OpenRaiser/Intern-Atlas huggingface dataset:
Secure Content Distribution in Vehicular Networks
Venue: arXiv cs.IT 2016
Year: 2016

Dedicated short range communication (DSRC) relies on secure distribution to vehicles of a certificate revocation list (CRL) for enabling security protocols. CRL distribution utilizing vehicle-to-vehicle (V2V) communications is preferred to an infrastructure-only approach. One approach to V2V CRL distribution, using rateless coding at the source and forwarding at vehicle relays is vulnerable to a pollution attack in which a few malicious vehicles forward incorrect packets which then spread through the network leading to denial-of-service. This paper develops a new scheme called Precode-and-Hash that enables efficient packet verification before forwarding thereby preventing the pollution attack. In contrast to rateless codes, it utilizes a fixed low-rate precode and random selection of packets from the set of precoded packets. The fixed precode admits efficient hash verification of all encoded packets. Specifically, hashes are computed for all precoded packets and sent securely using signatures. We analyze the performance of the Precode-and-Hash scheme for a multi-hop line network and provide simulation results for several schemes in a more realistic vehicular model.
Multiset Theories of Cardinality-based Feature Diagrams
Venue: arXiv cs.SE 2016
Year: 2016

Software product line engineering is a very common method for designing complex software systems. Feature modeling is the most common approach to specify product lines. The main part of a feature model is a special tree of features called a feature diagram. Cardinality-based feature diagrams provide the most expressive tool among the current feature diagram languages. The most common characterization of the semantics of a cardinality-based diagram is the set of flat multisets over features satisfying the constraints. However, this semantics provides a poor abstract view of the diagram. We address this problem by proposing another multiset theory for the cardinality-based feature diagram, called the hierarchical theory of the diagram. We show that this semantics captures all information of the diagram so that one can retrieve the diagram from its hierarchical semantics. We also characterize sets of multisets, which can provide a hierarchical semantics of some diagrams.
Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization
Venue: arXiv cs.CV 2016
Year: 2016

In this paper, we propose a novel approach to hyperspectral image super-resolution by modeling the global spatial-and-spectral correlation and local smoothness properties over hyperspectral images. Specifically, we utilize the tensor nuclear norm and tensor folded-concave penalty functions to describe the global spatial-and-spectral correlation hidden in hyperspectral images, and 3D total variation (TV) to characterize the local spatial-and-spectral smoothness across all hyperspectral bands. Then, we develop an efficient algorithm for solving the resulting optimization problem by combing the local linear approximation (LLA) strategy and alternative direction method of multipliers (ADMM). Experimental results on one hyperspectral image dataset illustrate the merits of the proposed approach.
Asymmetric Peer Influence in Smartphone Adoption in a Large Mobile Network
Venue: arXiv cs.SI 2016
Year: 2016

Understanding adoption patterns of smartphones is of vital importance to telecommunication managers in today's highly dynamic mobile markets. In this paper, we leverage the network structure and specific position of each individual in the social network to account for and measure the potential heterogeneous role of peer influence in the adoption of the iPhone 3G. We introduce the idea of core/periphery as a meso-level organizational principle to study the social network, which complements the use of centrality measures derived from either global network properties (macro-level) or from each individual's local social neighbourhood (micro-level). Using millions of call detailed records from a mobile network operator in one country for a period of eleven months, we identify overlapping social communities as well as core and periphery individuals in the network. Our empirical analysis shows that core users exert more influence on periphery users than vice versa. Our findings provide important insights to help identify influential members in the social network, which is potentially useful to design optimal targeting strategies to improve current network-based marketing practices.
Bipartite Perfect Matching is in quasi-NC
Venue: arXiv cs.CC 2016
Year: 2016

We show that the bipartite perfect matching problem is in quasi-NC$^2$. That is, it has uniform circuits of quasi-polynomial size $n^{O(\log n)}$, and $O(log^2 n)$ depth. Previously, only an exponential upper bound was known on the size of such circuits with poly-logarithmic depth. We obtain our result by an almost complete derandomization of the famous Isolation Lemma when applied to yield an efficient randomized parallel algorithm for the bipartite perfect matching problem.
Reducing Performance Impact of DRAM Refresh by Parallelizing Refreshes with Accesses
Venue: arXiv cs.AR 2016
Year: 2016

Modern DRAM cells are periodically refreshed to prevent data loss due to leakage. Commodity DDR DRAM refreshes cells at the rank level. This degrades performance significantly because it prevents an entire rank from serving memory requests while being refreshed. DRAM designed for mobile platforms, LPDDR DRAM, supports an enhanced mode, called per-bank refresh, that refreshes cells at the bank level. This enables a bank to be accessed while another in the same rank is being refreshed, alleviating part of the negative performance impact of refreshes. However, there are two shortcomings of per-bank refresh. First, the per-bank refresh scheduling scheme does not exploit the full potential of overlapping refreshes with accesses across banks because it restricts the banks to be refreshed in a sequential round-robin order. Second, accesses to a bank that is being refreshed have to wait. To mitigate the negative performance impact of DRAM refresh, we propose two complementary mechanisms, DARP (Dynamic Access Refresh Parallelization) and SARP (Subarray Access Refresh Parallelization). The goal is to address the drawbacks of per-bank refresh by building more efficient techniques to parallelize refreshes and accesses within DRAM. First, instead of issuing per-bank refreshes in a round-robin order, DARP issues per-bank refreshes to idle banks in an out-of-order manner. Furthermore, DARP schedules refreshes during intervals when a batch of writes are draining to DRAM. Second, SARP exploits the existence of mostly-independent subarrays within a bank. With minor modifications to DRAM organization, it allows a bank to serve memory accesses to an idle subarray while another subarray is being refreshed. Extensive evaluations show that our mechanisms improve system performance and energy efficiency compared to state-of-the-art refresh policies and the benefit increases as DRAM density increases.
Average Secrecy Capacity of Free-Space Optical Communication Systems with On-Off Keying Modulation and Threshold Detection
Venue: arXiv cs.IT 2016
Year: 2016

This paper considers secure communication over free-space optical (FSO) links suffering from turbulence-induced fading. In particular, we study the average secrecy capacity of applying physical layer security to achieve security in an FSO communication system with binary-level on-off keying intensity modulation and threshold detection, a widely used system in FSO communication. We first define the instantaneous secrecy capacity for our system and then provide a lower bound of it, which is achieved based on a simple design principle for practical applications and yields a simpler equation. We next derive a general expression of the average secrecy capacity and the corresponding lower bound based on bit error probabilities. Finally, numerical analysis is conducted for the special case of the correlated log-normal fading model to show the impacts of fading and channel correlation on the average secrecy capacity.
Reference Architecture for SMAC solutions
Venue: arXiv cs.NI 2016
Year: 2016

Web and internet computing is evolving into a combination of social media, mobile, analytics and cloud (SMAC) solutions. There is a need for an integrated approach when developing solutions that address web scale requirements with technologies that enable SMAC solutions. This paper presents an architecture model for the integrated approach that can form the basis for solutions and result in reuse, integration and agility for the business and IT in an enterprise.
On detecting and quantification of randomness for one-sided sequences
Venue: arXiv cs.IT 2016
Year: 2016

The paper studies discrete time processes and their predictability and randomness in deterministic pathwise setting, without using probabilistic assumptions on the ensemble. We suggest some approaches to quantification of randomness based on frequency analysis of two-sided and one-sided sequences. In addition, the paper suggests an extension of the notion of bandlimitiness on one-sided sequences and a procedure allowing to represent an one-sided sequence as a sum of left-bandlimited and predictable sequences and a non-reducible noise.
On Layered Erasure Interference Channels without CSI at Transmitters
Venue: arXiv cs.IT 2016
Year: 2016

This paper studies a layered erasure model for two-user interference channels, which can be viewed as a simplified version of Gaussian fading interference channel. It is assumed that channel state information~(CSI) is only available at receivers but not at transmitters. Under such assumption, an outer bound is derived for the capacity region of such interference channel. The new outer bound is tight in many circumstances. For the remaining open cases, the outer bound extends previous results.
Experimental Evaluation of Large Scale WiFi Multicast Rate Control
Venue: arXiv cs.NI 2016
Year: 2016

WiFi multicast to very large groups has gained attention as a solution for multimedia delivery in crowded areas. Yet, most recently proposed schemes do not provide performance guarantees and none have been tested at scale. To address the issue of providing high multicast throughput with performance guarantees, we present the design and experimental evaluation of the Multicast Dynamic Rate Adaptation (MuDRA) algorithm. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. MuDRA relies on feedback from some nodes collected via a light-weight protocol and dynamically adjusts the rate adaptation response time. Our experimental evaluation of MuDRA on the ORBIT testbed with over 150 nodes shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of receivers while meeting quality requirements. MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality.
QUOTE: "Querying" Users as Oracles in Tag Engines - A Semi-Supervised Learning Approach to Personalized Image Tagging
Venue: arXiv cs.IR 2016
Year: 2016

One common trend in image tagging research is to focus on visually relevant tags, and this tends to ignore the personal and social aspect of tags, especially on photoblogging websites such as Flickr. Previous work has correctly identified that many of the tags that users provide on images are not visually relevant (i.e. representative of the salient content in the image) and they go on to treat such tags as noise, ignoring that the users chose to provide those tags over others that could have been more visually relevant. Another common assumption about user generated tags for images is that the order of these tags provides no useful information for the prediction of tags on future images. This assumption also tends to define usefulness in terms of what is visually relevant to the image. For general tagging or labeling applications that focus on providing visual information about image content, these assumptions are reasonable, but when considering personalized image tagging applications, these assumptions are at best too rigid, ignoring user choice and preferences. We challenge the aforementioned assumptions, and provide a machine learning approach to the problem of personalized image tagging with the following contributions: 1.) We reformulate the personalized image tagging problem as a search/retrieval ranking problem, 2.) We leverage the order of tags, which does not always reflect visual relevance, provided by the user in the past as a cue to their tag preferences, similar to click data, 3.) We propose a technique to augment sparse user tag data (semi-supervision), and 4.) We demonstrate the efficacy of our method on a subset of Flickr images, showing improvement over previous state-of-art methods.
New Error Correcting Codes for Informed Receivers
Venue: arXiv cs.IT 2016
Year: 2016

We construct error correcting codes for jointly transmitting a finite set of independent messages to an 'informed receiver' which has prior knowledge of the values of some subset of the messages as side information. The transmitter is oblivious to the message subset already known to the receiver and performs encoding in such a way that any possible side information can be used efficiently at the decoder. We construct and identify several families of algebraic error correcting codes for this problem using cyclic and maximum distance separable (MDS) codes. The proposed codes are of short block length, many of them provide optimum or near-optimum error correction capabilities and guarantee larger minimum distances than known codes of similar parameters for informed receivers. The constructed codes are also useful as error correcting codes for index coding when the transmitter does not know the side information available at the receivers.
Elliptic Curve Multiset Hash
Venue: arXiv cs.CR 2016
Year: 2016

A homomorphic, or incremental, multiset hash function, associates a hash value to arbitrary collections of objects (with possible repetitions) in such a way that the hash of the union of two collections is easy to compute from the hashes of the two collections themselves: it is simply their sum under a suitable group operation. In particular, hash values of large collections can be computed incrementally and/or in parallel. Homomorphic hashing is thus a very useful primitive with applications ranging from database integrity verification to streaming set/multiset comparison and network coding. Unfortunately, constructions of homomorphic hash functions in the literature are hampered by two main drawbacks: they tend to be much longer than usual hash functions at the same security level (e.g. to achieve a collision resistance of 2^128, they are several thousand bits long, as opposed to 256 bits for usual hash functions), and they are also quite slow. In this paper, we introduce the Elliptic Curve Multiset Hash (ECMH), which combines a usual bit string-valued hash function like BLAKE2 with an efficient encoding into binary elliptic curves to overcome both difficulties. On the one hand, the size of ECMH digests is essentially optimal: 2m-bit hash values provide O(2^m) collision resistance. On the other hand, we demonstrate a highly-efficient software implementation of ECMH, which our thorough empirical evaluation shows to be capable of processing over 3 million set elements per second on a 4 GHz Intel Haswell machine at the 128-bit security level---many times faster than previous practical methods.
Online Community Detection by Using Nearest Hubs
Venue: arXiv cs.SI 2016
Year: 2016

Community and cluster detection is a popular field of social network analysis. Most algorithms focus on static graphs or series of snapshots. In this paper we present an algorithm, which detects communities in dynamic graphs. The method is based on shortest paths to high-connected nodes, so called hubs. Due to local message passing we can update the clustering results with low computational power. The presented algorithm is compared with other for some static social networks. The reached modularity is not as high as the Louvain method, but even higher then spectral clustering. For large-scale real-world datasets with given ground truth, we could reconstruct most of the given community structure. The advantage of the algorithm is the good performance in dynamic scenarios.
On Renyi Entropy Power Inequalities
Venue: arXiv cs.IT 2016
Year: 2016

This paper gives improved Rényi entropy power inequalities (R-EPIs). Consider a sum $S_n = \sum_{k=1}^n X_k$ of $n$ independent continuous random vectors taking values on $\mathbb{R}^d$, and let $α\in [1, \infty]$. An R-EPI provides a lower bound on the order-$α$ Rényi entropy power of $S_n$ that, up to a multiplicative constant (which may depend in general on $n, α, d$), is equal to the sum of the order-$α$ Rényi entropy powers of the $n$ random vectors $\{X_k\}_{k=1}^n$. For $α=1$, the R-EPI coincides with the well-known entropy power inequality by Shannon. The first improved R-EPI is obtained by tightening the recent R-EPI by Bobkov and Chistyakov which relies on the sharpened Young's inequality. A further improvement of the R-EPI also relies on convex optimization and results on rank-one modification of a real-valued diagonal matrix.
Orthogonal Chirp Division Multiplexing
Venue: arXiv cs.IT 2016
Year: 2016

Chirp waveform plays a significant role in radar and communication systems for its ability of pulse compression and spread spectrum. This paper presents a principle of orthogonally multiplexing a bank of linear chirp waveforms within the same bandwidth. The amplitude and phase of the chirps are modulated for information communication. As Fourier trans-form is the basis for orthogonal frequency division multiplexing (OFDM), Fresnel transform underlies the proposed orthogonal chirp division multiplexing (OCDM). Digital implementa-tion of the OCDM system using discrete Fresnel transform is proposed. Based on the con-volution theorem of the Fresnel transform, the transmission of the OCDM signal is analyzed under the linear time-invariant or quasi-static channel with additive noise, which can gener-alize typical linear transmission channels. Based on the eigen-decomposition of Fresnel transform, efficient digital signal processing algorithm is proposed for compensating chan-nel dispersion by linear single- tap equalizers. The implementation details of the OCDM system is discussed with emphasis on its compatibility to the OFDM system. Finally, simula-tion are provided to validate the feasibility of the proposed OCDM under wireless channels. It is shown that the OCDM system is able to utilize the multipath diversity and outperforms the OFDM system under the multipath fading channels.
A Novel Graph-based Approach for Determining Molecular Similarity
Venue: arXiv cs.DS 2016
Year: 2016

In this paper, we tackle the problem of measuring similarity among graphs that represent real objects with noisy data. To account for noise, we relax the definition of similarity using the maximum weighted co-$k$-plex relaxation method, which allows dissimilarities among graphs up to a predetermined level. We then formulate the problem as a novel quadratic unconstrained binary optimization problem that can be solved by a quantum annealer. The context of our study is molecular similarity where the presence of noise might be due to regular errors in measuring molecular features. We develop a similarity measure and use it to predict the mutagenicity of a molecule. Our results indicate that the relaxed similarity measure, designed to accommodate the regular errors, yields a higher prediction accuracy than the measure that ignores the noise.
Threshold Disjunctive Codes
Venue: arXiv cs.IT 2016
Year: 2016

Let $1 \le s < t$, $N \ge 1$ be integers and a complex electronic circuit of size $t$ is said to be an $s$-active, $\; s \ll t$, and can work as a system block if not more than $s$ elements of the circuit are defective. Otherwise, the circuit is said to be an $s$-defective and should be substituted for the similar $s$-active circuit. Suppose that there exists a possibility to check the $s$-activity of the circuit using $N$ non-adaptive group tests identified by a conventional disjunctive $s$-code $X$ of size~$t$ and length~$N$. As usually, we say that any group test yields the positive response if the group contains at least one defective element. In this case, there is no any interest to look for the defective elements. We need to decide on the number of the defective elements in the circuit without knowing the code~$X$. In addition, the decision has the minimal possible complexity because it is based on the simple comparison of a fixed threshold $T$, $0 \le T \le N - 1$, with the number of positive responses $p$, $0 \le p \le N$, obtained after carrying out $N$ non-adaptive tests prescribed by the disjunctive $s$-code~$X$. For the introduced group testing problem, a new class of the well-known disjunctive $s$-codes called the threshold disjunctive $s$-codes is defined. The aim of our paper is to discuss both some constructions of suboptimal threshold disjunctive $s$-codes and the best random coding bounds on the rate of threshold disjunctive $s$-codes.
New Pivot Selection for Sparse Symmetric Indefinite Factorization
Venue: arXiv cs.NA 2016
Year: 2016

We propose a new pivot selection technique for symmetric indefinite factorization of sparse matrices. Such factorization should maintain both sparsity and numerical stability of the factors, both of which depend solely on the choices of the pivots. Our method is based on the minimum degree algorithm and also considers the stability of the factors at the same time. Our experiments show that our method produces factors that are sparser than the factors computed by MA57 and are stable.
The Roles of Familiarity Design in Active Ageing
Venue: arXiv cs.HC 2016
Year: 2016

The elderly often struggle when interacting with technologies. This is because the software and hardware components of the technologies are not familiar to the elderly's mental model. This is a lack of empirical studies about how the concept of familiarity can be infused into the design of interactive technology systems to bridge the digital divide preventing today's elderly people from actively engaging with such technologies. In this paper, a multi pronged approach is utilized. We investigate the Effects of Familiarity in Design on the Adoption of Wellness Games by the Elderly, familiarity in productive ageing, familiarity in efficient collaborative crowdsourcing, productive ageing through familiarity based Intelligent Personalized Crowdsourcing and familiarity based Agent Augmented Inter-generational Crowdsourcing. The results show that familiarity in design improves the perceived satisfaction and adoption likelihood significantly among the elderly users. These results can potentially benefit intelligent interface agent design when such agents need to interact with elderly users. A Crowdsourcing algorithm, CrowdAsm is developed. By using CrowdAsm we are able to dynamically assemble teams of workers considering the budgets, the availability of workers with the required skills and their track records to complete crowdsourcing tasks requiring collaboration among workers with heterogeneous skills. Theoretical analysis has shown that CrowdAsm can achieve close to optimal profit for a collaborative crowdsourcing system if workers follow the recommendations.