Artificial Pupil Dilation for Data Augmentation in Iris Semantic Segmentation

Biometrics is the science of identifying an individual based on their intrinsic anatomical or behavioural characteristics, such as fingerprints, face, iris, gait, and voice. Iris recognition is one of the most successful methods because it exploits the rich texture of the human iris, which is unique even for twins and does not degrade with age. Modern approaches to iris recognition utilize deep learning to segment the valid portion of the iris from the rest of the eye, so it can then be encoded, stored and compared. This paper aims to improve the accuracy of iris semantic segmentation systems by introducing a novel data augmentation technique. Our method can transform an iris image with a certain dilation level into any desired dilation level, thus augmenting the variability and number of training examples from a small dataset. The proposed method is fast and does not require training. The results indicate that our data augmentation method can improve segmentation accuracy up to 15% for images with high pupil dilation, which creates a more reliable iris recognition pipeline, even under extreme dilation.Comment: 6 pages, 7 figures, 2 table

Pendency and Thickets

This article empirically investigates the results of an expert-based method to identify 'patent thickets' for a unique USPTO dataset. The research aims to identify the overall effect of patent thickets on patent pendency. We find that patents belonging to a thicket are, on average, granted protection sooner. At the same time, we show that patent groups with higher thicket frequency have higher average pendency time, as do patents within larger thickets. Both suggest spillovers in processing time across patents. We additionally find mild support that the first patent in a thicket has a longer pendency period

Robust zero-energy modes in an electronic higher-order topological insulator: the dimerized Kagome lattice

Quantum simulators are an essential tool for understanding complex quantum materials. Platforms based on ultracold atoms in optical lattices and photonic devices led the field so far, but electronic quantum simulators are proving to be equally relevant. Simulating topological states of matter is one of the holy grails in the field. Here, we experimentally realize a higher-order electronic topological insulator (HOTI). Specifically, we create a dimerized Kagome lattice by manipulating carbon-monoxide (CO) molecules on a Cu(111) surface using a scanning tunneling microscope (STM). We engineer alternating weak and strong bonds to show that a topological state emerges at the corner of the non-trivial configuration, while it is absent in the trivial one. Contrarily to conventional topological insulators (TIs), the topological state has two dimensions less than the bulk, denoting a HOTI. The corner mode is protected by a generalized chiral symmetry, which leads to a particular robustness against perturbations. Our versatile approach to quantum simulation with artificial lattices holds promises of revealing unexpected quantum phases of matter

Sign language recognition using wearable electronics: Implementing K-nearest neighbors with dynamic time warping and convolutional neural network algorithms

We propose a sign language recognition system based on wearable electronics and two different classification algorithms. The wearable electronics were made of a sensory glove and inertial measurement units to gather fingers, wrist, and arm/forearm movements. The classifiers were k-Nearest Neighbors with Dynamic Time Warping (that is a non-parametric method) and Convolutional Neural Networks (that is a parametric method). Ten sign-words were considered from the Italian Sign Language: cose, grazie, maestra, together with words with international meaning such as google, internet, jogging, pizza, television, twitter, and ciao. The signs were repeated one-hundred times each by seven people, five male and two females, aged 29–54 y ± 10.34 (SD). The adopted classifiers performed with an accuracy of 96.6% ± 3.4 (SD) for the k-Nearest Neighbors plus the Dynamic Time Warping and of 98.0% ± 2.0 (SD) for the Convolutional Neural Networks. Our system was made of wearable electronics among the most complete ones, and the classifiers top performed in comparison with other relevant works reported in the literature

Higher-order topological pumping

The discovery of the quantization of particle transport in adiabatic pumping cycles of periodic structures by Thouless [Thouless D. J., Phys. Rev. B 27, 6083 (1983)] linked the Chern number, a topological invariant characterizing the quantum Hall effect in two-dimensional electron gases, with the topology of dynamical periodic systems in one dimension. Here, we demonstrate its counterpart for higher-order topology. Specifically, we show that adiabatic cycles in two-dimensional crystals with vanishing dipole moments (and therefore zero `particle transport') can nevertheless be topologically nontrivial. These cycles are associated with higher-order topology and can be diagnosed by their ability to produce corner-to-corner transport in certain metamaterial platforms. We experimentally verify this transport by using an array of photonic waveguides modulated in their separations and refractive indices. By mapping the dynamical phenomenon demonstrated here from two spatial and one temporal to three spatial dimensions, this transport is equivalent to the observation of the chiral nature of the gapless hinge states in a three-dimensional second-order topological insulator.Comment: Main text: 5 pages, 3 figures. Supp. Info: 8 pages, 5 figure

Exploring 4D Quantum Hall Physics with a 2D Topological Charge Pump

The discovery of topological states of matter has profoundly augmented our understanding of phase transitions in physical systems. Instead of local order parameters, topological phases are described by global topological invariants and are therefore robust against perturbations. A prominent example thereof is the two-dimensional integer quantum Hall effect. It is characterized by the first Chern number which manifests in the quantized Hall response induced by an external electric field. Generalizing the quantum Hall effect to four-dimensional systems leads to the appearance of a novel non-linear Hall response that is quantized as well, but described by a 4D topological invariant - the second Chern number. Here, we report on the first observation of a bulk response with intrinsic 4D topology and the measurement of the associated second Chern number. By implementing a 2D topological charge pump with ultracold bosonic atoms in an angled optical superlattice, we realize a dynamical version of the 4D integer quantum Hall effect. Using a small atom cloud as a local probe, we fully characterize the non-linear response of the system by in-situ imaging and site-resolved band mapping. Our findings pave the way to experimentally probe higher-dimensional quantum Hall systems, where new topological phases with exotic excitations are predicted

Electrohysterographic characterization of the uterine myoelectrical response to labor induction drugs

[EN] Labor induction is a common practice to promote uterine contractions and labor onset. Uterine electrohysterogram (EHG) has proved its suitability for characterizing the uterus electrophysiological condition in women with spontaneous labor. The aim of this study was to characterize and compare uterine myoelectrical activity during the first 4h in response to labor induction drugs, Misoprostol (G1) and Dinoprostone (G2), by analyzing the differences between women who achieved active phase of labor and those who did not (successful and failed inductions). A set of temporal, spectral and complexity parameters were computed from the EHG-bursts. As for successful inductions, statistical significant and sustained increases with respect to basal period were obtained for EHG amplitude, mean frequency, uterine activity index (UAI) and Teager, after 60¿ for the G1 group; duration, amplitude, number of contractions and UAI for the G2 group, after 120¿. Moreover, Teager showed statistical significant and sustained differences between successful and failed inductions (1.43±1.45 µV2.Hz2.105 vs. 0.40±0.26 µV2.Hz2.105 after 240¿) for the G1 group, but not in the G2 group, probably due to the slower pharmacokinetics of this drug. These results revealed that EHG could be useful for successful induction prediction in the early stages of induction, especially when using Misoprostol.This research project was supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (DPI2015-68397-R) and by the company Bial SA.Benalcazar-Parra, C.; Ye Lin, Y.; Garcia Casado, J.; Monfort-Orti, R.; Alberola Rubio, J.; Perales Marín, AJ.; Prats-Boluda, G. (2018). Electrohysterographic characterization of the uterine myoelectrical response to labor induction drugs. Medical Engineering & Physics. 56:27-35. https://doi.org/10.1016/j.medengphy.2018.04.002S27355

Propozycja polskiego rynku mocy vs model brytyjski

Recently there has been a significant debate about the possible implementation of a centralized capacity mechanism in Poland. Despite the fact that capacity adequacy is currently being discussed at the national level as a long-term issue, the lack of sufficient capacity and insufficient demand flexibility has already been observed on a number of occasions. In July 2016, the Polish Ministry of Energy expressed its support for the implementation of a market-wide capacity mechanisms. In view of these recent events, the aim of this paper is to shed some light on the possible implementation of a capacity market in Poland. The paper presents a brief overview of the key problems that the Polish power sector faces and provides a comparative analysis between some of the main elements of the Polish capacity market proposal and the GB capacity market.W ostatnim czasie rozpoczęła się ważna debata na temat możliwego wdrożenia scentralizowanego mechanizmu mocowego w Polsce. Mimo tego że adekwatność zasobów jest obecnie omawiana na szczeblu krajowym jako kwestia długoterminowa, wielokrotnie podkreślano brak wystarczającej mocy i niewystarczającą elastyczność popytu. W lipcu 2016 roku polskie Ministerstwo Energii wyraziło poparcie dla wdrożenia mechanizmów mocy o zasięgu rynkowym. Biorąc więc pod uwagę ostatnie wydarzenia, celem niniejszego artykułu jest rzucenie światła na możliwość wdrożenia rynku mocy w Polsce. Praca prezentuje zwięzłe omówienie kluczowych problemów polskiego sektora wytwarzania i dostarcza analizy głównych elementów propozycji polskiego rynku mocy w kontekście rozwiązań wdrożonych w Wielkiej Brytanii

Koncepcja optymalizacji funkcjonowania sieci magazynów – wzrost efektywności systemów logistycznych

Over the last twenty years, there has been a deep change in the energy consumption of freight transport and the economics of logistics and the supply chain. Increasing competition forced supply chain networks to reconsider and restructure their business models in order to increase their sustainability and, consequently, reduce fuel consumption. Companies have turned to optimization models in order to find the best possible supply chain network configuration. This paper presents an overview of the current global energy consumption of the transport sector, in particular the road freight transport sector, and a review of literature on facility location models. Additionally, this paper proposes a conceptual basis for the formulation of a mixed-integer linear programming model that can be applied for the verification of warehouse locations in a supply chain network. The concept of the proposed model is formulated in a way that will lead to cost savings. The model will serve as a decision-support tool for distribution network optimization. The proposed concept includes in its objective function warehousing costs and transportation costs.W ciągu ostatnich dwudziestu lat doszło do istotnych zmian w zużyciu energii w sektorze transportu towarowego oraz w ekonomice procesów logistycznych i łańcucha dostaw. Rosnąca konkurencja wymusiła restrukturyzację oraz wzrost efektywności modeli biznesowych ukierunkowanych na zrównoważony rozwój, co w konsekwencji prowadzi do zmniejszenia zużycia paliw. Przedsiębiorstwa zwracają coraz większą uwagę na modele optymalizacyjne, pozwalające na wypracowanie najlepszych konfiguracji sieci łańcucha dostaw. W artykule przedstawiono analizę aktualnego zużycia energii w sektorze transportowym, w szczególności w sektorze drogowego transportu towarowego oraz dokonano przeglądu literatury w obszarze modeli optymalizujących lokalizację obiektów (np. magazynów). Ponadto, w artykule zaproponowano koncepcję sformułowania modelu matematycznego wykorzystującego podejście programowania mieszanego całkowitoliczbowego liniowego, który będzie mógł być zastosowany do opracowania i weryfikacji lokalizacjach magazynów. Model ten umożliwi redukcję kosztów prowadzenia działalności w obszarze gospodarki magazynowej. Będzie on służyć jako narzędzie wspomagania decyzji dla optymalizacji sieci dystrybucji. W funkcji celu przedmiotowego modelu uwzględnione zostaną koszty magazynowania oraz koszty transportu