OpenRaiser/Intern-Atlas huggingface dataset:
When Do Envy-Free Allocations Exist?
Venue: arXiv cs.GT 2018
Year: 2018

We consider a fair division setting in which $m$ indivisible items are to be allocated among $n$ agents, where the agents have additive utilities and the agents' utilities for individual items are independently sampled from a distribution. Previous work has shown that an envy-free allocation is likely to exist when $m=Ω(n\log n)$ but not when $m=n+o(n)$, and left open the question of determining where the phase transition from non-existence to existence occurs. We show that, surprisingly, there is in fact no universal point of transition---instead, the transition is governed by the divisibility relation between $m$ and $n$. On the one hand, if $m$ is divisible by $n$, an envy-free allocation exists with high probability as long as $m\geq 2n$. On the other hand, if $m$ is not "almost" divisible by $n$, an envy-free allocation is unlikely to exist even when $m=Θ(n\log n/\log\log n)$.
Mobility-aware Caching Scheduling for Fog Computing in mmWave Band
Venue: arXiv cs.NI 2018
Year: 2018

As an extension of cloud computing, fog computing at the edge of networks provides low latency, location awareness, and real-time interactions. At the same time, millimeter wave (mmWave) communications are able to provide directional multi-gigabit transmission rates with large available bandwidth. Based on the user mobile trajectories in a region, several activity hotspots that users pass by frequently can be obtained. By caching popular content at the edge nodes near the hotspots, users can download the cached content directly at a short distance, and the user experience can be significantly improved. Considering multiple hotspots in a region, how to efficiently schedule the transmission for the caching at edge nodes becomes a key problem. In this paper, we focus on the problem of mobility aware transmission scheduling for caching at edge nodes near hotspots, and utilize multi-hop relaying and concurrent transmissions to achieve better performance. After formulating the optimal scheduling problem as a stochastic nonlinear mixed integer program, we propose a mobility aware caching scheduling scheme, called MHRC (Multi-Hop Relaying based Caching), where multi-hop D2D paths are established for edge nodes, and concurrent transmissions are exploited in the scheduling of caching at edge nodes. Extensive performance evaluation demonstrates MHRC achieves more than 1x higher expected cached data amount compared with state-of-the-art schemes.
Bibliometric evaluation of research performance: where do we stand?
Venue: arXiv cs.DL 2018
Year: 2018

This work provides a critical examination of the most popular bibliometric indicators and methodologies to assess the research performance of individuals and institutions. The aim is to raise the fog and make practitioners more aware of the inherent risks in do-it-myself practices, or cozy out-of-the-shelf solutions to the difficult question of how to evaluate research. The manuscript also proposes what we believe is the correct approach to bibliometric evaluation of research performance.
Probabilistic Parameterized Polynomial Time
Venue: arXiv cs.CC 2018
Year: 2018

We examine a parameterized complexity class for randomized computation where only the error bound and not the full runtime is allowed to depend more than polynomially on the parameter, based on a proposal by Kwisthout in [15,16]. We prove that this class, for which we propose the shorthand name PPPT, has a robust definition and is in fact equal to the intersection of the classes paraBPP and PP. This result is accompanied by a Cook-style proof of completeness for the corresponding promise class (under a suitable notion of reduction) for parameterized approximation versions of the inference problem in Bayesian networks, which is known to be PP-complete. With these definitions and results in place, we proceed by showing how it follows from this that derandomization is equivalent to efficient deterministic approximation methods for the inference problem. Furthermore, we observe as a straightforward application of a result due to Drucker in [8] that these problems cannot have polynomial size randomized kernels unless the polynomial hierarchy collapses to the third level. We conclude by indicating potential avenues for further exploration and application of this framework.
A sensitivity analysis of researchers' productivity rankings to the time of citation observation
Venue: arXiv cs.DL 2018
Year: 2018

In this work we investigate the sensitivity of individual researchers' productivity rankings to the time of citation observation. The analysis is based on observation of research products for the 2001-2003 triennium for all research staff of Italian universities in the hard sciences, with the year of citation observation varying from 2004 to 2008. The 2008 rankings list is assumed the most accurate, as citations have had the longest time to accumulate and thus represent the best possible proxy of impact. By comparing the rankings lists from each year against the 2008 benchmark we provide policy-makers and research organization managers a measure of trade-off between timeliness of evaluation execution and accuracy of performance rankings. The results show that with variation in the evaluation citation window there are variable rates of inaccuracy across the disciplines of researchers. The inaccuracy results negligible for Physics, Biology and Medicine.
Data Integration for Supporting Biomedical Knowledge Graph Creation at Large-Scale
Venue: arXiv cs.DB 2018
Year: 2018

In recent years, following FAIR and open data principles, the number of available big data including biomedical data has been increased exponentially. In order to extract knowledge, these data should be curated, integrated, and semantically described. Accordingly, several semantic integration techniques have been developed; albeit effective, they may suffer from scalability in terms of different properties of big data. Even scaled-up approaches may be highly costly because tasks of semantification, curation and integration are performed independently. In order to overcome these issues, we devise ConMap, a semantic integration approach which exploits knowledge encoded in ontology in order to describe mapping rules to perform these tasks at the same time. Experimental results performed on different data sets suggest that ConMap can significantly reduce the time required for knowledge graph creation by up to 70\% of the time that is consumed following a traditional approach.
Composing Optimization Techniques for Vertex-Centric Graph Processing via Communication Channels
Venue: arXiv cs.DC 2018
Year: 2018

Pregel's vertex-centric model allows us to implement many interesting graph algorithms, where optimization plays an important role in making it practically useful. Although many optimizations have been developed for dealing with different performance issues, it is hard to compose them together to optimize complex algorithms, where we have to deal with multiple performance issues at the same time. In this paper, we propose a new approach to composing optimizations, by making use of the \emph{channel} interface, as a replacement of Pregel's message passing and aggregator mechanism, which can better structure the communication in Pregel algorithms. We demonstrate that it is convenient to optimize a Pregel program by simply using a proper channel from the channel library or composing them to deal with multiple performance issues. We intensively evaluate the approach through many nontrivial examples. By adopting the channel interface, our system achieves an all-around performance gain for various graph algorithms. In particular, the composition of different optimizations makes the S-V algorithm 2.20x faster than the current best implementation.
The field-standardized average impact of national research systems compared to world average: the case of Italy
Venue: arXiv cs.DL 2018
Year: 2018

The study presents a time-series analysis of field-standardized average impact of Italian research compared to the world average. The approach is purely bibliometric, based on census of the full scientific production from all Italian public research organizations active in 2001-2006 (hard sciences only). The analysis is conducted both at sectorial level (aggregated, by scientific discipline and for single fields within disciplines) and at organizational level (by type of organization and for single organizations). The essence of the methodology should be replicable in all other national contexts. Its offers support to policy-makers and administrators for strategic analysis aimed at identifying strengths and weaknesses of national research systems and institutions.
Decoding Generic Visual Representations From Human Brain Activity using Machine Learning
Venue: arXiv cs.NE 2018
Year: 2018

Among the most impressive recent applications of neural decoding is the visual representation decoding, where the category of an object that a subject either sees or imagines is inferred by observing his/her brain activity. Even though there is an increasing interest in the aforementioned visual representation decoding task, there is no extensive study of the effect of using different machine learning models on the decoding accuracy. In this paper we provide an extensive evaluation of several machine learning models, along with different similarity metrics, for the aforementioned task, drawing many interesting conclusions. That way, this paper a) paves the way for developing more advanced and accurate methods and b) provides an extensive and easily reproducible baseline for the aforementioned decoding task.
A national-scale cross-time analysis of university research performance
Venue: arXiv cs.DL 2018
Year: 2018

Research policies in the more developed nations are ever more oriented towards the introduction of productivity incentives and competition mechanisms intended to increase efficiency in research institutions. Assessments of the effects of these policy interventions on public research activity often neglect the normal, inherent variation in the performance of research institutions over time. In this work, we propose a cross-time bibliometric analysis of research performance by all Italian universities in two consecutive periods (2001-2003 and 2004-2008) not affected by national policy interventions. Findings show that productivity and impact increased at the level of individual scientists. At the level of university, significant variation in the rank was observed.
SCAV'18: Report of the 2nd International Workshop on Safe Control of Autonomous Vehicles
Venue: arXiv cs.SE 2018
Year: 2018

This report summarizes the discussions, open issues, take-away messages, and conclusions of the 2nd SCAV workshop.
A human-editable Sign Language representation for software editing---and a writing system?
Venue: arXiv cs.CL 2018
Year: 2018

To equip SL with software properly, we need an input system to represent and manipulate signed contents in the same way that every day software allows to process written text. Refuting the claim that video is good enough a medium to serve the purpose, we propose to build a representation that is: editable, queryable, synthesisable and user-friendly---we define those terms upfront. The issue being functionally and conceptually linked to that of writing, we study existing writing systems, namely those in use for vocal languages, those designed and proposed for SLs, and more spontaneous ways in which SL users put their language in writing. Observing each paradigm in turn, we move on to propose a new approach to satisfy our goals of integration in software. We finally open the prospect of our proposition being used outside of this restricted scope, as a writing system in itself, and compare its properties to the other writing systems presented.
National research assessment exercises: a measure of the distortion of performance rankings when labor input is treated as uniform
Venue: arXiv cs.DL 2018
Year: 2018

Measuring the efficiency of scientific research activity presents critical methodological aspects, many of which have not been sufficiently studied. Although many studies have assessed the relation between quality and research productivity and academic rank, not much is known about the extent of distortion in national university performance rankings when academic rank and the other labor factors are not considered as a factor of normalization. This work presents a comparative analysis that aims to quantify the sensitivity of bibliometric rankings to the choice of input, with input considered as only the number of researchers on staff, or alternatively where their cost is also considered. The field of observation consists of all 69 Italian universities active in the hard sciences. Performance measures are based on the 81,000 publications produced during the 2004-2006 triennium by all 34,000 research staff, with analysis carried out at the level of individual disciplines, 187 in total. The effect of the switch from labor to cost seems to be minimal except for a few outliers.
Testing the trade-off between productivity and quality in research activities
Venue: arXiv cs.DL 2018
Year: 2018

In recent years there has been an increasingly pressing need for the evaluation of results from public sector research activity, particularly to permit the efficient allocation of ever scarcer resources. Many of the studies and evaluation exercises that have been conducted at the national and international level emphasize the quality dimension of research output, while neglecting that of productivity. This work is intended to test for the possible existence of correlation between quantity and quality of scientific production and determine whether the most productive researchers are also those that achieve results that are qualitatively better than those of their colleagues. The analysis proposed refers to the entire Italian university system and is based on the observation of production in the hard sciences by above 26,000 researchers in the period 2001 to 2005. The results show that the output of more productive researchers is superior in quality than that of less productive researchers. The relation between productivity and quality results as largely insensitive to the types of indicators or the test methods applied and also seems to differ little among the various disciplines examined.
Digital Signature Security in Data Communication
Venue: arXiv cs.CR 2018
Year: 2018

Authenticity of access in very information are very important in the current era of Internet-based technology, there are many ways to secure information from irresponsible parties with various security attacks, some of technique can use for defend attack from irresponsible parties are using steganography, cryptography or also use digital signatures. Digital signatures could be one of solution where the authenticity of the message will be verified to prove that the received message is the original message without any change, Ong-Schnorr-Shamir is the algorithm are used in this research and the experiment are perform on the digital signature scheme and the hidden channel scheme.
A Novel Compressed Sensing Technique for Traffic Matrix Estimation of Software Defined Cloud Networks
Venue: arXiv cs.NI 2018
Year: 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under-constrained and under-determined system of equations with a dynamic measurement matrix. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements.
In-the-wild Facial Expression Recognition in Extreme Poses
Venue: arXiv cs.CV 2018
Year: 2018

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.
An Optimal Itinerary Generation in a Configuration Space of Large Intellectual Agent Groups with Linear Logic
Venue: arXiv cs.AI 2018
Year: 2018

A group of intelligent agents which fulfill a set of tasks in parallel is represented first by the tensor multiplication of corresponding processes in a linear logic game category. An optimal itinerary in the configuration space of the group states is defined as a play with maximal total reward in the category. New moments also are: the reward is represented as a degree of certainty (visibility) of an agent goal, and the system goals are chosen by the greatest value corresponding to these processes in the system goal lattice.
De Bruijn graphs and powers of $3/2$
Venue: arXiv cs.FL 2018
Year: 2018

In this paper we consider the set ${\mathbb Z}^{\pmω}_{6}$ of two-way infinite words $ξ$ over the alphabet $\{0,1,2,3,4,5\}$ with the integer left part $\lfloorξ\rfloor$ and the fractional right part $\{ξ\}$ separated by a radix point. For such words, the operation of multiplication by integers and division by $6$ are defined as the column multiplication and division in base 6 numerical system. The paper develops a finite automata approach for analysis of sequences $\left (\left \lfloor ξ\left (\frac{3}{2} \right)^n \right \rfloor \right)_{n \in {\mathbb Z}}$ for the words $ξ\in {\mathbb Z}^{\pm ω}_{6}$ that have some common properties with $Z$-numbers in Mahler's $3/2$-problem. Such sequence of $Z$-words written under each other with the same digit positions in the same column is an infinite $2$-dimensional word over the alphabet ${\mathbb Z}_6$. The automata representation of the columns in the integer part of $2$-dimensional $Z$-words has the nice structural properties of the de Bruijn graphs. This way provides some sufficient conditions for the emptiness of the set of $Z$-numbers. Our approach has been initially inspirated by the proposition 2.5 in [1] where authors applies cellular automata for analysis of $\left(\left\{ξ\left(\frac{3}{2}\right)^n\right\} \right)_{n\in{\mathbb Z}}$, $ξ\in{\mathbb R}$.
Robust Bhattacharyya bound linear discriminant analysis through adaptive algorithm
Venue: arXiv cs.LG 2018
Year: 2018

In this paper, we propose a novel linear discriminant analysis criterion via the Bhattacharyya error bound estimation based on a novel L1-norm (L1BLDA) and L2-norm (L2BLDA). Both L1BLDA and L2BLDA maximize the between-class scatters which are measured by the weighted pairwise distances of class means and meanwhile minimize the within-class scatters under the L1-norm and L2-norm, respectively. The proposed models can avoid the small sample size (SSS) problem and have no rank limit that may encounter in LDA. It is worth mentioning that, the employment of L1-norm gives a robust performance of L1BLDA, and L1BLDA is solved through an effective non-greedy alternating direction method of multipliers (ADMM), where all the projection vectors can be obtained once for all. In addition, the weighting constants of L1BLDA and L2BLDA between the between-class and within-class terms are determined by the involved data set, which makes our L1BLDA and L2BLDA adaptive. The experimental results on both benchmark data sets as well as the handwritten digit databases demonstrate the effectiveness of the proposed methods.
First Order Alternation
Venue: arXiv cs.FL 2018
Year: 2018

We introduce first order alternating automata, a generalization of boolean alternating automata, in which transition rules are described by multisorted first order formulae, with states and internal variables given by uninterpreted predicate terms. The model is closed under union, intersection and complement, and its emptiness problem is undecidable, even for the simplest data theory of equality. To cope with this limitation, we develop an abstraction refinement semi-algorithm based on lazy annotation of the symbolic execution paths with interpolants, obtained by applying (i) quantifier elimination with witness term generation and (ii) Lyndon interpolation in the quantifier-free data theory with uninterpreted predicate symbols. This provides a method for checking inclusion of timed and finite-memory register automata, and emptiness of quantified predicate automata, previously used in the verification of parameterized concurrent programs, composed of replicated threads, with a shared-memory communication model.
Architecture of Distributed Data Storage for Astroparticle Physics
Venue: arXiv cs.DC 2018
Year: 2018

For the successful development of the astrophysics and, accordingly, for obtaining more complete knowledge of the Universe, it is extremely important to combine and comprehensively analyze information of various types (e.g., about charged cosmic particles, gamma rays, neutrinos, etc.) obtained by using divers large-scale experimental setups located throughout the world. It is obvious that all kinds of activities must be performed continually across all stages of the data life cycle to help support effective data management, in particular, the collection and storage of data, its processing and analysis, refining the physical model, making preparations for publication, and data reprocessing taking refinement into account. In this paper we present a general approach to construction and the architecture of a system to be able to collect, store, and provide users' access to astrophysical data. We also suggest a new approach to the construction of a metadata registry based on the blockchain technology.