OpenRaiser/Intern-Atlas huggingface dataset:
Exact Hybrid Covariance Thresholding for Joint Graphical Lasso
Venue: arXiv cs.LG 2015
Year: 2015

This paper considers the problem of estimating multiple related Gaussian graphical models from a $p$-dimensional dataset consisting of different classes. Our work is based upon the formulation of this problem as group graphical lasso. This paper proposes a novel hybrid covariance thresholding algorithm that can effectively identify zero entries in the precision matrices and split a large joint graphical lasso problem into small subproblems. Our hybrid covariance thresholding method is superior to existing uniform thresholding methods in that our method can split the precision matrix of each individual class using different partition schemes and thus split group graphical lasso into much smaller subproblems, each of which can be solved very fast. In addition, this paper establishes necessary and sufficient conditions for our hybrid covariance thresholding algorithm. The superior performance of our thresholding method is thoroughly analyzed and illustrated by a few experiments on simulated data and real gene expression data.
Attack Trees with Sequential Conjunction
Venue: arXiv cs.CR 2015
Year: 2015

We provide the first formal foundation of SAND attack trees which are a popular extension of the well-known attack trees. The SAND attack tree formalism increases the expressivity of attack trees by introducing the sequential conjunctive operator SAND. This operator enables the modeling of ordered events. We give a semantics to SAND attack trees by interpreting them as sets of series-parallel graphs and propose a complete axiomatization of this semantics. We define normal forms for SAND attack trees and a term rewriting system which allows identification of semantically equivalent trees. Finally, we formalize how to quantitatively analyze SAND attack trees using attributes.
A General Scheme for Noise-Tolerant Logic Design Based on Probabilistic and DCVS Approaches
Venue: arXiv cs.AR 2015
Year: 2015

In this paper, a general circuit scheme for noise-tolerant logic design based on Markov Random Field theory and differential Cascade Voltage Switch technique has been proposed, which is an extension of the work in [1-3], [4]. A block with only four transistors has been successfully inserted to the original circuit scheme from [3] and extensive simulation results show that our proposed design can operate correctly with the input signal of 1 dB signal-noise-ratio. When using the evaluation parameter from [5], the output value of our design decreases by 76.5% on average than [3] which means that superior noise-immunity could be obtained through our work.
Predicting Virtual Learning Environment adoption - A case study
Venue: arXiv cs.CY 2015
Year: 2015

Purpose - To qualify the significance of Rogers' Diffusion of Innovations theory with regard to Virtual Learning Environments. To apply an existing Diffusion of Innovations instrument on a case organisation, the Royal University of Bhutan (RUB), in order to compare its results with previous findings. Descriptive statistics and logistic regression analysis were deployed to analyze adopter group memberships and predictor significance in Virtual Learning Environment adoption and use. Findings - The Diffusion of Innovations theory is not stable across organizations when it comes to predicting different user categories or the distribution of users. However, it was possible to achieve reliable results for virtual learning environments within a particular organization. Research limitations ND implications - The study questions scholarly attempts to establish models of this type across organizations. Practical implications - Professionals should be aware that cross-organizational generalizations from Diffusion Of Innovation findings within the domain of virtual learning environments may be very unreliable. Originality and value - The study challenges the massively cited Diffusion of Innovation literature. It provides data from Bhutan, which is underrepresented in empirical investigations.
Presenting Distributive Laws
Venue: arXiv cs.LO 2015
Year: 2015

Distributive laws of a monad T over a functor F are categorical tools for specifying algebra-coalgebra interaction. They proved to be important for solving systems of corecursive equations, for the specification of well-behaved structural operational semantics and, more recently, also for enhancements of the bisimulation proof method. If T is a free monad, then such distributive laws correspond to simple natural transformations. However, when T is not free it can be rather difficult to prove the defining axioms of a distributive law. In this paper we describe how to obtain a distributive law for a monad with an equational presentation from a distributive law for the underlying free monad. We apply this result to show the equivalence between two different representations of context-free languages.
Two Compact Incremental Prime Sieves
Venue: arXiv cs.DS 2015
Year: 2015

A prime sieve is an algorithm that finds the primes up to a bound $n$. We say that a prime sieve is incremental, if it can quickly determine if $n+1$ is prime after having found all primes up to $n$. We say a sieve is compact if it uses roughly $\sqrt{n}$ space or less. In this paper we present two new results: (1) We describe the rolling sieve, a practical, incremental prime sieve that takes $O(n\log\log n)$ time and $O(\sqrt{n}\log n)$ bits of space, and (2) We show how to modify the sieve of Atkin and Bernstein (2004) to obtain a sieve that is simultaneously sublinear, compact, and incremental. The second result solves an open problem given by Paul Pritchard in 1994.
Promoting Truthful Behaviour in Participatory-Sensing Mechanisms
Venue: arXiv cs.GT 2015
Year: 2015

In this paper, the interplay between a class of nonlinear estimators and strategic sensors is studied in several participatory-sensing scenarios. It is shown that for the class of estimators, if the strategic sensors have access to noiseless measurements of the to-be-estimated-variable, truth-telling is an equilibrium of the game that models the interplay between the sensors and the estimator. Furthermore, performance of the proposed estimators is examined in the case that the strategic sensors form coalitions and in the presence of noise.
Short Text Hashing Improved by Integrating Multi-Granularity Topics and Tags
Venue: arXiv cs.IR 2015
Year: 2015

Due to computational and storage efficiencies of compact binary codes, hashing has been widely used for large-scale similarity search. Unfortunately, many existing hashing methods based on observed keyword features are not effective for short texts due to the sparseness and shortness. Recently, some researchers try to utilize latent topics of certain granularity to preserve semantic similarity in hash codes beyond keyword matching. However, topics of certain granularity are not adequate to represent the intrinsic semantic information. In this paper, we present a novel unified approach for short text Hashing using Multi-granularity Topics and Tags, dubbed HMTT. In particular, we propose a selection method to choose the optimal multi-granularity topics depending on the type of dataset, and design two distinct hashing strategies to incorporate multi-granularity topics. We also propose a simple and effective method to exploit tags to enhance the similarity of related texts. We carry out extensive experiments on one short text dataset as well as on one normal text dataset. The results demonstrate that our approach is effective and significantly outperforms baselines on several evaluation metrics.
On the Performance of Multi-Antenna Wireless-Powered Communications with Energy Beamforming
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we study the average throughput performance of energy beamforming in a multi-antenna wireless-powered communication network (WPCN). The considered network consists of one hybrid access-point (AP) with multiple antennas and a single antenna user. The user does not have constant power supply and thus needs to harvest energy from the signals broadcast by the AP in the downlink (DL), before sending its data back to the AP with the harvested energy in the uplink (UL). We derive closed-form expressions of the average throughput and their asymptotic expressions at high SNR for both delay-limited and delay-tolerant transmission modes. The optimal DL energy harvesting time, which maximizes the system throughput, is then obtained for high SNR. All analytical expressions are validated by numerical simulations. The impact of various parameters, such as the AP transmit power, the energy harvesting time, and the number of antennas, on the system throughput is also investigated.
An Energy Efficient Ethernet Strategy Based on Traffic Prediction and Shaping
Venue: arXiv cs.NI 2015
Year: 2015

Recently, different communities in computer science, telecommunication and control systems have devoted a huge effort towards the design of energy efficient solutions for data transmission and network management. This paper collocates along this research line and presents a novel energy efficient strategy conceived for Ethernet networks. The proposed strategy combines the statistical properties of the network traffic with the opportunities offered by the IEEE 802.3az amendment to the Ethernet standard, called Energy Efficient Ethernet (EEE). This strategy exploits the possibility of predicting the incoming traffic from the analysis of the current data flow, which typically presents a self-similar behavior. Based on the prediction, Ethernet links can then be put in a low power consumption state for the intervals of time in which traffic is expected to be of low intensity. Theoretical bounds are derived that detail how the performance figures depend on the parameters of the designed strategy and scale with respect to the traffic load. Furthermore, simulations results, based on both real and synthetic traffic traces, are presented to prove the effectiveness of the strategy, which leads to considerable energy savings at the cost of only a limited bounded delay in data delivery.
RDF-Hunter: Automatically Crowdsourcing the Execution of Queries Against RDF Data Sets
Venue: arXiv cs.DB 2015
Year: 2015

In the last years, a large number of RDF data sets has become available on the Web. However, due to the semi-structured nature of RDF data, missing values affect answer completeness of queries that are posed against this data. To overcome this limitation, we propose RDF-Hunter, a novel hybrid query processing approach that brings together machine and human computation to execute queries against RDF data. We develop a novel quality model and query engine in order to enable RDF-Hunter to on the fly decide which parts of a query should be executed through conventional technology or crowd computing. To evaluate RDF-Hunter, we created a collection of 50 SPARQL queries against the DBpedia data set, executed them using our hybrid query engine, and analyzed the accuracy of the outcomes obtained from the crowd. The experiments clearly show that the overall approach is feasible and produces query results that reliably and significantly enhance completeness of automatic query processing responses.
Quantum Structure in Cognition, Origins, Developments, Successes and Expectations
Venue: arXiv cs.AI 2015
Year: 2015

We provide an overview of the results we have attained in the last decade on the identification of quantum structures in cognition and, more specifically, in the formalization and representation of natural concepts. We firstly discuss the quantum foundational reasons that led us to investigate the mechanisms of formation and combination of concepts in human reasoning, starting from the empirically observed deviations from classical logical and probabilistic structures. We then develop our quantum-theoretic perspective in Fock space which allows successful modeling of various sets of cognitive experiments collected by different scientists, including ourselves. In addition, we formulate a unified explanatory hypothesis for the presence of quantum structures in cognitive processes, and discuss our recent discovery of further quantum aspects in concept combinations, namely, 'entanglement' and 'indistinguishability'. We finally illustrate perspectives for future research.
OpenStreetCab: Exploiting Taxi Mobility Patterns in New York City to Reduce Commuter Costs
Venue: arXiv cs.SI 2015
Year: 2015

The rise of Uber as the global alternative taxi operator has attracted a lot of interest recently. Aside from the media headlines which discuss the new phenomenon, e.g. on how it has disrupted the traditional transportation industry, policy makers, economists, citizens and scientists have engaged in a discussion that is centred around the means to integrate the new generation of the sharing economy services in urban ecosystems. In this work, we aim to shed new light on the discussion, by taking advantage of a publicly available longitudinal dataset that describes the mobility of yellow taxis in New York City. In addition to movement, this data contains information on the fares paid by the taxi customers for each trip. As a result we are given the opportunity to provide a first head to head comparison between the iconic yellow taxi and its modern competitor, Uber, in one of the world's largest metropolitan centres. We identify situations when Uber X, the cheapest version of the Uber taxi service, tends to be more expensive than yellow taxis for the same journey. We also demonstrate how Uber's economic model effectively takes advantage of well known patterns in human movement. Finally, we take our analysis a step further by proposing a new mobile application that compares taxi prices in the city to facilitate traveller's taxi choices, hoping to ultimately to lead to a reduction of commuter costs. Our study provides a case on how big datasets that become public can improve urban services for consumers by offering the opportunity for transparency in economic sectors that lack up to date regulations.
Self-Adjusting Binary Search Trees: What Makes Them Tick?
Venue: arXiv cs.DS 2015
Year: 2015

Splay trees (Sleator and Tarjan) satisfy the so-called access lemma. Many of the nice properties of splay trees follow from it. What makes self-adjusting binary search trees (BSTs) satisfy the access lemma? After each access, self-adjusting BSTs replace the search path by a tree on the same set of nodes (the after-tree). We identify two simple combinatorial properties of the search path and the after-tree that imply the access lemma. Our main result (i) implies the access lemma for all minimally self-adjusting BST algorithms for which it was known to hold: splay trees and their generalization to the class of local algorithms (Subramanian, Georgakopoulos and Mc-Clurkin), as well as Greedy BST, introduced by Demaine et al. and shown to satisfy the access lemma by Fox, (ii) implies that BST algorithms based on "strict" depth-halving satisfy the access lemma, addressing an open question that was raised several times since 1985, and (iii) yields an extremely short proof for the O(log n log log n) amortized access cost for the path-balance heuristic (proposed by Sleator), matching the best known bound (Balasubramanian and Raman) to a lower-order factor. One of our combinatorial properties is locality. We show that any BST-algorithm that satisfies the access lemma via the sum-of-log (SOL) potential is necessarily local. The other property states that the sum of the number of leaves of the after-tree plus the number of side alternations in the search path must be at least a constant fraction of the length of the search path. We show that a weak form of this property is necessary for sequential access to be linear.
Comparing Network Structures of Commercial and Non-commercial Biohacking Online-communities
Venue: arXiv cs.SI 2015
Year: 2015

This paper compares two biohacking groups, Bulletproof Executive and DIYbio, whose distinct goals result in differences in social network structures, activities and entry points.
Environment Based Secure Transfer of Data in Wireless Sensor Networks
Venue: arXiv cs.CR 2015
Year: 2015

Most critical sensor readings (Top-k Monitoring) in environment monitoring system are important to many wireless sensor applications. In such applications, sensor nodes transmit the data continuously for a specific time period to the storage nodes. It is responsible for transferring the received results to the Authority on Top-k Query request from them. Dummy data's were added into the original text data to secure the data against adversary in case of hacking the sensor and storage nodes. If storage node gets hacked by adversary, false details will be sent to the authority. An effective technique named aggregate signature to validate the source of the message and also to protect the data against latest security attacks, cryptography technique combined with steganography has been introduced. Indexed based scheme for the database access has also been proposed, to validate the resources against availability before forwarding the data fetch request to storage nodes from Authority.
Modelling the Structure and Dynamics of Science Using Books
Venue: arXiv cs.DL 2015
Year: 2015

Scientific research is a major driving force in a knowledge based economy. Income, health and wellbeing depend on scientific progress. The better we understand the inner workings of the scientific enterprise, the better we can prompt, manage, steer, and utilize scientific progress. Diverse indicators and approaches exist to evaluate and monitor research activities, from calculating the reputation of a researcher, institution, or country to analyzing and visualizing global brain circulation. However, there are very few predictive models of science that are used by key decision makers in academia, industry, or government interested to improve the quality and impact of scholarly efforts. We present a novel 'bibliographic bibliometric' analysis which we apply to a large collection of books relevant for the modelling of science. We explain the data collection together with the results of the data analyses and visualizations. In the final section we discuss how the analysis of books that describe different modelling approaches can inform the design of new models of science.
Local variation of hashtag spike trains and popularity in Twitter
Venue: arXiv cs.SI 2015
Year: 2015

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamics, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media.
New Method for Public Key Distribution Based on Social Networks
Venue: arXiv cs.CR 2015
Year: 2015

The security of communication in everyday life becomes very important. On the other hand, all existing encryption protocols require from user additional knowledge end resources. In this paper we discuss the problem of public key distribution between interested parties. We propose to use a popular social media as a channel to publish public keys. This way of key distribution allows also easily connect owner of the key with real person institution (what is not always easy). Recognizing that the mobile devices become the main tool of communication, we present description of mobile application that uses proposed security methods.
Browserbite: Cross-Browser Testing via Image Processing
Venue: arXiv cs.SE 2015
Year: 2015

Cross-browser compatibility testing is concerned with identifying perceptible differences in the way a Web page is rendered across different browsers or configurations thereof. Existing automated cross-browser compatibility testing methods are generally based on Document Object Model (DOM) analysis, or in some cases, a combination of DOM analysis with screenshot capture and image processing. DOM analysis however may miss incompatibilities that arise not during DOM construction, but rather during rendering. Conversely, DOM analysis produces false alarms because different DOMs may lead to identical or sufficiently similar renderings. This paper presents a novel method for cross-browser testing based purely on image processing. The method relies on image segmentation to extract regions from a Web page and computer vision techniques to extract a set of characteristic features from each region. Regions extracted from a screenshot taken on a baseline browser are compared against regions extracted from the browser under test based on characteristic features. A machine learning classifier is used to determine if differences between two matched regions should be classified as an incompatibility. An evaluation involving 140 pages shows that the proposed method achieves an F-score exceeding 0.9, outperforming a state-of-the-art cross-browser testing tool based on DOM analysis.
Efficient Service Broker Policy For Large-Scale Cloud Environments
Venue: arXiv cs.DC 2015
Year: 2015

Algorithms, policies, and methodologies are necessary to achieve high user satisfaction and practical utilization in cloud computing by ensuring the efficient and fair allocation of every computing resource. Whenever a new job arrives in cloud environments, the service broker is responsible for selecting the data center that will execute that job. Selecting data centers serves an important function in enhancing the performance of a cloud environment. This study proposes a new service broker policy for large-scale cloud applications based on the round-robin algorithm. The proposed policy is implemented and evaluated using a CloudAnalyst simulator. It is then compared with three existing policies in terms of overall average response time by using different virtual machine load balancing algorithms. Simulation results show that the proposed policy improves the overall average response time relative to that of the other policies.
Cross platform app: a comparative study
Venue: arXiv cs.SE 2015
Year: 2015

The use of mobile applications is now so common that users now expect companies whose services which they consume already have an application to provide these services or a mobile version of your site, but this is not always simple to do or cheap. Thus, the hybrid development has emerged as a potential alternative to this need. The evolution of this new paradigm has taken the attention of researchers and companies as viable alternative to the mobile development. This paper shows how hybrid development can be an alternative for companies provide their services with a low investment and still offer a great service to their clients.
A Study on Optimized Resource Provisioning in Federated Cloud
Venue: arXiv cs.DC 2015
Year: 2015

Cloud computing changed the way of computing as utility services offered through public network. Selecting multiple providers for various computational requirements improves performance and minimizes cost of cloud services than choosing a single cloud provider. Federated cloud improves scalability, cost minimization, performance maximization, collaboration with other providers, multi-site deployment for fault tolerance and recovery, reliability and less energy consumption. Both providers and consumers could benefit from federated cloud where providers serve the consumers by satisfying Service Level Agreement, minimizing overall management and infrastructure cost; consumers get best services with less deployment cost and high availability. Efficient provisioning of resources to consumers in federated cloud is a challenging task. In this paper, the benefits of utilizing services from federated cloud, architecture with various coupling levels, different optimized resource provisioning methods and challenges associated with it are discussed and a comparative study is carried out over these aspects.