OpenRaiser/Intern-Atlas huggingface dataset:
A Stochastic Global Identification Framework for Aerospace Vehicles Operating Under Varying Flight States
Venue: arXiv cs.SY 2016
Year: 2016

In this work, a novel data-based stochastic global identification framework is introduced for air vehicles operating under varying flight states and uncertainty. In this context, the term global refers to the identification of a model that is capable of representing the system dynamics under any admissible flight state based on data recorded from sample states. The proposed framework is based on stochastic time-series models for representing the system dynamics and aeroelastic response under multiple flight states, with each state characterized by several variables, such as the airspeed and angle of attack, forming a flight state vector. The method's cornerstone lies in the new class of Vector-dependent Functionally Pooled (VFP) models which allow the explicit analytical inclusion of the flight state vector into the model parameters and, hence, system dynamics. The experimental evaluation is based on a prototype bio-inspired self-sensing composite wing that is subjected to a series of wind tunnel experiments. Distributed micro-sensors in the form of stretchable sensor networks are embedded in the composite layup of the wing to provide the sensing capabilities. Data collected from piezoelectric sensors are employed for the identification of a stochastic global VFP model. The estimated VFP model parameters constitute two-dimensional functions of the flight state vector defined by the airspeed and angle of attack. The identified model is able to successfully represent the aeroelastic response of the wing under the admissible flight states via a minimum number of estimated parameters compared to standard identification approaches. The obtained results demonstrate the high accuracy and effectiveness of the proposed global identification framework, thus constituting a first step towards the next generation of fly-by-feel aerospace vehicles with state awareness capabilities.
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network
Venue: arXiv cs.CV 2016
Year: 2016

Image-matched nonseparable wavelets can find potential use in many applications including image classification, segmen- tation, compressive sensing, etc. This paper proposes a novel design methodology that utilizes convolutional neural net- work (CNN) to design two-channel non-separable wavelet matched to a given image. The design is proposed on quin- cunx lattice. The loss function of the convolutional neural network is setup with total squared error between the given input image to CNN and the reconstructed image at the output of CNN, leading to perfect reconstruction at the end of train- ing. Simulation results have been shown on some standard images.
On Nonlinear Prices in Timed Automata
Venue: arXiv cs.FL 2016
Year: 2016

Priced timed automata provide a natural model for quantitative analysis of real-time systems and have been successfully applied in various scheduling and planning problems. The optimal reachability problem for linearly-priced timed automata is known to be PSPACE-complete. In this paper we investigate priced timed automata with more general prices and show that in the most general setting the optimal reachability problem is undecidable. We adapt and implement the construction of Audemard, Cimatti, Kornilowicz, and Sebastiani for non-linear priced timed automata using state-of-the-art theorem prover Z3 and present some preliminary results.
Towards the Verification of Safety-critical Autonomous Systems in Dynamic Environments
Venue: arXiv cs.SE 2016
Year: 2016

There is an increasing necessity to deploy autonomous systems in highly heterogeneous, dynamic environments, e.g. service robots in hospitals or autonomous cars on highways. Due to the uncertainty in these environments, the verification results obtained with respect to the system and environment models at design-time might not be transferable to the system behavior at run time. For autonomous systems operating in dynamic environments, safety of motion and collision avoidance are critical requirements. With regard to these requirements, Macek et al. [6] define the passive safety property, which requires that no collision can occur while the autonomous system is moving. To verify this property, we adopt a two phase process which combines static verification methods, used at design time, with dynamic ones, used at run time. In the design phase, we exploit UPPAAL to formalize the autonomous system and its environment as timed automata and the safety property as TCTL formula and to verify the correctness of these models with respect to this property. For the runtime phase, we build a monitor to check whether the assumptions made at design time are also correct at run time. If the current system observations of the environment do not correspond to the initial system assumptions, the monitor sends feedback to the system and the system enters a passive safe state.
Anti-Path Cover on Sparse Graph Classes
Venue: arXiv cs.DS 2016
Year: 2016

We show that it is possible to use Bondy-Chvatal closure to design an FPT algorithm that decides whether or not it is possible to cover vertices of an input graph by at most k vertex disjoint paths in the complement of the input graph. More precisely, we show that if a graph has tree-width at most w and its complement is closed under Bondy-Chvatal closure, then it is possible to bound neighborhood diversity of the complement by a function of w only. A simpler proof where tree-depth is used instead of tree-width is also presented.
Efficient and Fair Collaborative Mobile Internet Access
Venue: arXiv cs.NI 2016
Year: 2016

The surging global mobile data traffic challenges the economic viability of cellular networks and calls for innovative solutions to reduce the network congestion and improve user experience. In this context, user-provided networks (UPNs), where mobile users share their Internet access by exploiting their diverse network resources and needs, turn out to be very promising. Heterogeneous users with advanced handheld devices can form connections in a distributed fashion and unleash dormant network resources at the network edge. However, the success of such services heavily depends on users' willingness to contribute their resources, such as network access and device battery energy. In this paper, we introduce a general framework for UPN services and design a bargaining-based distributed incentive mechanism to ensure users participation. The proposed mechanism determines the resources that each user should contribute in order to maximise the aggregate data rate in UPN, and fairly allocate the benefit among the users. The numerical results verify that the service can always improve performance, and such improvement increases with the diversity of the users' resources. Quantitatively, it can reach an average 30% increase of the total served traffic for a typical scenario even with only 6 mobile users.
How Do App Stores Challenge the Global Internet Governance Ecosystem?
Venue: arXiv cs.CY 2016
Year: 2016

App stores challenge the culture of openness and resistance to central authorities cultivated by the pioneers of the Internet. Could multistakeholder governance bodies bring more inclusivity into the global cyberspace governance ecosystem?
Mirrored Light Field Video Camera Adapter
Venue: arXiv cs.RO 2016
Year: 2016

This paper proposes the design of a custom mirror-based light field camera adapter that is cheap, simple in construction, and accessible. Mirrors of different shape and orientation reflect the scene into an upwards-facing camera to create an array of virtual cameras with overlapping field of view at specified depths, and deliver video frame rate light fields. We describe the design, construction, decoding and calibration processes of our mirror-based light field camera adapter in preparation for an open-source release to benefit the robotic vision community.
Deep holes and MDS extensions of Reed-Solomon codes
Venue: arXiv cs.IT 2016
Year: 2016

We study the problem of classifying deep holes of Reed-Solomon codes. We show that this problem is equivalent to the problem of classifying MDS extensions of Reed-Solomon codes by one digit. This equivalence allows us to improve recent results on the former problem. In particular, we classify deep holes of Reed-Solomon codes of dimension greater than half the alphabet size. We also give a complete classification of deep holes of Reed Solomon codes with redundancy three in all dimensions.
A Distributed Algorithm for Throughput Optimal Routing in Overlay Networks
Venue: arXiv cs.NI 2016
Year: 2016

We address the problem of optimal routing in overlay networks. An overlay network is constructed by adding new overlay nodes on top of a legacy network. The overlay nodes are capable of implementing any dynamic routing policy, however, the legacy underlay has a fixed, single path routing scheme and uses a simple work-conserving forwarding policy. Moreover, the underlay routes are pre-determined and unknown to the overlay network. The overlay network can increase the achievable throughput of the underlay by using multiple routes, which consist of direct routes and indirect routes through other overlay nodes. We develop a throughput optimal dynamic routing algorithm for such overlay networks called the Optimal Overlay Routing Policy (OORP). OORP is derived using the classical dual subgradient descent method, and it can be implemented in a distributed manner. We show that the underlay queue-lengths can be used as a substitute for the dual variables. We also propose various schemes to gather the information about the underlay that is required by OORP and compare their performance via extensive simulations.
Parallel Integer Polynomial Multiplication
Venue: arXiv cs.SC 2016
Year: 2016

We propose a new algorithm for multiplying dense polynomials with integer coefficients in a parallel fashion, targeting multi-core processor architectures. Complexity estimates and experimental comparisons demonstrate the advantages of this new approach.
Survey Paper on Rising Threats of Subverting Privacy Infrastructure
Venue: arXiv cs.CR 2016
Year: 2016

One of the main challenges faced by a user today is protecting their privacy, especially during widespread surveil- lance. This led to the development of privacy infrastructures whose main purpose is to guarantee users privacy. However, they are being misused by attackers who consider them to be an exploitable resource to perform illegitimate activities. This paper proposes to analyze and assess the threats that occur due to subverting privacy infrastructures. It begins with an outline of critical privacy infrastructures that were developed. An overview of rising threats of subverting the most prominent privacy infrastructure, Tor is presented. Additionally, a brief assessment of the severity of these threats is discussed and the paper concludes by recommending the scope for further research to mitigate the risks due to such threats.
Secure Communications in the Presence of a Buffer-Aided Wireless-Powered Relay With Self-Energy Recycling
Venue: arXiv cs.IT 2016
Year: 2016

We consider a relay-assisted wireless network, where the energy-harvesting buffer-aided relay node is powered by radio-frequency signals from a source node wishing to communicate with its destination. We propose two secure cooperative protocols for a network composed of a source node equipped with a data buffer communicating with its destination in the presence of a buffer-aided relay node and an eavesdropper. Our proposed protocols are designed based on the channel state information and the buffer state information at the source and relay nodes. The burstiness of data at the source node queue (buffer) and the energy recycling process at the relay are taken into account in our analysis. In addition, we take the decoding and signal processing circuit power consumption constraints into consideration. For the limiting case of an infinite-size battery at the relay, we derive a sufficient condition for the energy queue to saturate. Our numerical results demonstrate the throughput gains of our proposed protocols.
Multiple Access for Visible Light Communications: Research Challenges and Future Trends
Venue: arXiv cs.IT 2016
Year: 2016

The ever-increasing demand of mobile Internet and multimedia services poses unique and significant challenges for current and future generation wireless networks. These challenges are mainly relating to the support of massive ubiquitous connectivity, low latency and highly efficient utilization of spectrum resources. Therefore, it is vital to consider them extensively prior to design and deployment of future wireless networks. To this end, the present article provides a comprehensive overview of a particularly promising and effective wireless technology, namely, visible light communication (VLC). In this context, we initially provide a thorough overview of frequency domain multiple access techniques for single and multi-carrier systems, which is then followed by an in depth discussion on the technical considerations of optical code division multiple access techniques and their adoption in indoor VLC applications. Furthermore, we address space division multiple access and, finally, we revisit and analyze the distinct characteristics of a new technology, namely, non-orthogonal multiple access, which has been proposed recently as a particularly effective solution.
Super Event Driven System OOP GUI Design
Venue: arXiv cs.HC 2016
Year: 2016

This article presents a new proposal design of GUI and new technology in programming Namely "Super Technology" which can be applied for supporting the proposal design of GUI
D-LITe: Building Internet of Things Choreographies
Venue: arXiv cs.SE 2016
Year: 2016

In this work, we present a complete architecture for designing Internet of Things applications. While a main issue in this domain is the heterogeneity of Objects hardware, networks and protocols, we propose D-LITe, a solution to hide this wide range of low layer technologies. By abstracting the hardware, we focus on object's features and not on its real characteristics. D-LITe aims to give a universal access to object's internal processing and computational power. A small virtual machine embedded in each object gives a universal view of its functionalities. Each object's features are discovered and programmed through the network, without any physical access. D-LITe comes with the SALT language that describes the logical behaviour needed to include user's Objects into an IoT application. This communication is based on REST architecture. Gathering all these logical units into a global composition is our way to build a services Choreography, in which each Object has its own task to achieve. This paper presents also an analysis of the gain obtained when a Choreography is used instead of the most common services.
Varieties of Metric and Quantitative Algebras
Venue: arXiv cs.LO 2016
Year: 2016

Metric algebras are metric variants of $Σ$-algebras. They are first introduced in the field of universal algebra to deal with algebras equipped with metric structures such as normed vector spaces. Recently a similar notion of quantitative algebra is used in computer science to formulate computational effects of probabilistic programs. In this paper we show that varieties of metric algebras (classes defined by a set of metric equations) are exactly classes closed under (metric versions of) subalgebras, products and quotients. This result implies the class of normed vector spaces cannot be defined by metric equations, differently from the classical case where the class of vector spaces is equational. This phenomenon suggests that metric equations are not a very natural class of formulas since they cannot express such a typical class of metric algebras. Therefore we need a broader class of formulas to acquire an appropriate metric counterpart of the classical variety theory.
An Artificial-Noise-Aided Hybrid TS/PS Scheme for OFDM-Based SWIPT Systems
Venue: arXiv cs.NI 2016
Year: 2016

We propose a new artificial-noise aided hybrid time-switching/power-splitting scheme for orthogonal frequency-division multiplexing (OFDM) systems to securely transmit data and transfer energy to a legitimate receiving node. In our proposed scheme, the cyclic prefix has two more benefits in addition to the cancellation of the inter-symbol interference between the OFDM blocks. Firstly, it enables the legitimate transmitter to send artificial-noise (AN) vectors in a way such that the interference can be canceled at the legitimate receiver prior to information decoding. Secondly, its power is used to energize the legitimate receiver. We optimize the cyclic prefix length, the time-switching and power-splitting parameters, and the power allocation ratio between the data and AN signals at the legitimate transmitter to maximize the average secrecy rate subject to a constraint on the average energy transfer rate at the legitimate receiver. Our numerical results demonstrate that our proposed scheme can achieve up to 23% average secrecy rate gain relative to a pure power-splitting scheme.
Cross-Modal Manifold Learning for Cross-modal Retrieval
Venue: arXiv cs.CV 2016
Year: 2016

This paper presents a new scalable algorithm for cross-modal similarity preserving retrieval in a learnt manifold space. Unlike existing approaches that compromise between preserving global and local geometries, the proposed technique respects both simultaneously during manifold alignment. The global topologies are maintained by recovering underlying mapping functions in the joint manifold space by deploying partially corresponding instances. The inter-, and intra-modality affinity matrices are then computed to reinforce original data skeleton using perturbed minimum spanning tree (pMST), and maximizing the affinity among similar cross-modal instances, respectively. The performance of proposed algorithm is evaluated upon two multimodal image datasets (coronary atherosclerosis histology and brain MRI) for two applications: classification, and regression. Our exhaustive validations and results demonstrate the superiority of our technique over comparative methods and its feasibility for improving computer-assisted diagnosis systems, where disease-specific complementary information shall be aggregated and interpreted across modalities to form the final decision.
Complex Network Tools to Understand the Behavior of Criminality in Urban Areas
Venue: arXiv cs.SI 2016
Year: 2016

Complex networks are nowadays employed in several applications. Modeling urban street networks is one of them, and in particular to analyze criminal aspects of a city. Several research groups have focused on such application, but until now, there is a lack of a well-defined methodology for employing complex networks in a whole crime analysis process, i.e. from data preparation to a deep analysis of criminal communities. Furthermore, the "toolset" available for those works is not complete enough, also lacking techniques to maintain up-to-date, complete crime datasets and proper assessment measures. In this sense, we propose a threefold methodology for employing complex networks in the detection of highly criminal areas within a city. Our methodology comprises three tasks: (i) Mapping of Urban Crimes; (ii) Criminal Community Identification; and (iii) Crime Analysis. Moreover, it provides a proper set of assessment measures for analyzing intrinsic criminality of communities, especially when considering different crime types. We show our methodology by applying it to a real crime dataset from the city of San Francisco - CA, USA. The results confirm its effectiveness to identify and analyze high criminality areas within a city. Hence, our contributions provide a basis for further developments on complex networks applied to crime analysis.
Data-Driven Relevance Judgments for Ranking Evaluation
Venue: arXiv cs.IR 2016
Year: 2016

Ranking evaluation metrics are a fundamental element of design and improvement efforts in information retrieval. We observe that most popular metrics disregard information portrayed in the scores used to derive rankings, when available. This may pose a numerical scaling problem, causing an under- or over-estimation of the evaluation depending on the degree of divergence between the scores of ranked items. The purpose of this work is to propose a principled way of quantifying multi-graded relevance judgments of items and enable a more accurate penalization of ordering errors in rankings. We propose a data-driven generation of relevance functions based on the degree of the divergence amongst a set of items' scores and its application in the evaluation metric Normalized Discounted Cumulative Gain (nDCG). We use synthetic data to demonstrate the interest of our proposal and a combination of data on news items from Google News and their respective popularity in Twitter to show its performance in comparison to the standard nDCG. Results show that our proposal is capable of providing a more fine-grained evaluation of rankings when compared to the standard nDCG, and that the latter frequently under- or over-estimates its evaluation scores in light of the divergence of items' scores.
Curved Surface Patches for Rough Terrain Perception
Venue: arXiv cs.RO 2016
Year: 2016

Attaining animal-like legged locomotion on rough outdoor terrain with sparse foothold affordances -a primary use-case for legs vs other forms of locomotion- is a largely open problem. New advancements in control and perception have enabled bipeds to walk on flat and uneven indoor environments. But tasks that require reliable contact with unstructured world surfaces, for example walking on natural rocky terrain, need new perception and control algorithms. This thesis introduces 3D perception algorithms for contact tasks such as foot placement in rough terrain environments. We introduce a new method to identify and model potential contact areas between the robot's foot and a surface using a set of bounded curved patches. We present a patch parameterization model and an algorithm to fit and perceptually validate patches to 3D point samples. Having defined the environment representation using the patch model, we introduce a way to assemble patches into a spatial map. This map represents a sparse set of local areas potentially appropriate for contact between the robot and the surface. The process of creating such a map includes sparse seed point sampling, neighborhood searching, as well as patch fitting and validation. Various ways of sampling are introduced including a real time bio-inspired system for finding patches statistically similar to those that humans select while traversing rocky trails. These sparse patch algorithms are integrated with a dense volumetric fusion of range data from a moving depth camera, maintaining a dynamic patch map of relevant contact surfaces around a robot in real time. We integrate and test the algorithms as part of a real-time foothold perception system on a mini-biped robot, performing foot placements on rocks.