Ідентифікація сигналів в трактах керування платформи гексапода

The paper deals method of identification useful signals, the disturbance and interference operatinghexapod platform management system for modeling large-scale marine spatial pitching shipПроведена идентификация полезных сигналов, возмущений и помех, действующих в системе управления платформы гексапода при моделировании пространственной качки крупнотоннажного морского суднаПроведено ідентифікацію корисних сигналів, збурень і завад, що діють у системі керування платформи гексаподапри моделюванні просторової качки крупнотонажного морського судн

Multi-view Face Detection Using Deep Convolutional Neural Networks

In this paper we consider the problem of multi-view face detection. While there has been significant research on this problem, current state-of-the-art approaches for this task require annotation of facial landmarks, e.g. TSM [25], or annotation of face poses [28, 22]. They also require training dozens of models to fully capture faces in all orientations, e.g. 22 models in HeadHunter method [22]. In this paper we propose Deep Dense Face Detector (DDFD), a method that does not require pose/landmark annotation and is able to detect faces in a wide range of orientations using a single model based on deep convolutional neural networks. The proposed method has minimal complexity; unlike other recent deep learning object detection methods [9], it does not require additional components such as segmentation, bounding-box regression, or SVM classifiers. Furthermore, we analyzed scores of the proposed face detector for faces in different orientations and found that 1) the proposed method is able to detect faces from different angles and can handle occlusion to some extent, 2) there seems to be a correlation between dis- tribution of positive examples in the training set and scores of the proposed face detector. The latter suggests that the proposed methods performance can be further improved by using better sampling strategies and more sophisticated data augmentation techniques. Evaluations on popular face detection benchmark datasets show that our single-model face detector algorithm has similar or better performance compared to the previous methods, which are more complex and require annotations of either different poses or facial landmarks.Comment: in International Conference on Multimedia Retrieval 2015 (ICMR

Hofstadter butterfly as Quantum phase diagram

The Hofstadter butterfly is viewed as a quantum phase diagram with infinitely many phases, labelled by their (integer) Hall conductance, and a fractal structure. We describe various properties of this phase diagram: We establish Gibbs phase rules; count the number of components of each phase, and characterize the set of multiple phase coexistence.Comment: 4 prl pages 1 colored figure typos corrected, reference [26] added, "Ten Martini" assumption adde

Financial statements of a company as an information base for decision-making in a transforming economy

In connection with the development of transforming the economy, the need for forecasting and analyzing the consequences of managerial decisions becomes more pressing. To substantiate and evaluate such decisions, a tool for prospective analysis of financial statements of companies is used. In recent years, the content and structure of a company's financial statements have undergone significant changes. With the development of economic relations, the principles of organization and methodology of accounting and reporting are also dynamically changing. The issues of reforming financial statements of a company are constantly discussed at international congresses of accountants and other professional forums. The purpose of the study is to improve the concept of preparing financial statements of a company as an information base for taking decisions in a transforming economy. As a result of the research, the economic essence of company's financial statements is substantiated from the point of view of an integrated approach; the importance of financial statements of an organization for effective management is determined; the main financial and non-financial indicators are systematized; it is proposed to introduce a mandatory requirement for disclosure of non-financial indicators in the corporate reporting system; proposals have been elaborated to improve the methods for analyzing financial statements as a tool for managing a company.peer-reviewe

Security and Efficiency Analysis of the Hamming Distance Computation Protocol Based on Oblivious Transfer

open access articleBringer et al. proposed two cryptographic protocols for the computation of Hamming distance. Their first scheme uses Oblivious Transfer and provides security in the semi-honest model. The other scheme uses Committed Oblivious Transfer and is claimed to provide full security in the malicious case. The proposed protocols have direct implications to biometric authentication schemes between a prover and a verifier where the verifier has biometric data of the users in plain form. In this paper, we show that their protocol is not actually fully secure against malicious adversaries. More precisely, our attack breaks the soundness property of their protocol where a malicious user can compute a Hamming distance which is different from the actual value. For biometric authentication systems, this attack allows a malicious adversary to pass the authentication without knowledge of the honest user's input with at most $O(n)$ complexity instead of $O(2^n)$, where $n$ is the input length. We propose an enhanced version of their protocol where this attack is eliminated. The security of our modified protocol is proven using the simulation-based paradigm. Furthermore, as for efficiency concerns, the modified protocol utilizes Verifiable Oblivious Transfer which does not require the commitments to outputs which improves its efficiency significantly

Study of collective radial breathing-like modes in double-walled carbon nanotubes: Combination of continuous two-dimensional membrane theory and Raman spectroscopy

Radial breathing modes (RBMs) are widely used for the atomic structure characterization and index assignment of single-walled carbon nanotubes (SWNTs) from resonant Raman spectroscopy. However, for double-walled carbon nanotubes (DWNTs), the use of conventional ¿RBM(d) formulas is complicated due to the van der Waals interaction between the layers, which strongly affects the frequencies of radial modes and leads to new collective vibrations. This paper presents an alternative way to theoretically study the collective radial breathing-like modes (RBLMs) of DWNTs and to account for interlayer interaction, namely the continuous two-dimensional membrane theory. We obtain an analytical ¿RBLM(do, di) relation, being the equivalent of the conventional ¿RBM(d) expressions, established for SWNTs. We compare our theoretical predictions with Raman data, measured on individual index-identified suspended DWNTs, and find a good agreement between experiment and theory. Moreover, we show that the interlayer coupling in individual DWNTs strongly depends on the interlayer distance, which is manifested in the frequency shifts of the RBLMs with respect to the RBMs of the individual inner and outer tubes. In terms of characterization, this means that the combination of Raman spectroscopy data and predictions of continuous membrane theory may give additional criteria for the index identification of DWNTs, namely the interlayer distance

Комплекс для амбулаторной диагностики сердечно-сосудистой системы

В цій роботі було розглянуто методи вивчення ССС, та визначено найефективніші методи для проведення обстеження пацієнтів у амбулаторних умовах, а також для контролю динаміки і дослідження ефективності терапевтичного процесу. Виявлено, що найбільш доцільно для даних цілей використовувати комплекс, що складається з реографу (що містить всі методи реографії), електрокардіографу і фотоплетизмографу. Для ергономічності роботи даний комплекс має містити бездротову комутацію і телеметричний модуль для роботи у єдиній мережі медичного закладу.In this paper the methods of studying the cardiovascular system, and identified the most effective methods for the examination of patients in outpatient settings, as well as to control the dynamics and effectiveness study of the therapeutic process. Revealed that the most appropriate for these purposes to use complex consisting of rheograph (which includes all methods rheography), electrocardiograph and photopletismograph. For ergonomic work this package should include switching and wireless telemetry module for a single network of medical institutions.В данной работе были рассмотрены методы изучения ССС, и определены наиболее эффективные методы для проведения обследования пациентов в амбулаторных условиях, а также для контроля динамики и исследование эффективности терапевтического процесса. Выявлено, что наиболее целесообразно для данных целей использовать комплекс, состоящий из реографа (включающий все методы реографии), электрокардиографа и фотоплетизмографа. Для эргономичности работы данный комплекс должен включать беспроводную коммутацию и телеметрический модуль для работы в единой сети медицинского учреждения

Electroanatomic substrate of atrial fibrillation in patients after COVID-19

Aim. To determine the features of left atrial electroanatomic structure and the arrhythmia substrate in patients with atrial fibrillation (AF) after coronavirus disease 2019 (COVID-19).Material and methods. The pilot study included 20 patients with AF who underwent catheter radiofrequency ablation. Ten patients had COVID-19 and 10 patients were included as a control group. AF substrate was identified using anatomic and bipolar mapping. Zones with following amplitudes were analyzed: <0,25 mV, <0,5 mV, from 0,5 to 0,75 mV inclusive, and >0,75 mV. Left atrial volume was determined based on anatomic map.Results. The groups were homogeneous in AF type, number of patients after prior pulmonary vein isolation, and heart rate during mapping. In the COVID-19 group, there was a higher area of fibrous zones with an amplitude of <0,25 mV (51,5±16,6% vs 29,1±16,1% in the control group, p=0,007), <0,5 mV (76,7±11,5% vs 45,6±22,7% in the control group, p=0,001) and a lower area of intact myocardium with an amplitude >0,75 mV (11,6±8,0% vs 45,0±25,0% in the control group, p=0,001). In 7 COVID-19 patients, the posterior wall was isolated due to low-amplitude zones. Of these, three patients underwent surgery for the first time. According to ROC analysis, in patients after COVID-19, fibrous tissue (<0,5 mV) occupies more than half of the area, while normal tissue (>0,75 mV) — ~30% or less.Conclusion. This study shows that SARS-CoV-2 infection may cause left atrial remodeling in the form of diffuse fibrosis. The arrhythmia substrate in patients after COVID-19 can be localized not only in pulmonary vein mouths, but also in other left atrial areas. This must be taken into account before ablation, even if the procedure is being performed for the first time. It is recommended to perform amplitude mapping for all patients who have had SARS-CoV-2 infection in order to identify fibrous zones and plan the operation extent

Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach

Despite several attacks have been proposed, text-based CAPTCHAs are still being widely used as a security mechanism. One of the reasons for the pervasive use of text captchas is that many of the prior attacks are scheme-specific and require a labor-intensive and time-consuming process to construct. This means that a change in the captcha security features like a noisier background can simply invalid an earlier attack. This paper presents a generic, yet effective text captcha solver based on the generative adversarial network. Unlike prior machine-learning-based approaches that need a large volume of manually-labeled real captchas to learn an effective solver, our approach requires significantly fewer real captchas but yields much better performance. This is achieved by first learning a captcha synthesizer to automatically generate synthetic captchas to learn a base solver, and then fine-tuning the base solver on a small set of real captchas using transfer learning. We evaluate our approach by applying it to 33 captcha schemes, including 11 schemes that are currently being used by 32 of the top-50 popular websites including Microsoft, Wikipedia, eBay and Google. Our approach is the most capable attack on text captchas seen to date. It outperforms four state-of-the-art text-captcha solvers by not only delivering a significant higher accuracy on all testing schemes, but also successfully attacking schemes where others have zero chance. We show that our approach is highly efficient as it can solve a captcha within 0.05 second using a desktop GPU. We demonstrate that our attack is generally applicable because it can bypass the advanced security features employed by most modern text captcha schemes. We hope the results of our work can encourage the community to revisit the design and practical use of text captchas