OpenRaiser/Intern-Atlas huggingface dataset:
MOBISPA: A Reference Framework for Mobile as a Personal Assistant
Venue: arXiv cs.HC 2015
Year: 2015

Mobile is taking center stage and becoming the device of preference for all aspects of communication because of our increasingly on the go lifestyles. With this the demands on mobile capability to execute increasingly complex operations are also on the rise. However, despite improvements in device computing power in the last couple of years a mobile device continues to have limitations. Mobile driven everyday use cases are increasingly raising expectations that rest on mobile technologies that are still evolving. A number of fragmented approaches and solutions have been created that address various requirements unique to mobility, however there is a lack of a single framework that serves as a unifying reference for industry and solution architectures. The paper addresses this concern through the specification of a comprehensive reference framework for mobility that is generic and vendor neutral.
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Venue: arXiv cs.AI 2015
Year: 2015

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.
Neural NILM: Deep Neural Networks Applied to Energy Disaggregation
Venue: arXiv cs.NE 2015
Year: 2015

Energy disaggregation estimates appliance-by-appliance electricity consumption from a single meter that measures the whole home's electricity demand. Recently, deep neural networks have driven remarkable improvements in classification performance in neighbouring machine learning fields such as image classification and automatic speech recognition. In this paper, we adapt three deep neural network architectures to energy disaggregation: 1) a form of recurrent neural network called `long short-term memory' (LSTM); 2) denoising autoencoders; and 3) a network which regresses the start time, end time and average power demand of each appliance activation. We use seven metrics to test the performance of these algorithms on real aggregate power data from five appliances. Tests are performed against a house not seen during training and against houses seen during training. We find that all three neural nets achieve better F1 scores (averaged over all five appliances) than either combinatorial optimisation or factorial hidden Markov models and that our neural net algorithms generalise well to an unseen house.
Pressure Fluctuations in Natural Gas Networks caused by Gas-Electric Coupling
Venue: arXiv cs.SY 2015
Year: 2015

The development of hydraulic fracturing technology has dramatically increased the supply and lowered the cost of natural gas in the United States, driving an expansion of natural gas-fired generation capacity in several electrical inter-connections. Gas-fired generators have the capability to ramp quickly and are often utilized by grid operators to balance intermittency caused by wind generation. The time-varying output of these generators results in time-varying natural gas consumption rates that impact the pressure and line-pack of the gas network. As gas system operators assume nearly constant gas consumption when estimating pipeline transfer capacity and for planning operations, such fluctuations are a source of risk to their system. Here, we develop a new method to assess this risk. We consider a model of gas networks with consumption modeled through two components: forecasted consumption and small spatio-temporarily varying consumption due to the gas-fired generators being used to balance wind. While the forecasted consumption is globally balanced over longer time scales, the fluctuating consumption causes pressure fluctuations in the gas system to grow diffusively in time with a diffusion rate sensitive to the steady but spatially-inhomogeneous forecasted distribution of mass flow. To motivate our approach, we analyze the effect of fluctuating gas consumption on a model of the Transco gas pipeline that extends from the Gulf of Mexico to the Northeast of the United States.
Supervised Collective Classification for Crowdsourcing
Venue: arXiv cs.SI 2015
Year: 2015

Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainly unsupervised methods that are unaware of the quality of crowdsourced data. In this paper, we propose a supervised collective classification algorithm that aims to identify reliable labelers from the training data (e.g., items with known labels). The reliability (i.e., weighting factor) of each labeler is determined via a saddle point algorithm. The results on several crowdsourced data show that supervised methods can achieve better classification accuracy than unsupervised methods, and our proposed method outperforms other algorithms.
Improved Answer-Set Programming Encodings for Abstract Argumentation
Venue: arXiv cs.AI 2015
Year: 2015

The design of efficient solutions for abstract argumentation problems is a crucial step towards advanced argumentation systems. One of the most prominent approaches in the literature is to use Answer-Set Programming (ASP) for this endeavor. In this paper, we present new encodings for three prominent argumentation semantics using the concept of conditional literals in disjunctions as provided by the ASP-system clingo. Our new encodings are not only more succinct than previous versions, but also outperform them on standard benchmarks.
Social Data Offloading in D2D-Enhanced Cellular Networks by Network Formation Games
Venue: arXiv cs.GT 2015
Year: 2015

Recently, cellular networks are severely overloaded by social-based services, such as YouTube, Facebook and Twitter, in which thousands of clients subscribe a common content provider (e.g., a popular singer) and download his/her content updates all the time. Offloading such traffic through complementary networks, such as a delay tolerant network formed by device-to-device (D2D) communications between mobile subscribers, is a promising solution to reduce the cellular burdens. In the existing solutions, mobile users are assumed to be volunteers who selfishlessly deliver the content to every other user in proximity while moving. However, practical users are selfish and they will evaluate their individual payoffs in the D2D sharing process, which may highly influence the network performance compared to the case of selfishless users. In this paper, we take user selfishness into consideration and propose a network formation game to capture the dynamic characteristics of selfish behaviors. In the proposed game, we provide the utility function of each user and specify the conditions under which the subscribers are guaranteed to converge to a stable network. Then, we propose a practical network formation algorithm in which the users can decide their D2D sharing strategies based on their historical records. Simulation results show that user selfishness can highly degrade the efficiency of data offloading, compared with ideal volunteer users. Also, the decrease caused by user selfishness can be highly affected by the cost ratio between the cellular transmission and D2D transmission, the access delays, and mobility patterns.
In Need of Creative Mobile Service Ideas? Forget Adults and Ask Young Children
Venue: arXiv cs.CY 2015
Year: 2015

It is well acknowledged that innovation is a key success factor in mobile service domain. Having creative ideas is the first critical step in the innovation process. Many studies suggest that customers are a valuable source of creative ideas. However, the literature also shows that adults may be constrained by existing technology frames, which are known to hinder creativity. Instead young children (aged 7-12) are considered digital natives yet are free from existing technology frames. This led us to study them as a potential source for creative mobile service ideas. A set of 41,000 mobile ideas obtained from a research project in 2006 granted us a unique opportunity to study the mobile service ideas from young children. We randomly selected two samples of ideas (N=400 each), one contained the ideas from young children, the other from adults (aged 17-50). These ideas were evaluated by several evaluators using an existing creativity framework. The results show that the mobile service ideas from the young children are significantly more original, transformational, implementable, and relevant than those from the adults. Therefore, this study shows that young children are better sources of novel and quality ideas than adults in the mobile services domain. This study bears significant contributions to the creativity and innovation research. It also indicates a new and valuable source for the companies that seek for creative ideas for innovative products and services.
Modelling and Analysis Network Security -- a PVCCS approach
Venue: arXiv cs.CR 2015
Year: 2015

In this work, we propose a probabilistic value-passing CCS (Calculus of Communicating System) approach to model and analyze a typical network security scenario with one attacker and one defender. By minimizing this model with respect to probabilistic bisimulation and abstracting it through graph-theoretic methods, two algorithms based on backward induction are designed to compute Nash Equilibrium strategy and Social Optimal strategy respectively. For each algorithm, the correctness is proved and an implementation is realized. Finally, this approach is illustrated by a detailed case study.
Weak upper topologies and duality for cones
Venue: arXiv cs.LO 2015
Year: 2015

In functional analysis it is well known that every linear functional defined on the dual of a locally convex vector space which is continuous for the weak topology is the evaluation at a uniquely determined point of the given vector space. M. Schroeder and A. Simpson have obtained a similar result for lower semicontinuous linear functionals on the cone of all Scott-continuous valuations on a topological space endowed with the weak upper topology, an asymmetric version of the weak topology. This result has given rise to several proofs, originally by the Schroeder and Simpson themselves and, more recently, by the author of these Notes and by J. Goubault-Larrecq. The proofs developed from very technical arguments to more and more conceptual ones. The present Note continues on this line, presenting a conceptual approach inspired by classical functional analysis which may prove useful in other situations.
Memristive integrative sensors for neuronal activity
Venue: arXiv cs.ET 2015
Year: 2015

The advent of advanced neuronal interfaces offers great promise for linking brain functions to electronics. A major bottleneck in achieving this is real-time processing of big data that imposes excessive requirements on bandwidth, energy and computation capacity; limiting the overall number of bio-electronic links. Here, we present a novel monitoring system concept that exploits the intrinsic properties of memristors for processing neural information in real time. We demonstrate that the inherent voltage thresholds of solid-state TiOx memristors can be useful for discriminating significant neural activity, i.e. spiking events, from noise. When compared with a multi-dimensional, principal component feature space threshold detector, our system is capable of recording the majority of significant events, without resorting to computationally heavy off-line processing. We also show a memristive integrating sensing array that discriminates neuronal activity recorded in-vitro. We prove that information on spiking event amplitude is simultaneously transduced and stored as non-volatile resistive state transitions, allowing for more efficient data compression, demonstrating the memristors' potential for building scalable, yet energy efficient on-node processors for big data.
Multi-objective analysis of computational models
Venue: arXiv cs.NE 2015
Year: 2015

Computational models are of increasing complexity and their behavior may in particular emerge from the interaction of different parts. Studying such models becomes then more and more difficult and there is a need for methods and tools supporting this process. Multi-objective evolutionary algorithms generate a set of trade-off solutions instead of a single optimal solution. The availability of a set of solutions that have the specificity to be optimal relative to carefully chosen objectives allows to perform data mining in order to better understand model features and regularities. We review the corresponding work, propose a unifying framework, and highlight its potential use. Typical questions that such a methodology allows to address are the following: what are the most critical parameters of the model? What are the relations between the parameters and the objectives? What are the typical behaviors of the model? Two examples are provided to illustrate the capabilities of the methodology. The features of a flapping-wing robot are thus evaluated to find out its speed-energy relation, together with the criticality of its parameters. A neurocomputational model of the Basal Ganglia brain nuclei is then considered and its most salient features according to this methodology are presented and discussed.
Nonexistence of two classes of generalized bent functions
Venue: arXiv cs.IT 2015
Year: 2015

We obtain new nonexistence results of generalized bent functions from $\{Z^n}_q$ to $\Z_q$ (called type $[n,q]$) in the case that there exist cyclotomic integers in $ \Z[ζ_{q}]$ with absolute value $q^{\frac{n}{2}}$. This result generalize the previous two scattered nonexistence results $[n,q]=[1,2\times7]$ of Pei \cite{Pei} and $[3,2\times 23^e]$ of Jiang-Deng \cite{J-D} to a generalized class. In the last section, we remark that this method can apply to the GBF from $\Z^n_2$ to $\Z_m$.
Exploratory Analysis of Quality Practices in Open Source Domain
Venue: arXiv cs.SE 2015
Year: 2015

Software quality assurance has been a heated topic for several decades, but relatively few analyses were performed on open source software (OSS). As OSS has become very popular in our daily life, many researchers have been keen on the quality practices in this area. Although quality management presents distinct patterns compared with those in closed-source software development, some widely used OSS products have been implemented. Therefore, quality assurance of OSS projects has attracted increased research focuses. In this paper, a survey is conducted to reveal the general quality practices in open source communities. Exploratory analysis has been carried out to disclose those quality related activities. The results are compared with those from closed-source environments and the distinguished features of the quality assurance in OSS projects have been confirmed. Moreover, this study suggests potential directions for OSS developers to follow.
A Denotational Semantics for Equilibrium Logic
Venue: arXiv cs.LO 2015
Year: 2015

In this paper we provide an alternative semantics for Equilibrium Logic and its monotonic basis, the logic of Here-and-There (also known as Gödel's G3 logic) that relies on the idea of "denotation" of a formula, that is, a function that collects the set of models of that formula. Using the three-valued logic G3 as a starting point and an ordering relation (for which equilibrium/stable models are minimal elements) we provide several elementary operations for sets of interpretations. By analysing structural properties of the denotation of formulas, we show some expressiveness results for G3 such as, for instance, that conjunction is not expressible in terms of the other connectives. Moreover, the denotational semantics allows us to capture the set of equilibrium models of a formula with a simple and compact set expression. We also use this semantics to provide several formal definitions for entailment relations that are usual in the literature, and further introduce a new one called "strong entailment". We say that $α$ strongly entails $β$ when the equilibrium models of $α\wedge γ$ are also equilibrium models of $β\wedge γ$ for any context $γ$. We also provide a characterisation of strong entailment in terms of the denotational semantics, and give an example of a sufficient condition that can be applied in some cases.
An Empirical Study on the Procedure to Derive Software Quality Estimation Models
Venue: arXiv cs.SE 2015
Year: 2015

Software quality assurance has been a heated topic for several decades. If factors that influence software quality can be identified, they may provide more insight for better software development management. More precise quality assurance can be achieved by employing resources according to accurate quality estimation at the early stages of a project. In this paper, a general procedure is proposed to derive software quality estimation models and various techniques are presented to accomplish the tasks in respective steps. Several statistical techniques together with machine learning method are utilized to verify the effectiveness of software metrics. Moreover, a neuro-fuzzy approach is adopted to improve the accuracy of the estimation model. This procedure is carried out based on data from the ISBSG repository to present its empirical value.
A Study of Morphological Filtering Using Graph and Hypergraphs
Venue: arXiv cs.CV 2015
Year: 2015

Mathematical morphology (MM) helps to describe and analyze shapes using set theory. MM can be effectively applied to binary images which are treated as sets. Basic morphological operators defined can be used as an effective tool in image processing. Morphological operators are also developed based on graph and hypergraph. These operators have found better performance and applications in image processing. Bino et al. [8], [9] developed the theory of morphological operators on hypergraph. A hypergraph structure is considered and basic morphological operation erosion/dilation is defined. Several new operators opening/closing and filtering are also defined on the hypergraphs. Hypergraph based filtering have found comparatively better performance with morphological filters based on graph. In this paper we evaluate the effectiveness of hypergraph based ASF on binary images. Experimental results shows that hypergraph based ASF filters have outperformed graph based ASF.
Making sense of randomness: an approach for fast recovery of compressively sensed signals
Venue: arXiv cs.IT 2015
Year: 2015

In compressed sensing (CS) framework, a signal is sampled below Nyquist rate, and the acquired compressed samples are generally random in nature. However, for efficient estimation of the actual signal, the sensing matrix must preserve the relative distances among the acquired compressed samples. Provided this condition is fulfilled, we show that CS samples will preserve the envelope of the actual signal even at different compression ratios. Exploiting this envelope preserving property of CS samples, we propose a new fast dictionary learning (DL) algorithm which is able to extract prototype signals from compressive samples for efficient sparse representation and recovery of signals. These prototype signals are orthogonal intrinsic mode functions (IMFs) extracted using empirical mode decomposition (EMD), which is one of the popular methods to capture the envelope of a signal. The extracted IMFs are used to build the dictionary without even comprehending the original signal or the sensing matrix. Moreover, one can build the dictionary on-line as new CS samples are available. In particularly, to recover first $L$ signals ($\in\mathbb{R}^n$) at the decoder, one can build the dictionary in just $\mathcal{O}(nL\log n)$ operations, that is far less as compared to existing approaches. The efficiency of the proposed approach is demonstrated experimentally for recovery of speech signals.
Range Predecessor and Lempel-Ziv Parsing
Venue: arXiv cs.DS 2015
Year: 2015

The Lempel-Ziv parsing of a string (LZ77 for short) is one of the most important and widely-used algorithmic tools in data compression and string processing. We show that the Lempel-Ziv parsing of a string of length $n$ on an alphabet of size $σ$ can be computed in $O(n\log\logσ)$ time ($O(n)$ time if we allow randomization) using $O(n\logσ)$ bits of working space; that is, using space proportional to that of the input string in bits. The previous fastest algorithm using $O(n\logσ)$ space takes $O(n(\logσ+\log\log n))$ time. We also consider the important rightmost variant of the problem, where the goal is to associate with each phrase of the parsing its most recent occurrence in the input string. We solve this problem in $O(n(1 + (\logσ/\sqrt{\log n}))$ time, using the same working space as above. The previous best solution for rightmost parsing uses $O(n(1+\logσ/\log\log n))$ time and $O(n\log n)$ space. As a bonus, in our solution for rightmost parsing we provide a faster construction method for efficient 2D orthogonal range reporting, which is of independent interest.
On Liveness of Dynamic Storage
Venue: arXiv cs.DC 2015
Year: 2015

Dynamic distributed storage algorithms such as DynaStore, Reconfigurable Paxos, RAMBO, and RDS, do not ensure liveness (wait-freedom) in asynchronous runs with infinitely many reconfigurations. We prove that this is inherent for asynchronous dynamic storage algorithms, including ones that use $Ω$ or $\diamond S$ oracles. Our result holds even if only one process may fail, provided that machines that were successfully removed from the system's configuration may be switched off by an administrator. Intuitively, the impossibility relies on the fact that a correct process can be suspected to have failed at any time, i.e., its failure is indistinguishable to other processes from slow delivery of its messages, and so the system should be able to reconfigure without waiting for this process to complete its pending operations. To circumvent this result, we define a dynamic eventually perfect failure detector, and present an algorithm that uses it to emulate wait-free dynamic atomic storage (with no restrictions on reconfiguration rate). Together, our results thus draw a sharp line between oracles like $Ω$ and $\diamond S$, which allow some correct process to continue to be suspected forever, and a dynamic eventually perfect one, which does not.
Political Bots and the Manipulation of Public Opinion in Venezuela
Venue: arXiv cs.SI 2015
Year: 2015

Social and political bots have a small but strategic role in Venezuelan political conversations. These automated scripts generate content through social media platforms and then interact with people. In this preliminary study on the use of political bots in Venezuela, we analyze the tweeting, following and retweeting patterns for the accounts of prominent Venezuelan politicians and prominent Venezuelan bots. We find that bots generate a very small proportion of all the traffic about political life in Venezuela. Bots are used to retweet content from Venezuelan politicians but the effect is subtle in that less than 10 percent of all retweets come from bot-related platforms. Nonetheless, we find that the most active bots are those used by Venezuela's radical opposition. Bots are pretending to be political leaders, government agencies and political parties more than citizens. Finally, bots are promoting innocuous political events more than attacking opponents or spreading misinformation.