OpenRaiser/Intern-Atlas huggingface dataset:
Alternating Decision trees for early diagnosis of dengue fever
Venue: arXiv cs.LG 2013
Year: 2013

Dengue fever is a flu-like illness spread by the bite of an infected mosquito which is fast emerging as a major health problem. Timely and cost effective diagnosis using clinical and laboratory features would reduce the mortality rates besides providing better grounds for clinical management and disease surveillance. We wish to develop a robust and effective decision tree based approach for predicting dengue disease. Our analysis is based on the clinical characteristics and laboratory measurements of the diseased individuals. We have developed and trained an alternating decision tree with boosting and compared its performance with C4.5 algorithm for dengue disease diagnosis. Of the 65 patient records a diagnosis establishes that 53 individuals have been confirmed to have dengue fever. An alternating decision tree based algorithm was able to differentiate the dengue fever using the clinical and laboratory data with number of correctly classified instances as 89%, F-measure of 0.86 and receiver operator characteristics (ROC) of 0.826 as compared to C4.5 having correctly classified instances as 78%,h F-measure of 0.738 and ROC of 0.617 respectively. Alternating decision tree based approach with boosting has been able to predict dengue fever with a higher degree of accuracy than C4.5 based decision tree using simple clinical and laboratory features. Further analysis on larger data sets is required to improve the sensitivity and specificity of the alternating decision trees.
Pervasive Parallelism in Highly-Trustable Interactive Theorem Proving Systems
Venue: arXiv cs.LO 2013
Year: 2013

This is an overview of the Paral-ITP project, which intents to make the proof assistants Isabelle and Coq fit for the multicore era.
Monitoring Large-Scale Cloud Systems with Layered Gossip Protocols
Venue: arXiv cs.DC 2013
Year: 2013

Monitoring is an essential aspect of maintaining and developing computer systems that increases in difficulty proportional to the size of the system. The need for robust monitoring tools has become more evident with the advent of cloud computing. Infrastructure as a Service (IaaS) clouds allow end users to deploy vast numbers of virtual machines as part of dynamic and transient architectures. Current monitoring solutions, including many of those in the open-source domain rely on outdated concepts including manual deployment and configuration, centralised data collection and adapt poorly to membership churn. In this paper we propose the development of a cloud monitoring suite to provide scalable and robust lookup, data collection and analysis services for large-scale cloud systems. In lieu of centrally managed monitoring we propose a multi-tier architecture using a layered gossip protocol to aggregate monitoring information and facilitate lookup, information collection and the identification of redundant capacity. This allows for a resource aware data collection and storage architecture that operates over the system being monitored. This in turn enables monitoring to be done in-situ without the need for significant additional infrastructure to facilitate monitoring services. We evaluate this approach against alternative monitoring paradigms and demonstrate how our solution is well adapted to usage in a cloud-computing context.
Advanced Personnel Vetting Techniques in Critical Multi-Tennant Hosted Computing Environments
Venue: arXiv cs.CR 2013
Year: 2013

The emergence of cloud computing presents a strategic direction for critical infrastructures and promises to have far-reaching effects on their systems and networks to deliver better outcomes to the nations at a lower cost. However, when considering cloud computing, government entities must address a host of security issues (such as malicious insiders) beyond those of service cost and flexibility. The scope and objective of this paper is to analyze, evaluate and investigate the insider threat in cloud security in sensitive infrastructures as well as to propose two proactive socio-technical solutions for securing commercial and governmental cloud infrastructures. Firstly, it proposes actionable framework, techniques and practices in order to ensure that such disruptions through human threats are infrequent, of minimal duration, manageable, and cause the least damage possible. Secondly, it aims for extreme security measures to analyze and evaluate human threats related assessment methods for employee screening in certain high-risk situations using cognitive analysis technology, in particular functional magnetic Resonance Imaging (fMRI). The significance of this research is also to counter human rights and ethical dilemmas by presenting a set of ethical and professional guidelines. The main objective of this work is to analyze related risks, identify countermeasures and present recommendations to develop a security awareness culture that will allow cloud providers to utilize effectively the benefits of this advanced techniques without sacrificing system security.
An Open Question on the Uniqueness of (Encrypted) Arithmetic
Venue: arXiv cs.CR 2013
Year: 2013

We ask whether two or more images of arithmetic may inhabit the same space via different encodings. The answers have significance for a class of processor design that does all its computation in an encrypted form, without ever performing any decryption or encryption itself. Against the possibility of algebraic attacks against the arithmetic in a `crypto-processor' (KPU) we propose a defence called `ABC encryption' and show how this kind of encryption makes it impossible for observations of the arithmetic to be used by an attacker to discover the actual values. We also show how to construct such encrypted arithmetics.
Recursive Sorting in Lattices
Venue: arXiv cs.DM 2013
Year: 2013

The direct application of the definition of sorting in lattices is impractical because it leads to an algorithm with exponential complexity. In this paper we present for distributive lattices a recursive formulation to compute the sort of a sequence. This alternative formulation is inspired by the identity that underlies Pascal's triangle. It provides quadratic complexity and is in fact a generalization of insertion sort for lattices.
A Hierarchical Modulation for Upgrading Digital Broadcast Systems
Venue: arXiv cs.IT 2013
Year: 2013

A hierarchical modulation scheme is proposed to upgrade an existing digital broadcast system, such as satellite TV, or satellite radio, by adding more data in its transmission. The hierarchical modulation consists of a basic constellation, which is the same as in the original system, and a secondary constellation, which carries the additional data for the upgraded system. The upgraded system with the hierarchical modulation is backward compatible in the sense that receivers that have been deployed in the original system can continue receiving data in the basic constellation. New receivers can be designed to receive data carried in the secondary constellation, as well as those in the basic constellation. Analysis will be performed to show the tradeoff between bit rate of the data in secondary constellation and the penalty to the performance of receiving the basic constellation.
Providing Local Content in a Hybrid Single Frequency Network using Hierarchical Modulation
Venue: arXiv cs.IT 2013
Year: 2013

A hierarchical modulation method is proposed for providing local content in a hybrid satellite and terrestrial single frequency network such DVB-SH. The hierarchical modulation is used to transmit both global and local content in terrestrial transmitters. The global content is transmitted with high priority layer of the hierarchical modulation, and the local content is modulated with the low priority layer of the hierarchical modulation. The satellite transmits global content only. The performance of the hierarchical system for both global and local content is analyzed.
Digital predistortion for power amplifiers using separable functions
Venue: arXiv cs.IT 2013
Year: 2013

This paper is concerned with digital predistortion for linearization of RF high power amplifiers (HPAs). It has two objectives. First, we establish a theoretical framework for a generic predistorter system, and show that if a postdistorter exists, then it is also a predistorter, and therefore, the predistorter and postdistorter are equivalent. This justifies the indirect learning methods for a large class of HPAs. Secondly, we establish a systematic and general structure for a predistorter that is capable of compensating nonlinearity for a large variety of HPAs. This systematic structure is derived using approximation by separable functions, and avoids selection of predistorters based on the assumption of HPA models traditionally done in the literature.
Sensitive Ants for Denial Jamming Attack on Wireless Sensor Network
Venue: arXiv cs.CR 2013
Year: 2013

A new defence mechanism for different jamming attack on Wireless Sensor Network (WSN) based on ant system it is introduced. The artificial sensitive ants react on network attacks in particular based on their sensitivity level. The information is re-directed from the attacked node to its appropriate destination node. It is analyzed how are detected and isolated the jamming attacks with mobile agents in general and in particular with the newly ant-based sensitive approach.
An Analysis of the Connections Between Layers of Deep Neural Networks
Venue: arXiv cs.CV 2013
Year: 2013

We present an analysis of different techniques for selecting the connection be- tween layers of deep neural networks. Traditional deep neural networks use ran- dom connection tables between layers to keep the number of connections small and tune to different image features. This kind of connection performs adequately in supervised deep networks because their values are refined during the training. On the other hand, in unsupervised learning, one cannot rely on back-propagation techniques to learn the connections between layers. In this work, we tested four different techniques for connecting the first layer of the network to the second layer on the CIFAR and SVHN datasets and showed that the accuracy can be im- proved up to 3% depending on the technique used. We also showed that learning the connections based on the co-occurrences of the features does not confer an advantage over a random connection table in small networks. This work is helpful to improve the efficiency of connections between the layers of unsupervised deep neural networks.
Dynamic Ad Allocation: Bandits with Budgets
Venue: arXiv cs.LG 2013
Year: 2013

We consider an application of multi-armed bandits to internet advertising (specifically, to dynamic ad allocation in the pay-per-click model, with uncertainty on the click probabilities). We focus on an important practical issue that advertisers are constrained in how much money they can spend on their ad campaigns. This issue has not been considered in the prior work on bandit-based approaches for ad allocation, to the best of our knowledge. We define a simple, stylized model where an algorithm picks one ad to display in each round, and each ad has a \emph{budget}: the maximal amount of money that can be spent on this ad. This model admits a natural variant of UCB1, a well-known algorithm for multi-armed bandits with stochastic rewards. We derive strong provable guarantees for this algorithm.
Perceptions and Truth: A Mechanism Design Approach to Crowd-Sourcing Reputation
Venue: arXiv cs.GT 2013
Year: 2013

We consider a distributed multi-user system where individual entities possess observations or perceptions of one another, while the truth is only known to themselves, and they might have an interest in withholding or distorting the truth. We ask the question whether it is possible for the system as a whole to arrive at the correct perceptions or assessment of all users, referred to as their reputation, by encouraging or incentivizing the users to participate in a collective effort without violating private information and self-interest. Two specific applications, online shopping and network reputation, are provided to motivate our study and interpret the results. In this paper we investigate this problem using a mechanism design theoretic approach. We introduce a number of utility models representing users' strategic behavior, each consisting of one or both of a truth element and an image element, reflecting the user's desire to obtain an accurate view of the other and an inflated image of itself. For each model, we either design a mechanism that achieves the optimal performance (solution to the corresponding centralized problem), or present individually rational sub-optimal solutions. In the latter case, we demonstrate that even when the centralized solution is not achievable, by using a simple punish-reward mechanism, not only a user has the incentive to participate and provide information, but also that this information can improve the system performance.
A Trust-based Recruitment Framework for Multi-hop Social Participatory Sensing
Venue: arXiv cs.SI 2013
Year: 2013

The idea of social participatory sensing provides a substrate to benefit from friendship relations in recruiting a critical mass of participants willing to attend in a sensing campaign. However, the selection of suitable participants who are trustable and provide high quality contributions is challenging. In this paper, we propose a recruitment framework for social participatory sensing. Our framework leverages multi-hop friendship relations to identify and select suitable and trustworthy participants among friends or friends of friends, and finds the most trustable paths to them. The framework also includes a suggestion component which provides a cluster of suggested friends along with the path to them, which can be further used for recruitment or friendship establishment. Simulation results demonstrate the efficacy of our proposed recruitment framework in terms of selecting a large number of well-suited participants and providing contributions with high overall trust, in comparison with one-hop recruitment architecture.
An efficient method for evaluating BEM singular integrals on curved elements with application in acoustic analysis
Venue: arXiv cs.CE 2013
Year: 2013

The polar coordinate transformation (PCT) method has been extensively used to treat various singular integrals in the boundary element method (BEM). However, the resultant integrands of the PCT tend to become nearly singular when (1) the aspect ratio of the element is large or (2) the field point is closed to the element boundary; thus a large number of quadrature points are needed to achieve a relatively high accuracy. In this paper, the first problem is circumvented by using a conformal transformation so that the geometry of the curved physical element is preserved in the transformed domain. The second problem is alleviated by using a sigmoidal transformation, which makes the quadrature points more concentrated around the near singularity. By combining the proposed two transformations with the Guiggiani's method in [M. Guiggiani, \emph{et al}. A general algorithm for the numerical solution of hypersingular boundary integral equations. \emph{ASME Journal of Applied Mechanics}, 59(1992), 604-614], one obtains an efficient and robust numerical method for computing the weakly-, strongly- and hyper-singular integrals in high-order BEM with curved elements. Numerical integration results show that, compared with the original PCT, the present method can reduce the number of quadrature points considerably, for given accuracy. For further verification, the method is incorporated into a 2-order Nyström BEM code for solving acoustic Burton-Miller boundary integral equation. It is shown that the method can retain the convergence rate of the BEM with much less quadrature points than the existing PCT. The method is implemented in C language and freely available.
Revisiting Circular-Based Random Node Simulation
Venue: arXiv cs.IT 2013
Year: 2013

In literature, a stochastic model for spreading nodes in a cellular cell is available. Despite its existence, the current method does not offer any versatility in dealing with sectored layers. Of course, this needed adaptability could be created synthetically through heuristic means. However, due to selective sampling, such practice dissolves the true randomness sought. Hence, in this paper, a universal exact scattering model is derived. Also, as an alternative to exhaustive simulation, a generic close-form path-loss predictor between a node and a BS is obtained. Further, using these results, an algorithm based on the superposition principle is proposed. This will ensure greater emulation flexibility, and attain a heterogeneous spatial density.
Managing Unbounded-Length Keys in Comparison-Driven Data Structures with Applications to On-Line Indexing
Venue: arXiv cs.DS 2013
Year: 2013

This paper presents a general technique for optimally transforming any dynamic data structure that operates on atomic and indivisible keys by constant-time comparisons, into a data structure that handles unbounded-length keys whose comparison cost is not a constant. Examples of these keys are strings, multi-dimensional points, multiple-precision numbers, multi-key data (e.g.~records), XML paths, URL addresses, etc. The technique is more general than what has been done in previous work as no particular exploitation of the underlying structure of is required. The only requirement is that the insertion of a key must identify its predecessor or its successor. Using the proposed technique, online suffix tree can be constructed in worst case time $O(\log n)$ per input symbol (as opposed to amortized $O(\log n)$ time per symbol, achieved by previously known algorithms). To our knowledge, our algorithm is the first that achieves $O(\log n)$ worst case time per input symbol. Searching for a pattern of length $m$ in the resulting suffix tree takes $O(\min(m\log |Σ|, m + \log n) + tocc)$ time, where $tocc$ is the number of occurrences of the pattern. The paper also describes more applications and show how to obtain alternative methods for dealing with suffix sorting, dynamic lowest common ancestors and order maintenance.
A Three-Dimensional Model of Residential Energy Consumer Archetypes for Local Energy Policy Design in the UK
Venue: arXiv cs.CY 2013
Year: 2013

This paper reviews major studies in three traditional lines of research in residential energy consumption in the UK, i.e. economic/infrastructure, behaviour, and load profiling. Based on the review the paper proposes a three-dimensional model for archetyping residential energy consumers in the UK by considering property energy efficiency levels, the greenness of household behaviour of using energy, and the duration of property daytime occupancy. With the proposed model, eight archetypes of residential energy consumers in the UK have been identified. They are: pioneer greens, follower greens, concerned greens, home stayers, unconscientious wasters, regular wasters, daytime wasters, and disengaged wasters. Using a case study, these archetypes of residential energy consumers demonstrate the robustness of the 3-D model in aiding local energy policy/intervention design in the UK.
Hybrid Coding: An Interface for Joint Source-Channel Coding and Network Communication
Venue: arXiv cs.IT 2013
Year: 2013

A new approach to joint source-channel coding is presented in the context of communicating correlated sources over multiple access channels. Similar to the separation architecture, the joint source-channel coding system architecture in this approach is modular, whereby the source encoding and channel decoding operations are decoupled. However, unlike the separation architecture, the same codeword is used for both source coding and channel coding, which allows the resulting hybrid coding scheme to achieve the performance of the best known joint source-channel coding schemes. Applications of the proposed architecture to relay communication are also discussed.
Identifying Pairs in Simulated Bio-Medical Time-Series
Venue: arXiv cs.LG 2013
Year: 2013

The paper presents a time-series-based classification approach to identify similarities in pairs of simulated human-generated patterns. An example for a pattern is a time-series representing a heart rate during a specific time-range, wherein the time-series is a sequence of data points that represent the changes in the heart rate values. A bio-medical simulator system was developed to acquire a collection of 7,871 price patterns of financial instruments. The financial instruments traded in real-time on three American stock exchanges, NASDAQ, NYSE, and AMEX, simulate bio-medical measurements. The system simulates a human in which each price pattern represents one bio-medical sensor. Data provided during trading hours from the stock exchanges allowed real-time classification. Classification is based on new machine learning techniques: self-labeling, which allows the application of supervised learning methods on unlabeled time-series and similarity ranking, which applied on a decision tree learning algorithm to classify time-series regardless of type and quantity.
Estimating the distance from testable affine-invariant properties
Venue: arXiv cs.CC 2013
Year: 2013

Let $\cal{P}$ be an affine invariant property of functions $\mathbb{F}_p^n \to [R]$ for fixed $p$ and $R$. We show that if $\cal{P}$ is locally testable with a constant number of queries, then one can estimate the distance of a function $f$ from $\cal{P}$ with a constant number of queries. This was previously unknown even for simple properties such as cubic polynomials over $\mathbb{F}_2$. Our test is simple: take a restriction of $f$ to a constant dimensional affine subspace, and measure its distance from $\cal{P}$. We show that by choosing the dimension large enough, this approximates with high probability the global distance of $f$ from $\cP$. The analysis combines the approach of Fischer and Newman [SIAM J. Comp 2007] who established a similar result for graph properties, with recently developed tools in higher order Fourier analysis, in particular those developed in Bhattacharyya et al. [STOC 2013].
Predictability of Event Occurrences in Timed Systems
Venue: arXiv cs.SY 2013
Year: 2013

We address the problem of predicting events' occurrences in partially observable timed systems modelled by timed automata. Our contribution is many-fold: 1) we give a definition of bounded predictability, namely k-predictability, that takes into account the minimum delay between the prediction and the actual event's occurrence; 2) we show that 0-predictability is equivalent to the original notion of predictability of S. Genc and S. Lafortune; 3) we provide a necessary and sufficient condition for k-predictability (which is very similar to k-diagnosability) and give a simple algorithm to check k-predictability; 4) we address the problem of predictability of events' occurrences in timed automata and show that the problem is PSPACE-complete.
Tracing cross-free polylines oriented by a N-symmetry direction field on triangulated surfaces
Venue: arXiv cs.CG 2013
Year: 2013

We propose an algorithm for tracing polylines on a triangle mesh such that: they are aligned with a N-symmetry direction field, and two such polylines cannot cross or merge. This property is fundamental for mesh segmentation and is very difficult to enforce with numerical integration of vector fields. We propose an alternative solution based on "stream-mesh", a new combinatorial data structure that defines, for each point of a triangle edge, where the corresponding polyline leaves the triangle. It makes it possible to trace polylines by iteratively crossing triangles. Vector field singularities and polyline/vertex crossing are characterized and consistently handled. The polylines inherits the cross-free property of the stream-mesh, except inside triangles where avoiding local overlaps would require higher order polycurves.