OpenRaiser/Intern-Atlas huggingface dataset:
State Observers for Sensorless Control of Magnetic Levitation Systems
Venue: arXiv cs.SY 2017
Year: 2017

In this paper we address the problem of state observation for sensorless control of nonlinear magnetic levitation systems, that is, the regulation of the position of a levitated object measuring only the voltage and current of the electrical supply. Instrumental for the development of the theory is the use of parameter estimation-based observers, which combined with the dynamic regressor extension and mixing parameter estimation technique, allow the reconstruction of the magnetic flux. With the knowledge of the latter it is shown that the mechanical coordinates can be estimated with suitably tailored nonlinear observers. Replacing the observed states, in a certainty equivalent manner, with a full information globally stabilising law completes the sensorless controller design. We consider one and two-degrees-of-freedom systems that, interestingly, demand totally different mathematical approaches for their solutions. Simulation results are used to illustrate the performance of the proposed schemes.
Stability Analysis of TDD Networks Revisited: A trade-off between Complexity and Precision
Venue: arXiv cs.IT 2017
Year: 2017

In this paper, we revisit the stability region of a cellular time division duplex (TDD) network. We characterize the queuing stability region of a network model that consists of two types of communications: (i) users communicating with the base station and (ii) users communicating with each other by passing through the base station. When a communication passes through the base station (BS) then a packet cannot be delivered to the destination UE until it is first received by the BS queue from the source UE. Due to the relaying functionality at the BS level, a coupling is created between the queues of the source users and the BS queues. In addition, contrarily to the majority of the existing works where an ON/OFF model of transmission is considered, we assume a link adaptation model (i.e. multiple rate model) where the bit rate of a link depends on its radio conditions. The coupling between the queues as well as the multiple rate model are the main challenges that highly increase the complexity of the stability region characterization. In this paper, we propose a simple approach that permits to overcome these challenges and to provide a full characterization of the exact stability region as a convex polytope with a finite number of vertices. An approximated model is proposed for reducing the computational complexity of the exact stability region. For the multi-user scenario, a trade-off is established between the complexity and the preciseness of the approximated stability region compared to the exact one. Furthermore, numerical results are presented to corroborate our claims.
Probability Risk Identification Based Intrusion Detection System for SCADA Systems
Venue: arXiv cs.CR 2017
Year: 2017

. As Supervisory Control and Data Acquisition (SCADA) systems control several critical infrastructures, they have connected to the internet. Consequently, SCADA systems face different sophisticated types of cyber adversaries. This paper suggests a Probability Risk Identification based Intrusion Detection System (PRI-IDS) technique based on analysing network traffic of Modbus TCP/IP for identifying replay attacks. It is acknowledged that Modbus TCP is usually vulnerable due to its unauthenticated and unencrypted nature. Our technique is evaluated using a simulation environment by configuring a testbed, which is a cus- tom SCADA network that is cheap, accurate and scalable. The testbed is exploited when testing the IDS by sending individual packets from an attacker located on the same LAN as the Modbus master and slave. The experimental results demonstrated that the proposed technique can effectively and efficiently recognise replay attacks.
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Venue: arXiv cs.LG 2017
Year: 2017

This paper proposes a stochastic variant of a classic algorithm---the cubic-regularized Newton method [Nesterov and Polyak 2006]. The proposed algorithm efficiently escapes saddle points and finds approximate local minima for general smooth, nonconvex functions in only $\mathcal{\tilde{O}}(ε^{-3.5})$ stochastic gradient and stochastic Hessian-vector product evaluations. The latter can be computed as efficiently as stochastic gradients. This improves upon the $\mathcal{\tilde{O}}(ε^{-4})$ rate of stochastic gradient descent. Our rate matches the best-known result for finding local minima without requiring any delicate acceleration or variance-reduction techniques.
An Analysis of Privacy-Aware Personalization Signals by Using Online Evaluation Methods
Venue: arXiv cs.IR 2017
Year: 2017

Personalization despite being an effective solution to the problem information overload remains tricky on account of multiple dimensions to consider. Furthermore, the challenge of avoiding overdoing personalization involves estimation of a user's preferences in relation to different queries. This work is an attempt to make inferences about when personalization would be beneficial by relating observable user behavior to his/her social network usage patterns and user-generated content. User behavior on a search system is observed by means of team-draft interleaving whereby results from two retrieval functions are presented in an interleaved manner, and user clicks are utilised to infer preference for a certain retrieval function. This improves upon earlier work which had limited usefulness due to reliance on user survey results; our findings may aid real-time personalization in search systems by detecting a user-related and query-related personalization signals.
Marginal Release Under Local Differential Privacy
Venue: arXiv cs.DB 2017
Year: 2017

Many analysis and machine learning tasks require the availability of marginal statistics on multidimensional datasets while providing strong privacy guarantees for the data subjects. Applications for these statistics range from finding correlations in the data to fitting sophisticated prediction models. In this paper, we provide a set of algorithms for materializing marginal statistics under the strong model of local differential privacy. We prove the first tight theoretical bounds on the accuracy of marginals compiled under each approach, perform empirical evaluation to confirm these bounds, and evaluate them for tasks such as modeling and correlation testing. Our results show that releasing information based on (local) Fourier transformations of the input is preferable to alternatives based directly on (local) marginals.
Stochastic Stability in Max-Product and Max-Plus Systems with Markovian Jumps
Venue: arXiv cs.SY 2017
Year: 2017

We study Max-Product and Max-Plus Systems with Markovian Jumps and focus on stochastic stability problems. At first, a Lyapunov function is derived for the asymptotically stable deterministic Max-Product Systems. This Lyapunov function is then adjusted to derive sufficient conditions for the stochastic stability of Max-Product systems with Markovian Jumps. Many step Lyapunov functions are then used to derive necessary and sufficient conditions for stochastic stability. The results for the Max-Product systems are then applied to Max-Plus systems with Markovian Jumps, using an isomorphism and almost sure bounds for the asymptotic behavior of the state are obtained. A numerical example illustrating the application of the stability results on a production system is also given.
An Application of Mosaic Diagrams to the Visualization of Set Relationships
Venue: arXiv cs.GR 2017
Year: 2017

We present an application of mosaic diagrams to the visualisation of set relations. Venn and Euler diagrams are the best known visual representations of sets and their relationships (intersections, containment or subsets, exclusion or disjointness). In recent years, alternative forms of visualisation have been proposed. Among them, linear diagrams have been shown to compare favourably to Venn and Euler diagrams, in supporting non-interactive assessment of set relationships. Recent studies that compared several variants of linear diagrams have demonstrated that users perform best at tasks involving identification of intersections, disjointness and subsets when using a horizontally drawn linear diagram with thin lines representing sets, and employing vertical lines as guide lines. The essential visual task the user needs to perform in order to interpret this kind of diagram is vertical alignment of parallel lines and detection of overlaps. Space-filling mosaic diagrams which support this same visual task have been used in other applications, such as the visualization of schedules of activities, where they have been shown to be superior to linear Gantt charts. In this paper, we present an application of mosaic diagrams for visualization of set relationships, and compare it to linear diagrams in terms of accuracy, time-to-answer, and subjective ratings of perceived task difficulty. The study participants exhibited similar performance on both visualisations, suggesting that mosaic diagrams are a good alternative to Venn and Euler diagrams, and that the choice between linear diagrams and mosaics may be solely guided by visual design considerations.
R(QPS-Serena) and R(QPS-Serenade): Two Novel Augmenting-Path Based Algorithms for Computing Approximate Maximum Weight Matching
Venue: arXiv cs.DS 2017
Year: 2017

In this addendum, we show that the switching algorithm QPS-SERENA can be converted R(QPS-SERENA), an algorithm for computing approximate Maximum Weight Matching (MWM). Empirically, R(QPS-SERENA) computes $(1-ε)$-MWM within linear time (with respect to the number of edges $N^2$) for any fixed $ε\in (0,1)$, for complete bipartite graphs with {\it i.i.d.} uniform edge weight distributions. This efficacy matches that of the state-of-art solution, although we so far cannot prove any theoretical guarantees on the time complexities needed to attain a certain approximation ratio. Then, we have similarly converted QPS-SERENADE to R(QPS-SERENADE), which empirically should output $(1-ε)$-MWM within only $O(N \log N)$ time for the same type of complete bipartite graphs as described above.
Information Directed Sampling for Stochastic Bandits with Graph Feedback
Venue: arXiv cs.LG 2017
Year: 2017

We consider stochastic multi-armed bandit problems with graph feedback, where the decision maker is allowed to observe the neighboring actions of the chosen action. We allow the graph structure to vary with time and consider both deterministic and Erdős-Rényi random graph models. For such a graph feedback model, we first present a novel analysis of Thompson sampling that leads to tighter performance bound than existing work. Next, we propose new Information Directed Sampling based policies that are graph-aware in their decision making. Under the deterministic graph case, we establish a Bayesian regret bound for the proposed policies that scales with the clique cover number of the graph instead of the number of actions. Under the random graph case, we provide a Bayesian regret bound for the proposed policies that scales with the ratio of the number of actions over the expected number of observations per iteration. To the best of our knowledge, this is the first analytical result for stochastic bandits with random graph feedback. Finally, using numerical evaluations, we demonstrate that our proposed IDS policies outperform existing approaches, including adaptions of upper confidence bound, $ε$-greedy and Exp3 algorithms.
Distances in and Layering of a DAG
Venue: arXiv cs.DS 2017
Year: 2017

The diameter of an undirected unweighted graph $G=(V,E)$ is the maximum value of the distance from any vertex $u$ to another vertex $v$ for $u,v \in V$ where distance i.e. $d(u,v)$ is the length of the shortest path from $u$ to $v$ in $G$. DAG, is a directed graph without a cycle. We denote the diameter of an unweighted DAG $G=(V,E)$ by $δ(G)$. The stretch of a DAG $G$ is the length of longest path from $u$ to $v$ in $G$, for all choices of $(u, v) \in V$ denoted by $Δ(G)$. The diameter of an undirected graph can be computed in $O(|V|(|V|+|E|))$ time by executing breadth first search $|V|$ times. We show that stretch and diameter of a DAG can be computed in $O(|V|+|E|)$ time and $O(|V||E|)$ time respectively. A DAG is balanced if and only if a consistent assignment of level numbers to all vertices is possible. Layering refers to such an assignment. A balanced DAG is defined. An efficient algorithm that either detects whether a given DAG is unbalanced or layers it otherwise is designed with a running time of $O(|V|+|E|)$. \\ Key words: Diameter, directed acyclic graph, longest directed path, graph algorithms, complexity.
Weak Flip Codes and their Optimality on the Binary Erasure Channel
Venue: arXiv cs.IT 2017
Year: 2017

This paper investigates fundamental properties of nonlinear binary codes by looking at the codebook matrix not row-wise (codewords), but column-wise. The family of weak flip codes is presented and shown to contain many beautiful properties. In particular the subfamily fair weak flip codes, which goes back to Berlekamp, Gallager, and Shannon and which was shown to achieve the error exponent with a fixed number of codewords $M$, can be seen as a generalization of linear codes to an arbitrary number of codewords. Based on the column-wise approach, the $r$-wise Hamming distance is introduced as a generalization to the widely used (pairwise) Hamming distance. It is shown that the minimum $r$-wise Hamming distance satisfies a generalized $r$-wise Plotkin bound. The $r$-wise Hamming distance structure of the nonlinear fair weak flip codes is analyzed and shown to be superior to many codes. In particular, it is proven that the fair weak flip codes achieve the $r$-wise Plotkin bound with equality for all $r$. In the second part of the paper, these insights are applied to a binary erasure channel (BEC) with an arbitrary erasure probability. An exact formula for the average error probability of an arbitrary code using maximum likelihood decoding is derived and shown to be expressible using only the $r$-wise Hamming distance structure of the code. For a number of codewords $M\leq4$ and an arbitrary blocklength $n$, the globally optimal codes (in the sense of minimizing the average error probability) are found. For $M=5,6$ and an arbitrary blocklength $n$, the optimal codes are conjectured. For larger $M$, observations regarding the optimal design are presented, e.g., that good codes have a large $r$-wise Hamming distance structure for all $r$. Numerical results validate our code design criteria and show the superiority of our best found nonlinear weak flip codes compared to the best linear codes.
Multi-Relevance Transfer Learning
Venue: arXiv cs.LG 2017
Year: 2017

Transfer learning aims to faciliate learning tasks in a label-scarce target domain by leveraging knowledge from a related source domain with plenty of labeled data. Often times we may have multiple domains with little or no labeled data as targets waiting to be solved. Most existing efforts tackle target domains separately by modeling the `source-target' pairs without exploring the relatedness between them, which would cause loss of crucial information, thus failing to achieve optimal capability of knowledge transfer. In this paper, we propose a novel and effective approach called Multi-Relevance Transfer Learning (MRTL) for this purpose, which can simultaneously transfer different knowledge from the source and exploits the shared common latent factors between target domains. Specifically, we formulate the problem as an optimization task based on a collective nonnegative matrix tri-factorization framework. The proposed approach achieves both source-target transfer and target-target leveraging by sharing multiple decomposed latent subspaces. Further, an alternative minimization learning algorithm is developed with convergence guarantee. Empirical study validates the performance and effectiveness of MRTL compared to the state-of-the-art methods.
Estimation of optimal encoding ladders for tiled 360° VR video in adaptive streaming systems
Venue: arXiv cs.MM 2017
Year: 2017

Given the significant industrial growth of demand for virtual reality (VR), 360° video streaming is one of the most important VR applications that require cost-optimal solutions to achieve widespread proliferation of VR technology. Because of its inherent variability of data-intensive content types and its tiled-based encoding and streaming, 360° video requires new encoding ladders in adaptive streaming systems to achieve cost-optimal and immersive streaming experiences. In this context, this paper targets both the provider's and client's perspectives and introduces a new content-aware encoding ladder estimation method for tiled 360° VR video in adaptive streaming systems. The proposed method first categories a given 360° video using its features of encoding complexity and estimates the visual distortion and resource cost of each bitrate level based on the proposed distortion and resource cost models. An optimal encoding ladder is then formed using the proposed integer linear programming (ILP) algorithm by considering practical constraints. Experimental results of the proposed method are compared with the recommended encoding ladders of professional streaming service providers. Evaluations show that the proposed encoding ladders deliver better results compared to the recommended encoding ladders in terms of objective quality for 360° video, providing optimal encoding ladders using a set of service provider's constraint parameters.
Cons-free Programming with Immutable Functions
Venue: arXiv cs.LO 2017
Year: 2017

We investigate the power of non-determinism in purely functional programming languages with higher-order types. Specifically, we set out to characterise the hierarchy NP $\subseteq$ NEXP $\subseteq$ NEXP$^{(2)}$ $\subseteq \cdots \subseteq$ NEXP$^{(k)}$ $\subseteq \cdots$ solely in terms of higher-typed, purely functional programs. Although the work is incomplete, we present an initial approach using cons-free programs with immutable functions.
h: A Plank for Higher-order Attribute Contraction Schemes
Venue: arXiv cs.PL 2017
Year: 2017

We present and formalize h, a core (or "plank") calculus that can serve as the foundation for several compiler specification languages, notably CRSX (Combinatory Reductions Systems with eXtensions), HACS (Higher-order Attribute Contraction Schemes), and TransScript. We discuss how the h typing and formation rules introduce the necessary restrictions to ensure that rewriting is well-defined, even in the presence of h's powerful extensions for manipulating free variables and environments as first class elements (including in pattern matching).
Eventually Sound Points-To Analysis with Missing Code
Venue: arXiv cs.PL 2017
Year: 2017

Static analyses make the increasingly tenuous assumption that all source code is available for analysis; for example, large libraries often call into native code that cannot be analyzed. We propose a points-to analysis that initially makes optimistic assumptions about missing code, and then inserts runtime checks that report counterexamples to these assumptions that occur during execution. Our approach guarantees eventual soundness, i.e., the static analysis is sound for the available code after some finite number of counterexamples. We implement Optix, an eventually sound points-to analysis for Android apps, where the Android framework is missing. We show that the runtime checks added by Optix incur low overhead on real programs, and demonstrate how Optix improves a client information flow analysis for detecting Android malware.
Multi-cell Device-to-Device Communications: A Spectrum Sharing and Densification Study
Venue: arXiv cs.IT 2017
Year: 2017

One of the most significant 5G technology enablers will be Device-to-Device (D2D) communications. D2D communications constitute a promising way to improve spectral, energy and latency performance, exploiting the physical proximity of communicating devices and increasing resource utilization. Furthermore, network infrastructure densification has been considered as one of the most substantial methods to increase system performance, taking advantage of base station proximity and spatial reuse of system resources. However, could we improve system performance by leveraging both of these two 5G enabling technologies together in a multi-cell environment? How does spectrum sharing affect performance enhancement? This article investigates the implications of interference, densification and spectrum sharing in D2D performance gain. The in-band D2D approach, where legacy users coexist with potential D2D pairs, is considered in a multi-cell system. Overlay and underlay spectrum sharing approaches are employed in order for the potential D2D pairs to access the spectrum. Given that two of the most critical problems in the D2D concept are mode selection and user scheduling, we jointly address them, aiming at maximizing the total system uplink throughput. Thus, we present a radio resource management mechanism for intra-cell and cross-cell overlay/underlay D2D communications enabled in a multi-cell system. System-level simulations are executed to evaluate the system performance and examine the trends of D2D communication gain for the different spectrum sharing approaches and various densification scenarios. Finally, realworld SDR-based experiments are performed to test and assess D2D communications for overlay and underlay spectrum sharing.
Coordinated AC/DC Microgrid Optimal Scheduling
Venue: arXiv cs.SY 2017
Year: 2017

This paper proposes a coordinated optimal scheduling model for hybrid AC/DC microgrids. The objective of the proposed model is to minimize the total microgrid operation cost when considering interactions between AC and DC sub-systems of the microgrid network. Nonlinear power flow equations for AC and DC networks have been linearized through a proposed model to enable formulating the problem by mixed integer linear programming (MILP) which expedites the solution process and ensures better solutions in terms of optimality. The proposed model is tested on the modified IEEE 33-bus test system. Numerical simulations exhibit the merits of the proposed coordinated AC/DC optimal scheduling model and further analyze its sensitivity to various decisive operational parameters.
Co-Optimization Generation and Distribution Planning in Microgrids
Venue: arXiv cs.SY 2017
Year: 2017

This paper proposes a co-optimization generation and distribution planning model in microgrids in which simultaneous investment in generation, i.e., distributed generation (DG) and distributed energy storage (DES), and distribution, i.e., upgrading the existing distribution network, is considered. The objective of the proposed model is to minimize the microgrid total planning cost which comprises the investment cost of installed generation assets and lines, the microgrid operation cost, and the cost of unserved energy. The microgrid planning solution determines the optimal generation size, location, and mix, as well as required network upgrade. To consider line flow and voltage limits, a linearized power flow model is proposed and used, allowing further application of mixed integer linear programming (MILP) in problem modeling. The proposed model is applied to the IEEE 33-bus standard test system to demonstrate the acceptable performance and the effectiveness of the proposed model.