OpenRaiser/Intern-Atlas huggingface dataset:
Self-Learning for Player Localization in Sports Video
Venue: arXiv cs.CV 2013
Year: 2013

This paper introduces a novel self-learning framework that automates the label acquisition process for improving models for detecting players in broadcast footage of sports games. Unlike most previous self-learning approaches for improving appearance-based object detectors from videos, we allow an unknown, unconstrained number of target objects in a more generalized video sequence with non-static camera views. Our self-learning approach uses a latent SVM learning algorithm and deformable part models to represent the shape and colour information of players, constraining their motions, and learns the colour of the playing field by a gentle Adaboost algorithm. We combine those image cues and discover additional labels automatically from unlabelled data. In our experiments, our approach exploits both labelled and unlabelled data in sparsely labelled videos of sports games, providing a mean performance improvement of over 20% in the average precision for detecting sports players and improved tracking, when videos contain very few labelled images.
Students learning center strategy based on e-learning and blogs
Venue: arXiv cs.CY 2013
Year: 2013

Education is the main infrastructure for promoting a nation and increasing their competitiveness in globalization era that involves the use of information technology (IT). This paper has goal to expand the alternative for learning strategy based on IT for final year students that will conduct a research for their final report. The final year students are expected have the ability to learn independently to manage the needness of their learning supply. In this paper, the author will discuss how to use the e-learning media and blogs to manage the independently learning environment or self-learning. E-learning offers the flexibilities in term of time and place in supporting the learning activities as well as a media for faculty/lecturer to disseminate learning materials. While the blog has been a free medium for the publication of variety contents, including academic contents. In this paper, author suggests some the institutions regulations, lecturers roles, and students participations are involve in set the learning environment based on e-learning and blog. These activities able to support students in learning independently or self-learning.
Analysis and Modeling of Network Connectivity in Routing Protocols for MANETs and VANETs
Venue: arXiv cs.NI 2013
Year: 2013

In this paper, a framework is presented for node distribution with respect to density, network connectivity and communication time. According to modeled framework we evaluate and compare the performance of three routing protocols; Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Fisheye State Routing (FSR) in MANETs and VANETs using two Mac-layer protocols; 802.11 and 802.11p. We have further modified these protocols by changing their routing information exchange intervals; MOD AODV, MOD DSR and MOD FSR. A comprehensive simulation work is performed in NS-2 for the comparison of these routing protocols for varying mobilities and scalabilities of nodes. To evaluate their efficiency; throughput, End-to-End Delay (E2ED) and Normalized Routing Load (NRL) of these protocols are taken into account as performance parameters. After extensive simulations, we observe that AODV outperforms both with MANETs and VANETs.
The Power of Spreadsheet Computations
Venue: arXiv cs.PL 2013
Year: 2013

We investigate the expressive power of spreadsheets. We consider spreadsheets which contain only formulas, and assume that they are small templates, which can be filled to a larger area of the grid to process input data of variable size. Therefore we can compare them to well-known machine models of computation. We consider a number of classes of spreadsheets defined by restrictions on their reference structure. Two of the classes correspond closely to parallel complexity classes: we prove a direct correspondence between the dimensions of the spreadsheet and amount of hardware and time used by a parallel computer to compute the same function. As a tool, we produce spreadsheets which are universal in these classes, i.e. can emulate any other spreadsheet from them. In other cases we implement in the spreadsheets in question instances of a polynomial-time complete problem, which indicates that the the spreadsheets are unlikely to have efficient parallel evaluation algorithms. Thus we get a picture how the computational power of spreadsheets depends on their dimensions and structure of references.
Fit or Unfit : Analysis and Prediction of 'Closed Questions' on Stack Overflow
Venue: arXiv cs.SI 2013
Year: 2013

Stack Overflow is widely regarded as the most popular Community driven Question Answering (CQA) website for programmers. Questions posted on Stack Overflow which are not related to programming topics, are marked as 'closed' by experienced users and community moderators. A question can be 'closed' for five reasons - duplicate, off-topic, subjective, not a real question and too localized. In this work, we present the first study of 'closed' questions in Stack Overflow. We download 4 years of publicly available data which contains 3.4 Million questions. We first analyze and characterize the complete set of 0.1 Million 'closed' questions. Next, we use a machine learning framework and build a predictive model to identify a 'closed' question at the time of question creation. One of our key findings is that despite being marked as 'closed', subjective questions contain high information value and are very popular with the users. We observe an increasing trend in the percentage of closed questions over time and find that this increase is positively correlated to the number of newly registered users. In addition, we also see a decrease in community participation to mark a 'closed' question which has led to an increase in moderation job time. We also find that questions closed with the Duplicate and Off Topic labels are relatively more prone to reputation gaming. For the 'closed' question prediction task, we make use of multiple genres of feature sets based on - user profile, community process, textual style and question content. We use a state-of-art machine learning classifier based on an ensemble learning technique and achieve an overall accuracy of 73%. To the best of our knowledge, this is the first experimental study to analyze and predict 'closed' questions on Stack Overflow.
Complexity of Manipulation, Bribery, and Campaign Management in Bucklin and Fallback Voting
Venue: arXiv cs.GT 2013
Year: 2013

A central theme in computational social choice is to study the extent to which voting systems computationally resist manipulative attacks seeking to influence the outcome of elections, such as manipulation (i.e., strategic voting), control, and bribery. Bucklin and fallback voting are among the voting systems with the broadest resistance (i.e., NP-hardness) to control attacks. However, only little is known about their behavior regarding manipulation and bribery attacks. We comprehensively investigate the computational resistance of Bucklin and fallback voting for many of the common manipulation and bribery scenarios; we also complement our discussion by considering several campaign management problems for Bucklin and fallback.
Improving Data Forwarding in Mobile Social Networks with Infrastructure Support: A Space-Crossing Community Approach
Venue: arXiv cs.SI 2013
Year: 2013

In this paper, we study two tightly coupled issues: space-crossing community detection and its influence on data forwarding in Mobile Social Networks (MSNs) by taking the hybrid underlying networks with infrastructure support into consideration. The hybrid underlying network is composed of large numbers of mobile users and a small portion of Access Points (APs). Because APs can facilitate the communication among long-distance nodes, the concept of physical proximity community can be extended to be one across the geographical space. In this work, we first investigate a space-crossing community detection method for MSNs. Based on the detection results, we design a novel data forwarding algorithm SAAS (Social Attraction and AP Spreading), and show how to exploit the space-crossing communities to improve the data forwarding efficiency. We evaluate our SAAS algorithm on real-life data from MIT Reality Mining and UIM. Results show that space-crossing community plays a positive role in data forwarding in MSNs in terms of deliver ratio and delay. Based on this new type of community, SAAS achieves a better performance than existing social community-based data forwarding algorithms in practice, including Bubble Rap and Nguyen's Routing algorithms.
Learning Frames from Text with an Unsupervised Latent Variable Model
Venue: arXiv cs.CL 2013
Year: 2013

We develop a probabilistic latent-variable model to discover semantic frames---types of events and their participants---from corpora. We present a Dirichlet-multinomial model in which frames are latent categories that explain the linking of verb-subject-object triples, given document-level sparsity. We analyze what the model learns, and compare it to FrameNet, noting it learns some novel and interesting frames. This document also contains a discussion of inference issues, including concentration parameter learning; and a small-scale error analysis of syntactic parsing accuracy.
ROSoClingo: A ROS package for ASP-based robot control
Venue: arXiv cs.RO 2013
Year: 2013

Knowledge representation and reasoning capacities are vital to cognitive robotics because they provide higher level cognitive functions for reasoning about actions, environments, goals, perception, etc. Although Answer Set Programming (ASP) is well suited for modelling such functions, there was so far no seamless way to use ASP in a robotic environment. We address this shortcoming and show how a recently developed reactive ASP system can be harnessed to provide appropriate reasoning capacities within a robotic system. To be more precise, we furnish a package integrating the reactive ASP solver oClingo with the popular open-source robotic middleware ROS. The resulting system, ROSoClingo, provides a generic way by which an ASP program can be used to control the behaviour of a robot and to respond to the results of the robot's actions.
Reasoning for Moving Blocks Problem: Formal Representation and Implementation
Venue: arXiv cs.RO 2013
Year: 2013

The combined approach of the Qualitative Reasoning and Probabilistic Functions for the knowledge representation is proposed. The method aims at represent uncertain, qualitative knowledge that is essential for the moving blocks task's execution. The attempt to formalize the commonsense knowledge is performed with the Situation Calculus language for reasoning and robot's beliefs representation. The method is implemented in the Prolog programming language and tested for a specific simulated scenario. In most cases the implementation enables us to solve a given task, i.e., move blocks to desired positions. The example of robot's reasoning and main parts of the implemented program's code are presented.
Algebraic Meta-Theory of Processes with Data
Venue: arXiv cs.LO 2013
Year: 2013

There exists a rich literature of rule formats guaranteeing different algebraic properties for formalisms with a Structural Operational Semantics. Moreover, there exist a few approaches for automatically deriving axiomatizations characterizing strong bisimilarity of processes. To our knowledge, this literature has never been extended to the setting with data (e.g. to model storage and memory). We show how the rule formats for algebraic properties can be exploited in a generic manner in the setting with data. Moreover, we introduce a new approach for deriving sound and ground-complete axiom schemata for a notion of bisimilarity with data, called stateless bisimilarity, based on intuitive auxiliary function symbols for handling the store component. We do restrict, however, the axiomatization to the setting where the store component is only given in terms of constants.
Relative Errors for Deterministic Low-Rank Matrix Approximations
Venue: arXiv cs.DS 2013
Year: 2013

We consider processing an n x d matrix A in a stream with row-wise updates according to a recent algorithm called Frequent Directions (Liberty, KDD 2013). This algorithm maintains an l x d matrix Q deterministically, processing each row in O(d l^2) time; the processing time can be decreased to O(d l) with a slight modification in the algorithm and a constant increase in space. We show that if one sets l = k+ k/eps and returns Q_k, a k x d matrix that is the best rank k approximation to Q, then we achieve the following properties: ||A - A_k||_F^2 <= ||A||_F^2 - ||Q_k||_F^2 <= (1+eps) ||A - A_k||_F^2 and where pi_{Q_k}(A) is the projection of A onto the rowspace of Q_k then ||A - pi_{Q_k}(A)||_F^2 <= (1+eps) ||A - A_k||_F^2. We also show that Frequent Directions cannot be adapted to a sparse version in an obvious way that retains the l original rows of the matrix, as opposed to a linear combination or sketch of the rows.
Levels of Integration between Low-Level Reasoning and Task Planning
Venue: arXiv cs.RO 2013
Year: 2013

We provide a systematic analysis of levels of integration between discrete high-level reasoning and continuous low-level reasoning to address hybrid planning problems in robotics. We identify four distinct strategies for such an integration: (i) low-level checks are done for all possible cases in advance and then this information is used during plan generation, (ii) low-level checks are done exactly when they are needed during the search for a plan, (iii) first all plans are computed and then infeasible ones are filtered, and (iv) by means of replanning, after finding a plan, low-level checks identify whether it is infeasible or not; if it is infeasible, a new plan is computed considering the results of previous low- level checks. We perform experiments on hybrid planning problems in robotic manipulation and legged locomotion domains considering these four methods of integration, as well as some of their combinations. We analyze the usefulness of levels of integration in these domains, both from the point of view of computational efficiency (in time and space) and from the point of view of plan quality relative to its feasibility. We discuss advantages and disadvantages of each strategy in the light of experimental results and provide some guidelines on choosing proper strategies for a given domain.
Improved Service Delivery and Cost Effective Framework for e-Governance in India
Venue: arXiv cs.CY 2013
Year: 2013

In current era, the involvement of technologies like virtualization, consolidation and cloud computing, and adoption of free and open source software in designing and deploying e-governance that can reduce the total cost associated with and hence the financial burden abide by the state and central governments. The success of any e-governance project depends upon its utilization by the intended group and so there accessibility needs to be enhanced drastically by reengineered framework. Here, we design an Improved Service Delivery and Cost Effective Framework for e-Governance that will be useful for success of e-governance projects and the delivery mechanism in India by using free and open access software for development and deployment of e-governance applications, virtualization and consolidation techniques for management of e-services and cloud computing for enhancing the accessibility of services.
Building on the Case Teaching Method to Generate Learning Games Relevant to Numerous Educational Fields
Venue: arXiv cs.CY 2013
Year: 2013

University teachers often feel the need to try innovative learning technologies such as Learning Games to motivate the new generation of students. However, the typically limited resources of universities coupled with the high cost of designing and developing Learning Games result in it rarely being feasible to meet this need. To address this challenging problem, we have designed a framework that allows teachers to create their own Learning Games with very little or no help from developers and graphic designers. This framework, tested and validated by several university teachers, is suited to a wide variety of educational fields because it generates Learning Games based on the widely-used case teaching method.
Towards a System Theoretic Approach to Wireless Network Capacity in Finite Time and Space
Venue: arXiv cs.PF 2013
Year: 2013

In asymptotic regimes, both in time and space (network size), the derivation of network capacity results is grossly simplified by brushing aside queueing behavior in non-Jackson networks. This simplifying double-limit model, however, lends itself to conservative numerical results in finite regimes. To properly account for queueing behavior beyond a simple calculus based on average rates, we advocate a system theoretic methodology for the capacity problem in finite time and space regimes. This methodology also accounts for spatial correlations arising in networks with CSMA/CA scheduling and it delivers rigorous closed-form capacity results in terms of probability distributions. Unlike numerous existing asymptotic results, subject to anecdotal practical concerns, our transient one can be used in practical settings: for example, to compute the time scales at which multi-hop routing is more advantageous than single-hop routing.
Herding the Crowd: Automated Planning for Crowdsourced Planning
Venue: arXiv cs.AI 2013
Year: 2013

There has been significant interest in crowdsourcing and human computation. One subclass of human computation applications are those directed at tasks that involve planning (e.g. travel planning) and scheduling (e.g. conference scheduling). Much of this work appears outside the traditional automated planning forums, and at the outset it is not clear whether automated planning has much of a role to play in these human computation systems. Interestingly however, work on these systems shows that even primitive forms of automated oversight of the human planner does help in significantly improving the effectiveness of the humans/crowd. In this paper, we will argue that the automated oversight used in these systems can be viewed as a primitive automated planner, and that there are several opportunities for more sophisticated automated planning in effectively steering crowdsourced planning. Straightforward adaptation of current planning technology is however hampered by the mismatch between the capabilities of human workers and automated planners. We identify two important challenges that need to be overcome before such adaptation of planning technology can occur: (i) interpreting the inputs of the human workers (and the requester) and (ii) steering or critiquing the plans being produced by the human workers armed only with incomplete domain and preference models. In this paper, we discuss approaches for handling these challenges, and characterize existing human computation systems in terms of the specific choices they make in handling these challenges.
Local, Smooth, and Consistent Jacobi Set Simplification
Venue: arXiv cs.CG 2013
Year: 2013

The relation between two Morse functions defined on a common domain can be studied in terms of their Jacobi set. The Jacobi set contains points in the domain where the gradients of the functions are aligned. Both the Jacobi set itself as well as the segmentation of the domain it induces have shown to be useful in various applications. Unfortunately, in practice functions often contain noise and discretization artifacts causing their Jacobi set to become unmanageably large and complex. While there exist techniques to simplify Jacobi sets, these are unsuitable for most applications as they lack fine-grained control over the process and heavily restrict the type of simplifications possible. In this paper, we introduce a new framework that generalizes critical point cancellations in scalar functions to Jacobi sets in two dimensions. We focus on simplifications that can be realized by smooth approximations of the corresponding functions and show how this implies simultaneously simplifying contiguous subsets of the Jacobi set. These extended cancellations form the atomic operations in our framework, and we introduce an algorithm to successively cancel subsets of the Jacobi set with minimal modifications according to some user-defined metric. We prove that the algorithm is correct and terminates only once no more local, smooth and consistent simplifications are possible. We disprove a previous claim on the minimal Jacobi set for manifolds with arbitrary genus and show that for simply connected domains, our algorithm reduces a given Jacobi set to its simplest configuration.
A Connection between Good Rate-distortion Codes and Backward DMCs
Venue: arXiv cs.IT 2013
Year: 2013

Let $X^n\in\mathcal{X}^n$ be a sequence drawn from a discrete memoryless source, and let $Y^n\in\mathcal{Y}^n$ be the corresponding reconstruction sequence that is output by a good rate-distortion code. This paper establishes a property of the joint distribution of $(X^n,Y^n)$. It is shown that for $D>0$, the input-output statistics of a $R(D)$-achieving rate-distortion code converge (in normalized relative entropy) to the output-input statistics of a discrete memoryless channel (dmc). The dmc is "backward" in that it is a channel from the reconstruction space $\mathcal{Y}^n$ to source space $\mathcal{X}^n$. It is also shown that the property does not necessarily hold when normalized relative entropy is replaced by variational distance.
An Overview of Load Balancing in HetNets: Old Myths and Open Problems
Venue: arXiv cs.IT 2013
Year: 2013

Matching the demand for resources ("load") with the supply of resources ("capacity") is a basic problem occurring across many fields of engineering, logistics, and economics, and has been considered extensively both in the Internet and in wireless networks. The ongoing evolution of cellular communication networks into dense, organic, and irregular heterogeneous networks ("HetNets") has elevated load-awareness to a central problem, and introduces many new subtleties. This paper explains how several long-standing assumptions about cellular networks need to be rethought in the context of a load-balanced HetNet: we highlight these as three deeply entrenched myths that we then dispel. We survey and compare the primary technical approaches to HetNet load balancing: (centralized) optimization, game theory, Markov decision processes, and the newly popular cell range expansion (a.k.a. "biasing"), and draw design lessons for OFDMA-based cellular systems. We also identify several open areas for future exploration.
The generalized Robinson-Foulds metric
Venue: arXiv cs.DS 2013
Year: 2013

The Robinson-Foulds (RF) metric is arguably the most widely used measure of phylogenetic tree similarity, despite its well-known shortcomings: For example, moving a single taxon in a tree can result in a tree that has maximum distance to the original one; but the two trees are identical if we remove the single taxon. To this end, we propose a natural extension of the RF metric that does not simply count identical clades but instead, also takes similar clades into consideration. In contrast to previous approaches, our model requires the matching between clades to respect the structure of the two trees, a property that the classical RF metric exhibits, too. We show that computing this generalized RF metric is, unfortunately, NP-hard. We then present a simple Integer Linear Program for its computation, and evaluate it by an all-against-all comparison of 100 trees from a benchmark data set. We find that matchings that respect the tree structure differ significantly from those that do not, underlining the importance of this natural condition.