OpenRaiser/Intern-Atlas huggingface dataset:
Robust imaging of hippocampal inner structure at 7T: in vivo acquisition protocol and methodological choices
Venue: arXiv cs.CV 2016
Year: 2016

OBJECTIVE:Motion-robust multi-slab imaging of hippocampal inner structure in vivo at 7T.MATERIALS AND METHODS:Motion is a crucial issue for ultra-high resolution imaging, such as can be achieved with 7T MRI. An acquisition protocol was designed for imaging hippocampal inner structure at 7T. It relies on a compromise between anatomical details visibility and robustness to motion. In order to reduce acquisition time and motion artifacts, the full slab covering the hippocampus was split into separate slabs with lower acquisition time. A robust registration approach was implemented to combine the acquired slabs within a final 3D-consistent high-resolution slab covering the whole hippocampus. Evaluation was performed on 50 subjects overall, made of three groups of subjects acquired using three acquisition settings; it focused on three issues: visibility of hippocampal inner structure, robustness to motion artifacts and registration procedure performance.RESULTS:Overall, T2-weighted acquisitions with interleaved slabs proved robust. Multi-slab registration yielded high quality datasets in 96 % of the subjects, thus compatible with further analyses of hippocampal inner structure.CONCLUSION:Multi-slab acquisition and registration setting is efficient for reducing acquisition time and consequently motion artifacts for ultra-high resolution imaging of the inner structure of the hippocampus.
Low-order continuous finite element spaces on hybrid non-conforming hexahedral-tetrahedral meshes
Venue: arXiv cs.CG 2016
Year: 2016

This article deals with solving partial differential equations with the finite element method on hybrid non-conforming hexahedral-tetrahedral meshes. By non-conforming, we mean that a quadrangular face of a hexahedron can be connected to two triangular faces of tetrahedra. We introduce a set of low-order continuous (C0) finite element spaces defined on these meshes. They are built from standard tri-linear and quadratic Lagrange finite elements with an extra set of constraints at non-conforming hexahedra-tetrahedra junctions to recover continuity. We consider both the continuity of the geometry and the continuity of the function basis as follows: the continuity of the geometry is achieved by using quadratic mappings for tetrahedra connected to tri-affine hexahedra and the continuity of interpolating functions is enforced in a similar manner by using quadratic Lagrange basis on tetrahedra with constraints at non-conforming junctions to match tri-linear hexahedra. The so-defined function spaces are validated numerically on simple Poisson and linear elasticity problems for which an analytical solution is known. We observe that using a hybrid mesh with the proposed function spaces results in an accuracy significantly better than when using linear tetrahedra and slightly worse than when solely using tri-linear hexahedra. As a consequence, the proposed function spaces may be a promising alternative for complex geometries that are out of reach of existing full hexahedral meshing methods.
Image Classification of Grapevine Buds using Scale-Invariant Features Transform, Bag of Features and Support Vector Machines
Venue: arXiv cs.CV 2016
Year: 2016

In viticulture, there are several applications where bud detection in vineyard images is a necessary task, susceptible of being automated through the use of computer vision methods. A common and effective family of visual detection algorithms are the scanning-window type, that slide a (usually) fixed size window along the original image, classifying each resulting windowed-patch as containing or not containing the target object. The simplicity of these algorithms finds its most challenging aspect in the classification stage. Interested in grapevine buds detection in natural field conditions, this paper presents a classification method for images of grapevine buds ranging 100 to 1600 pixels in diameter, captured in outdoor, under natural field conditions, in winter (i.e., no grape bunches, very few leaves, and dormant buds), without artificial background, and with minimum equipment requirements. The proposed method uses well-known computer vision technologies: Scale-Invariant Feature Transform for calculating low-level features, Bag of Features for building an image descriptor, and Support Vector Machines for training a classifier. When evaluated over images containing buds of at least 100 pixels in diameter, the approach achieves a recall higher than 0.9 and a precision of 0.86 over all windowed-patches covering the whole bud and down to 60% of it, and scaled up to window patches containing a proportion of 20%-80% of bud versus background pixels. This robustness on the position and size of the window demonstrates its viability for use as the classification stage in a scanning-window detection algorithms.
Micro-Synchrophasors for Power Distribution Monitoring, a Technology Review
Venue: arXiv cs.SY 2016
Year: 2016

The smart grid revolution is creating a paradigm shift in distribution networks that is marked by new, significant intermittencies and uncertainties in power supply and demand. These developments include the dramatic increase in the adoption of distributed energy resources (DER), electric vehicles, energy storage, and controllable loads. This transformation imposes new challenges on existing distribution infrastructure and system operations for stockholders, engineers, operators and customers. Unfortunately, distribution networks historically lag behind transmission networks in terms of observability, measurement accuracy, and data granularity. The changes in the operation of the electric grid dramatically increase the need for tools to monitor and manage distribution networks in a fast, reliable and accurate fashion. This paper describes the development process of a network of high-precision micro phasor measurement units or uPMUs, beginning with an overview of the uPMU technology that provides synchronous measurements of voltage phase angles, or synchrophasors. Next, the uPMU network and communications infrastructure are discussed, followed by an analysis of potential diagnostic and control applications of uPMU data in the electric grid at the distribution level.
Expediting Support for Social Learning with Behavior Modeling
Venue: arXiv cs.CY 2016
Year: 2016

An important research problem for Educational Data Mining is to expedite the cycle of data leading to the analysis of student learning processes and the improvement of support for those processes. For this goal in the context of social interaction in learning, we propose a three-part pipeline that includes data infrastructure, learning process analysis with behavior modeling, and intervention for support. We also describe an application of the pipeline to data from a social learning platform to investigate appropriate goal-setting behavior as a qualification of role models. Students following appropriate goal setters persisted longer in the course, showed increased engagement in hands-on course activities, and were more likely to review previously covered materials as they continued through the course. To foster this beneficial social interaction among students, we propose a social recommender system and show potential for assisting students in interacting with qualified goal setters as role models. We discuss how this generalizable pipeline can be adapted for other support needs in online learning settings.
Performance Analysis of the Gradient Comparator LMS Algorithm
Venue: arXiv cs.IT 2016
Year: 2016

The sparsity-aware zero attractor least mean square (ZA-LMS) algorithm manifests much lower misadjustment in strongly sparse environment than its sparsity-agnostic counterpart, the least mean square (LMS), but is shown to perform worse than the LMS when sparsity of the impulse response decreases. The reweighted variant of the ZA-LMS, namely RZA-LMS shows robustness against this variation in sparsity, but at the price of increased computational complexity. The other variants such as the l 0 -LMS and the improved proportionate normalized LMS (IPNLMS), though perform satisfactorily, are also computationally intensive. The gradient comparator LMS (GC-LMS) is a practical solution of this trade-off when hardware constraint is to be considered. In this paper, we analyse the mean and the mean square convergence performance of the GC-LMS algorithm in detail. The analyses satisfactorily match with the simulation results.
Separating Topological Noise from Features using Persistent Entropy
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we derive a simple method for separating topological noise from topological features using a novel measure for comparing persistence barcodes called persistent entropy.
Path-Additions of Graphs
Venue: arXiv cs.DM 2016
Year: 2016

Path-addition is an operation that takes a graph and adds an internally vertex-disjoint path between two vertices together with a set of supplementary edges. Path-additions are just the opposite of taking minors. We show that some classes of graphs are closed under path-addition, including non-planar, right angle crossing, fan-crossing free, quasi-planar, (aligned) bar 1-visibility, and interval graphs, whereas others are not closed, including all subclasses of planar graphs, bounded treewidth, k-planar, fan-planar, outer-fan planar, outer-fan-crossing free, and bar (1,j)-visibility graphs.
Grammatical Case Based IS-A Relation Extraction with Boosting for Polish
Venue: arXiv cs.CL 2016
Year: 2016

Pattern-based methods of IS-A relation extraction rely heavily on so called Hearst patterns. These are ways of expressing instance enumerations of a class in natural language. While these lexico-syntactic patterns prove quite useful, they may not capture all taxonomical relations expressed in text. Therefore in this paper we describe a novel method of IS-A relation extraction from patterns, which uses morpho-syntactical annotations along with grammatical case of noun phrases that constitute entities participating in IS-A relation. We also describe a method for increasing the number of extracted relations that we call pseudo-subclass boosting which has potential application in any pattern-based relation extraction method. Experiments were conducted on a corpus of about 0.5 billion web documents in Polish language.
Energy Shaping Control of an Inverted Flexible Pendulum Fixed to a Cart
Venue: arXiv cs.SY 2016
Year: 2016

Control of compliant mechanical systems is increasingly being researched for several applications including flexible link robots and ultra-precision positioning systems. The control problem in these systems is challenging, especially with gravity coupling and large deformations, because of inherent underactuation and the combination of lumped and distributed parameters of a nonlinear system. In this paper we consider an ultra-flexible inverted pendulum on a cart and propose a new nonlinear energy shaping controller to keep the pendulum at the upward position with the cart stopped at a desired location. The design is based on a model, obtained via the constrained Lagrange formulation, which previously has been validated experimentally. The controller design consists of a partial feedback linearization step followed by a standard PID controller acting on two passive outputs. Boundedness of all signals and (local) asymptotic stability of the desired equilibrium is theoretically established. Simulations and experimental evidence assess the performance of the proposed controller.
On the Capacity Region of Multiple Access Channel
Venue: arXiv cs.IT 2016
Year: 2016

The capacity region of a multiple access channel is discussed. It was found that orthogonal multiple access and non orthogonal multiple access have the same capacity region under the constraint of same sum power.
PARAPH: Presentation Attack Rejection by Analyzing Polarization Hypotheses
Venue: arXiv cs.CV 2016
Year: 2016

For applications such as airport border control, biometric technologies that can process many capture subjects quickly, efficiently, with weak supervision, and with minimal discomfort are desirable. Facial recognition is particularly appealing because it is minimally invasive yet offers relatively good recognition performance. Unfortunately, the combination of weak supervision and minimal invasiveness makes even highly accurate facial recognition systems susceptible to spoofing via presentation attacks. Thus, there is great demand for an effective and low cost system capable of rejecting such attacks.To this end we introduce PARAPH -- a novel hardware extension that exploits different measurements of light polarization to yield an image space in which presentation media are readily discernible from Bona Fide facial characteristics. The PARAPH system is inexpensive with an added cost of less than 10 US dollars. The system makes two polarization measurements in rapid succession, allowing them to be approximately pixel-aligned, with a frame rate limited by the camera, not the system. There are no moving parts above the molecular level, due to the efficient use of twisted nematic liquid crystals. We present evaluation images using three presentation attack media next to an actual face -- high quality photos on glossy and matte paper and a video of the face on an LCD. In each case, the actual face in the image generated by PARAPH is structurally discernible from the presentations, which appear either as noise (print attacks) or saturated images (replay attacks).
The complexity of downward closure comparisons
Venue: arXiv cs.FL 2016
Year: 2016

The downward closure of a language is the set of all (not necessarily contiguous) subwords of its members. It is well-known that the downward closure of every language is regular. Moreover, recent results show that downward closures are computable for quite powerful system models. One advantage of abstracting a language by its downward closure is that then equivalence and inclusion become decidable. In this work, we study the complexity of these two problems. More precisely, we consider the following decision problems: Given languages $K$ and $L$ from classes $\mathcal{C}$ and $\mathcal{D}$, respectively, does the downward closure of $K$ include (equal) that of $L$? These problems are investigated for finite automata, one-counter automata, context-free grammars, and reversal-bounded counter automata. For each combination, we prove a completeness result either for fixed or for arbitrary alphabets. Moreover, for Petri net languages, we show that both problems are Ackermann-hard and for higher-order pushdown automata of order~$k$, we prove hardness for complements of nondeterministic $k$-fold exponential time.
Road Detection through Supervised Classification
Venue: arXiv cs.CV 2016
Year: 2016

Autonomous driving is a rapidly evolving technology. Autonomous vehicles are capable of sensing their environment and navigating without human input through sensory information such as radar, lidar, GNSS, vehicle odometry, and computer vision. This sensory input provides a rich dataset that can be used in combination with machine learning models to tackle multiple problems in supervised settings. In this paper we focus on road detection through gray-scale images as the sole sensory input. Our contributions are twofold: first, we introduce an annotated dataset of urban roads for machine learning tasks; second, we introduce a road detection framework on this dataset through supervised classification and hand-crafted feature vectors.
Super-Resolution MIMO Radar
Venue: arXiv cs.IT 2016
Year: 2016

A multiple input, multiple output (MIMO) radar emits probings signals with multiple transmit antennas and records the reflections from targets with multiple receive antennas. Estimating the relative angles, delays, and Doppler shifts from the received signals allows to determine the locations and velocities of the targets. Standard approaches to MIMO radar based on digital matched filtering or compressed sensing only resolve the angle-delay-Doppler triplets on a $(1/(N_T N_R), 1/B,1/T)$ grid, where $N_T$ and $N_R$ are the number of transmit and receive antennas, $B$ is the bandwidth of the probing signals, and $T$ is the length of the time interval over which the reflections are observed. In this work, we show that the \emph{continuous} angle-delay-Doppler triplets and the corresponding attenuation factors can be recovered perfectly by solving a convex optimization problem. This result holds provided that the angle-delay-Doppler triplets are separated either by $10/(N_T N_R-1)$ in angle, $10.01/B$ in delay, or $10.01/T$ in Doppler direction. Furthermore, this result is optimal (up to log factors) in the number of angle-delay-Doppler triplets that can be recovered.
A Stochastic Geometric Analysis of Device-to-Device Communications Operating over Generalized Fading Channels
Venue: arXiv cs.IT 2016
Year: 2016

Device-to-device (D2D) communications are now considered as an integral part of future 5G networks which will enable direct communication between user equipment (UE) without unnecessary routing via the network infrastructure. This architecture will result in higher throughputs than conventional cellular networks, but with the increased potential for co-channel interference induced by randomly located cellular and D2D UEs. The physical channels which constitute D2D communications can be expected to be complex in nature, experiencing both line-of-sight (LOS) and non-LOS (NLOS) conditions across closely located D2D pairs. As well as this, given the diverse range of operating environments, they may also be subject to clustering of the scattered multipath contribution, i.e., propagation characteristics which are quite dissimilar to conventional Rayeligh fading environments. To address these challenges, we consider two recently proposed generalized fading models, namely $κ-μ$ and $η-μ$, to characterize the fading behavior in D2D communications. Together, these models encompass many of the most widely encountered and utilized fading models in the literature such as Rayleigh, Rice (Nakagami-$n$), Nakagami-$m$, Hoyt (Nakagami-$q$) and One-Sided Gaussian. Using stochastic geometry we evaluate the rate and bit error probability of D2D networks under generalized fading conditions. Based on the analytical results, we present new insights into the trade-offs between the reliability, rate, and mode selection under realistic operating conditions. Our results suggest that D2D mode achieves higher rates over cellular link at the expense of a higher bit error probability. Through numerical evaluations, we also investigate the performance gains of D2D networks and demonstrate their superiority over traditional cellular networks.
Physically Unclonable Function using Initial Waveform of Ring Oscillators
Venue: arXiv cs.CR 2016
Year: 2016

A silicon physically unclonable function (PUF) is considered to be one of the key security system solutions for local devices in an era in which the internet is pervasive. Among many proposals, a PUF using ring oscillators (RO-PUF) has the advantage of easy application to FPGA. In the conventional RO-PUF, frequency difference between two ROs is used as one bit of ID. Thus, in order to obtain an ID of long bit length, the corresponding number of RO pairs are required and consequently power consumption is large, leading to difficulty in implementing RO-PUF in local devices. Here, we provide a RO-PUF using the initial waveform of the ROs. Because a waveform constitutes a part of the ID, the number of ROs is greatly reduced and the time needed to generate the ID is finished in a couple of system clocks. We also propose a solution to a change of PUF performance attributable to temperature or voltage change.
A robust particle detection algorithm based on symmetry
Venue: arXiv cs.CV 2016
Year: 2016

Particle tracking is common in many biophysical, ecological, and micro-fluidic applications. Reliable tracking information is heavily dependent on of the system under study and algorithms that correctly determines particle position between images. However, in a real environmental context with the presence of noise including particular or dissolved matter in water, and low and fluctuating light conditions, many algorithms fail to obtain reliable information. We propose a new algorithm, the Circular Symmetry algorithm (C-Sym), for detecting the position of a circular particle with high accuracy and precision in noisy conditions. The algorithm takes advantage of the spatial symmetry of the particle allowing for subpixel accuracy. We compare the proposed algorithm with four different methods using both synthetic and experimental datasets. The results show that C-Sym is the most accurate and precise algorithm when tracking micro-particles in all tested conditions and it has the potential for use in applications including tracking biota in their environment.
Investigating the opportunities of using mobile learning by young children in Bulgaria
Venue: arXiv cs.CY 2016
Year: 2016

This paper provides an analysis of literature related to the use of mobile devices in teaching young children. For this purpose, the most popular mobile operating systems in Bulgaria are considered and the functionality of the existing mobile applications with Bulgarian interface is discussed. The results of a survey of parents' views regarding the mobile devices as a learning tool are presented and the ensuing conclusions are provided.
A Novel Framework for Electronic Global Health Record Access
Venue: arXiv cs.CY 2016
Year: 2016

When most patients visit physicians in a clinic or a hospital, they are asked about their medical history and related medical tests' results which might not exist or might simply have been lost over time. In emergency situations, many patients suffer or sadly die because of lack of pertinent medical information. Patient's Health information (PHI) saved by Electronic Medical Record (EMR) could be accessible only by a hospital using their EMR system. Furthermore, Personal Health Record (PHR) information cannot be solely relied on since it is controlled solely by patients. This paper introduces a novel framework for accessing, sharing, and controlling the medical records for patients and their physicians globally, while patients' PHI are securely stored and their privacy is taken into consideration. Based on the framework, a proof of concept prototype is implemented. Preliminary performance evaluation results indicate the validity and viability of the proposed framework.
COCO: Performance Assessment
Venue: arXiv cs.NE 2016
Year: 2016

We present an any-time performance assessment for benchmarking numerical optimization algorithms in a black-box scenario, applied within the COCO benchmarking platform. The performance assessment is based on runtimes measured in number of objective function evaluations to reach one or several quality indicator target values. We argue that runtime is the only available measure with a generic, meaningful, and quantitative interpretation. We discuss the choice of the target values, runlength-based targets, and the aggregation of results by using simulated restarts, averages, and empirical distribution functions.