with the number of receive antennas.