OpenRaiser/Intern-Atlas huggingface dataset:
Joint Filter and Waveform Design for Radar STAP in Signal Dependent Interference
Venue: arXiv cs.SY 2015
Year: 2015

Waveform design is a pivotal component of the fully adaptive radar construct. In this paper we consider waveform design for radar space time adaptive processing (STAP), accounting for the waveform dependence of the clutter correlation matrix. Due to this dependence, in general, the joint problem of receiver filter optimization and radar waveform design becomes an intractable, non-convex optimization problem, Nevertheless, it is however shown to be individually convex either in the filter or in the waveform variables. We derive constrained versions of: a) the alternating minimization algorithm, b) proximal alternating minimization, and c) the constant modulus alternating minimization, which, at each step, iteratively optimizes either the STAP filter or the waveform independently. A fast and slow time model permits waveform design in radar STAP but the primary bottleneck is the computational complexity of the algorithms.
The Attack as Intuitionistic Negation
Venue: arXiv cs.LO 2015
Year: 2015

We translate the argumentation networks ${\cal A}=(S, R)$ into a theory $D$ of intuitionistic logic, retaining $S$ as the domain and using intuitionistic negation to model the attack $R$ in ${\cal A}$: the attack $xRy$ is translated to $x\to\neg y$. The intuitionistic models of $D$ characterise the complete extensions of ${\cal A}$. The reduction of argumentation networks to intuitionistic logic yields, in addition to a representation theorem, some additional benefits: it allows us to give semantics to higher level attacks, where an attack "$xRy$" can itself attack another attack "$uRv$"; one can make higher level meta-statements $W$ on $(S, R)$ and such meta-statements can attack and be attacked in the domain.
Disk storage management for LHCb based on Data Popularity estimator
Venue: arXiv cs.DC 2015
Year: 2015

This paper presents an algorithm providing recommendations for optimizing the LHCb data storage. The LHCb data storage system is a hybrid system. All datasets are kept as archives on magnetic tapes. The most popular datasets are kept on disks. The algorithm takes the dataset usage history and metadata (size, type, configuration etc.) to generate a recommendation report. This article presents how we use machine learning algorithms to predict future data popularity. Using these predictions it is possible to estimate which datasets should be removed from disk. We use regression algorithms and time series analysis to find the optimal number of replicas for datasets that are kept on disk. Based on the data popularity and the number of replicas optimization, the algorithm minimizes a loss function to find the optimal data distribution. The loss function represents all requirements for data distribution in the data storage system. We demonstrate how our algorithm helps to save disk space and to reduce waiting times for jobs using this data.
A Generative Model of Words and Relationships from Multiple Sources
Venue: arXiv cs.CL 2015
Year: 2015

Neural language models are a powerful tool to embed words into semantic vector spaces. However, learning such models generally relies on the availability of abundant and diverse training examples. In highly specialised domains this requirement may not be met due to difficulties in obtaining a large corpus, or the limited range of expression in average use. Such domains may encode prior knowledge about entities in a knowledge base or ontology. We propose a generative model which integrates evidence from diverse data sources, enabling the sharing of semantic information. We achieve this by generalising the concept of co-occurrence from distributional semantics to include other relationships between entities or words, which we model as affine transformations on the embedding space. We demonstrate the effectiveness of this approach by outperforming recent models on a link prediction task and demonstrating its ability to profit from partially or fully unobserved data training labels. We further demonstrate the usefulness of learning from different data sources with overlapping vocabularies.
On a Hybrid Preamble/Soft-Output Demapper Approach for Time Synchronization for IEEE 802.15.6 Narrowband WBAN
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we present a maximum likelihood (ML) based time synchronization algorithm for Wireless Body Area Networks (WBAN). The proposed technique takes advantage of soft information retrieved from the soft demapper for the time delay estimation. This algorithm has a low complexity and is adapted to the frame structure specified by the IEEE 802.15.6 standard for the narrowband systems. Simulation results have shown good performance which approach the theoretical mean square error limit bound represented by the Cramer Rao Bound (CRB).
Sustainability: Scholarly Repository as an Enterprise
Venue: arXiv cs.DL 2015
Year: 2015

The expanding need for an open information sharing infrastructure to promote scholarly communication led to the pioneering establishment of arXiv.org, now maintained by the Cornell University Library. To be sustainable, the repository requires careful, long term planning for services, management and funding. The library is developing a sustainability model for arXiv.org, based on voluntary contributions and the ongoing participation and support of 200 libraries and research laboratories around the world. The sustainability initiative is based on a membership model and builds on arXiv's technical, service, financial and policy infrastructure. Five principles for sustainability drive development, starting with deep integration into the scholarly community. Also key are a clearly defined mandate and governance structure, a stable yet innovative technology platform, systematic creation of content policies and strong business planning strategies. Repositories like arXiv must consider usability and life cycle alongside values and trends in scholarly communication. To endure, they must also support and enhance their service by securing and managing resources and demonstrating responsible stewardship.
Characterizing SW-Efficiency in the Social Choice Domain
Venue: arXiv cs.GT 2015
Year: 2015

Recently, Dogan, Dogan and Yildiz (2015) presented a new efficiency notion for the random assignment setting called SW (social welfare)-efficiency and characterized it. In this note, we generalize the characterization for the more general domain of randomized social choice.
Implementing Efficient All Solutions SAT Solvers
Venue: arXiv cs.DS 2015
Year: 2015

All solutions SAT (AllSAT for short) is a variant of propositional satisfiability problem. Despite its significance, AllSAT has been relatively unexplored compared to other variants. We thus survey and discuss major techniques of AllSAT solvers. We faithfully implement them and conduct comprehensive experiments using a large number of instances and various types of solvers including one of the few public softwares. The experiments reveal solver's characteristics. Our implemented solvers are made publicly available so that other researchers can easily develop their solver by modifying our codes and compare it with existing methods.
Electrical Reduction, Homotopy Moves, and Defect
Venue: arXiv cs.CG 2015
Year: 2015

We prove the first nontrivial worst-case lower bounds for two closely related problems. First, $Ω(n^{3/2})$ degree-1 reductions, series-parallel reductions, and $Δ$Y transformations are required in the worst case to reduce an $n$-vertex plane graph to a single vertex or edge. The lower bound is achieved by any planar graph with treewidth $Θ(\sqrt{n})$. Second, $Ω(n^{3/2})$ homotopy moves are required in the worst case to reduce a closed curve in the plane with $n$ self-intersection points to a simple closed curve. For both problems, the best upper bound known is $O(n^2)$, and the only lower bound previously known was the trivial $Ω(n)$. The first lower bound follows from the second using medial graph techniques ultimately due to Steinitz, together with more recent arguments of Noble and Welsh [J. Graph Theory 2000]. The lower bound on homotopy moves follows from an observation by Haiyashi et al. [J. Knot Theory Ramif. 2012] that the standard projections of certain torus knots have large defect, a topological invariant of generic closed curves introduced by Aicardi and Arnold. Finally, we prove that every closed curve in the plane with $n$ crossings has defect $O(n^{3/2})$, which implies that better lower bounds for our algorithmic problems will require different techniques.
Towards the Forensic Identification and Investigation of Cloud Hosted Servers through Noninvasive Wiretaps
Venue: arXiv cs.DC 2015
Year: 2015

When conducting modern cybercrime investigations, evidence has often to be gathered from computer systems located at cloud-based data centres of hosting providers. In cases where the investigation cannot rely on the cooperation of the hosting provider, or where documentation is not available, investigators can often find the identification of which distinct server among many is of interest difficult and extremely time consuming. To address the problem of identifying these servers, in this paper a new approach to rapidly and reliably identify these cloud hosting computer systems is presented. In the outlined approach, a handheld device composed of an embedded computer combined with a method of undetectable interception of Ethernet based communications is presented. This device is tested and evaluated, and a discussion is provided on its usefulness in identifying of server of interest to an investigation.
Delay Analysis of Hybrid WiFi-LiFi System
Venue: arXiv cs.NI 2015
Year: 2015

Heterogeneous wireless networks are capable of effectively leveraging different access technologies to provide a wide variety of coverage areas. In this paper, the coexistence of WiFi and visible light communication (VLC) is investigated as a paradigm. The delay of two configurations of such heterogeneous system has been evaluated. In the first configuration, the non-aggregated system, any request is either allocated to WiFi or VLC. While in the second configuration, the aggregated system, each request is split into two pieces, one is forwarded to WiFi and the other is forwarded to VLC. Under the assumptions of Poisson arrival process of requests and the exponential distribution of requests size, it is mathematically proved that the aggregated system provides lower minimum average system delay than that of the non-aggregated system. For the non-aggregated system, the optimal traffic allocation ratio is derived. For the aggregated system, an efficient solution for the splitting ratio is proposed. Empirical results show that the solution proposed here incurs a delay penalty (less than 3\%) over the optimal result.
WHOI-Plankton- A Large Scale Fine Grained Visual Recognition Benchmark Dataset for Plankton Classification
Venue: arXiv cs.CV 2015
Year: 2015

Planktonic organisms are of fundamental importance to marine ecosystems: they form the basis of the food web, provide the link between the atmosphere and the deep ocean, and influence global-scale biogeochemical cycles. Scientists are increasingly using imaging-based technologies to study these creatures in their natural habit. Images from such systems provide an unique opportunity to model and understand plankton ecosystems, but the collected datasets can be enormous. The Imaging FlowCytobot (IFCB) at Woods Hole Oceanographic Institution, for example, is an \emph{in situ} system that has been continuously imaging plankton since 2006. To date, it has generated more than 700 million samples. Manual classification of such a vast image collection is impractical due to the size of the data set. In addition, the annotation task is challenging due to the large space of relevant classes, intra-class variability, and inter-class similarity. Methods for automated classification exist, but the accuracy is often below that of human experts. Here we introduce WHOI-Plankton: a large scale, fine-grained visual recognition dataset for plankton classification, which comprises over 3.4 million expert-labeled images across 70 classes. The labeled image set is complied from over 8 years of near continuous data collection with the IFCB at the Martha's Vineyard Coastal Observatory (MVCO). We discuss relevant metrics for evaluation of classification performance and provide results for a traditional method based on hand-engineered features and two methods based on convolutional neural networks.
Differential Privacy: An Estimation Theory-Based Method for Choosing Epsilon
Venue: arXiv cs.CR 2015
Year: 2015

Differential privacy is achieved by the introduction of Laplacian noise in the response to a query, establishing a precise trade-off between the level of differential privacy and the accuracy of the database response (via the amount of noise introduced). However, the amount of noise to add is typically defined through the scale parameter of the Laplace distribution, whose use may not be so intuitive. In this paper we propose to use two parameters instead, related to the notion of interval estimation, which provide a more intuitive picture of how precisely the true output of a counting query may be gauged from the noise-polluted one (hence, how much the individual's privacy is protected).
The ISO Problem: Decentralized Stochastic Control via Bidding Schemes
Venue: arXiv cs.SY 2015
Year: 2015

We consider a smart-grid connecting several agents, modeled as stochastic dynamical systems, who may be electricity consumers/producers. At each discrete time instant, which may represent a 15 minute interval, each agent may consume/generate some quantity of electrical energy. The Independent System Operator (ISO) is given the task of assigning consumptions/generations to the agents so as to maximize the sum of the utilities accrued to the agents, subject to the constraint that energy generation equals consumption at each time. This task of coordinating generation and demand has to be accomplished by the ISO without the agents revealing their system states, dynamics, or utility/cost functions. We show how and when a simple iterative procedure converges to the optimal solution. The ISO iteratively obtains electricity bids by the agents, and declares the tentative market clearing prices. In response to these prices, the agents submit new bids. On the demand side, the solution yields an optimal demand response for dynamic and stochastic loads. On the generation side, it provides the optimal utilization of stochastically varying renewables such as solar/wind, and generation with fossil fuel based generation with dynamic constraints such as ramping rates. Thereby we solve a decentralized stochastic control problem, without agents sharing any information about their system models, states or utility functions.
Unsupervised diffusion-based LMS for node-specific parameter estimation over wireless sensor networks
Venue: arXiv cs.SY 2015
Year: 2015

We study a distributed node-specific parameter estimation problem where each node in a wireless sensor network is interested in the simultaneous estimation of different vectors of parameters that can be of local interest, of common interest to a subset of nodes, or of global interest to the whole network. We assume a setting where the nodes do not know which other nodes share the same estimation interests. First, we conduct a theoretical analysis on the asymptotic bias that results in case the nodes blindly process all the local estimates of all their neighbors to solve their own node-specific parameter estimation problem. Next, we propose an unsupervised diffusion-based LMS algorithm that allows each node to obtain unbiased estimates of its node-specific vector of parameters by continuously identifying which of the neighboring local estimates correspond to each of its own estimation tasks. Finally, simulation experiments illustrate the efficiency of the proposed strategy.
Calculating entropy at different scales among diverse communication systems
Venue: arXiv cs.IT 2015
Year: 2015

We evaluated the impact of changing the observation scale over the entropy measures for text descriptions. MIDI coded Music, computer code and two human natural languages were studied at the scale of characters, words, and at the Fundamental Scale resulting from adjusting the symbols length used to interpret each text-description until it produced minimum entropy. The results show that the Fundamental Scale method is comparable with the use of words when measuring entropy levels in written texts. However, this method can also be used in communication systems lacking words such as music. Measuring symbolic entropy at the fundamental scale allows to calculate quantitatively, relative levels of complexity for different communication systems. The results open novel vision on differences among the structure of the communication systems studied.
Illustration of iterative linear solver behavior on simple 1D and 2D problems
Venue: arXiv cs.NA 2015
Year: 2015

In geometry processing, numerical optimization methods often involve solving sparse linear systems of equations. These linear systems have a structure that strongly resembles to adjacency graphs of the underlying mesh. We observe how classic linear solvers behave on this specific type of problems. For the sake of simplicity, we minimise either the squared gradient or the squared Laplacian, evaluated by finite differences on a regular 1D or 2D grid. We observed the evolution of the solution for both energies, in 1D and 2D, and with different solvers: Jacobi, Gauss-Seidel, SSOR (Symmetric successive over-relaxation) and CG (conjugate gradient [She94]). Plotting results at different iterations allows to have an intuition of the behavior of these classic solvers.
Reduced Precision Checking to Detect Errors in Floating Point Arithmetic
Venue: arXiv cs.NA 2015
Year: 2015

In this paper, we use reduced precision checking (RPC) to detect errors in floating point arithmetic. Prior work explored RPC for addition and multiplication. In this work, we extend RPC to a complete floating point unit (FPU), including division and square root, and we present precise analyses of the errors undetectable with RPC that show bounds that are smaller than prior work. We implement RPC for a complete FPU in RTL and experimentally evaluate its error coverage and cost.
Optimal Mission Planner with Timed Temporal Logic Constraints
Venue: arXiv cs.SY 2015
Year: 2015

In this paper, we present an optimization based method for path planning of a mobile robot subject to time bounded temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specification such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. This approach is different from the automata based methods which generate a finite abstraction of the environment and dynamics, and use an automata theoretic approach to formally generate a path that satisfies the TL. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications.
Abstraction/Representation Theory for Heterotic Physical Computing
Venue: arXiv cs.LO 2015
Year: 2015

We give a rigorous framework for the interaction of physical computing devices with abstract computation. Device and program are mediated by the non-logical 'representation relation'; we give the conditions under which representation and device theory give rise to commuting diagrams between logical and physical domains, and the conditions for computation to occur. We give the interface of this new framework with currently existing formal methods, showing in particular its close relationship to refinement theory, and the implications for questions of meaning and reference in theoretical computer science. The case of hybrid computing is considered in detail, addressing in particular the example of an internet-mediated 'social machine', and the abstraction/representation framework used to provide a formal distinction between heterotic and hybrid computing. This forms the basis for future use of the framework in formal treatments of nonstandard physical computers.
Waveforms for the Massive MIMO Downlink: Amplifier Efficiency, Distortion and Performance
Venue: arXiv cs.IT 2015
Year: 2015

In massive MIMO, most precoders result in downlink signals that suffer from high PAR, independently of modulation order and whether single-carrier or OFDM transmission is used. The high PAR lowers the power efficiency of the base station amplifiers. To increase power efficiency, low-PAR precoders have been proposed. In this article, we compare different transmission schemes for massive MIMO in terms of the power consumed by the amplifiers. It is found that (i) OFDM and single-carrier transmission have the same performance over a hardened massive MIMO channel and (ii) when the higher amplifier power efficiency of low-PAR precoding is taken into account, conventional and low-PAR precoders lead to approximately the same power consumption. Since downlink signals with low PAR allow for simpler and cheaper hardware, than signals with high PAR, therefore, the results suggest that low-PAR precoding with either single-carrier or OFDM transmission should be used in a massive MIMO base station.
BER Analysis of the box relaxation for BPSK Signal Recovery
Venue: arXiv cs.IT 2015
Year: 2015

We study the problem of recovering an $n$-dimensional vector of $\{\pm1\}^n$ (BPSK) signals from $m$ noise corrupted measurements $\mathbf{y}=\mathbf{A}\mathbf{x}_0+\mathbf{z}$. In particular, we consider the box relaxation method which relaxes the discrete set $\{\pm1\}^n$ to the convex set $[-1,1]^n$ to obtain a convex optimization algorithm followed by hard thresholding. When the noise $\mathbf{z}$ and measurement matrix $\mathbf{A}$ have iid standard normal entries, we obtain an exact expression for the bit-wise probability of error $P_e$ in the limit of $n$ and $m$ growing and $\frac{m}{n}$ fixed. At high SNR our result shows that the $P_e$ of box relaxation is within 3dB of the matched filter bound MFB for square systems, and that it approaches MFB as $m $ grows large compared to $n$. Our results also indicates that as $m,n\rightarrow\infty$, for any fixed set of size $k$, the error events of the corresponding $k$ bits in the box relaxation method are independent.
Spectral Properties of Laplacian and Stochastic Diffusion Process for Edge Expansion in Hypergraphs
Venue: arXiv cs.DM 2015
Year: 2015

There has been recent work [Louis STOC 2015] to analyze the spectral properties of hypergraphs with respect to edge expansion. In particular, a diffusion process is defined on a hypergraph such that within each hyperedge, measure flows from nodes having maximum weighted measure to those having minimum. The diffusion process determines a Laplacian, whose spectral properties are related to the edge expansion properties of the hypergraph. It is suggested that in the above diffusion process, within each hyperedge, measure should flow uniformly in the complete bipartite graph from nodes with maximum weighted measure to those with minimum. However, we discover that this method has some technical issues. First, the diffusion process would not be well-defined. Second, the resulting Laplacian would not have the claimed spectral properties. In this paper, we show that the measure flow between the above two sets of nodes must be coordinated carefully over different hyperedges in order for the diffusion process to be well-defined, from which a Laplacian can be uniquely determined. Since the Laplacian is non-linear, we have to exploit other properties of the diffusion process to recover a spectral property concerning the "second eigenvalue" of the resulting Laplacian. Moreover, we show that higher order spectral properties cannot hold in general using the current framework.