Бюджетна безпека держави в умовах соціально-економічних трансформацій (Budget of the state security in the socio-economic transformation)

У статті виконано оцінку бюджетної безпеки держави за відповідними індикаторами. Проаналізовано основні загрози бюджетній безпеці на сучасному етапі соціально-економічного розвитку. Обгрунтовано напрями мініміза- ції та подолання бюджетних ризиків у контексті підвищення рівня бюджетної безпеки держави та забезпечення ефективності бюджетної політики в умовах соціально-економічних трансформацій. (In the article the estimation of state security budget for the respective indicators. The basic threat to public safety at the present stage of socio-economic development. The directions to minimize and overcome budgetary risks in the context of increasing the level of budget security and ensuring the effectiveness of fiscal policy in terms of socio-economic transformations.

Impact of Traffic Sign Diversity on Autonomous Vehicles: A Literature Review

Traffic sign classification is indispensable for road traffic systems, including automated ones. There is a fundamental difference in the visual appearance of traffic signs from one country to another. Each dataset has its design standards and regulations based on shape, color, and information content, making implementing classification and recognition techniques more difficult. This paper aims to assess the influence of traffic sign diversity on autonomous vehicles (AVs) by reviewing several previous studies, comparing, summarizing their results, and focusing on classifying and detecting traffic sign datasets based on color, shape, and deep learning spaces using various methods and applications. Furthermore, it covers the main challenges facing road designers and planners considering changes to road safety infrastructure. It will be argued that compiling and standardizing a comprehensive global database of traffic signs is very difficult because it is costly and complex in application. However, it is still one of the possible solutions for the coming decades. Recommendations for future developments are also presented in this study

Advances in the Ordovician graptolite biostratigraphy of the St Petersburg area, Russia

The Ordovician shallow-water shelf deposits rich in benthic fauna are exposed along the Russian part of the Baltic–Ladoga Klint. Graptolites occur only at some stratigraphic levels, being comparatively numerous in marls and clays and very rare in carbonate layers. Since the 19th century graptolites have been collected from exposures of the Pakerort, Hunneberg, Billingen, and Volkhov regional stages (Tremadocian–Dapingian), while in the Uhaku–Idavere stratigraphic interval (Darriwilian–lower Sandbian) rare graptolites have been found in boreholes. Up to now, only some collections have been systematically studied. On the basis of new graptolite finds, recently the Pterograptus elegans Biozone was established in the upper Aseri Stage and the Nemagraptus gracilis Biozone in the lower Kukruse Stage. Detailed sampling of the Shundorovo Formation (upper Idavere Stage) resulted in the discovery of numerous diplograptids at five stratigraphic levels, in association with various dendroids. These diplograptids were provisionally assigned to ?Archiclimacograptus antiquus lineatus Elles & Wood. A systematic description of the late Darriwilian and early Sandbian diplograptids is under preparation

Monolithic integration of a very low threshold GaInAsP laser and metal-insulator-semiconductor field-effect transistor on semi-insulating InP

Monolithic integration of 1.3-µm groove lasers and metal-insulator-semiconductor field-effect transistors (MISFET) is achieved by a simple single liquid phase epitaxy (LPE) growth process. Laser thresholds as low as 14 mA for 300-µm cavity length are obtained. MIS depletion mode FET's with n channels on LPE grown InP layer show typical transconductance of 5–10 mmho. Laser modulation by the FET current is demonstrated at up to twice the threshold current

When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy

In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect the privacy of location information. For this purpose, people should know their location privacy preferences, that is, whether or not he/she can release location information at each place and time. However, it is not easy for each user to make such decisions and it is troublesome to set the privacy preference at each time. Therefore, we propose a method to recommend location privacy preferences for decision making. Comparing to existing method, our method can improve the accuracy of recommendation by using matrix factorization and preserve privacy strictly by local differential privacy, whereas the existing method does not achieve formal privacy guarantee. In addition, we found the best granularity of a location privacy preference, that is, how to express the information in location privacy protection. To evaluate and verify the utility of our method, we have integrated two existing datasets to create a rich information in term of user number. From the results of the evaluation using this dataset, we confirmed that our method can predict location privacy preferences accurately and that it provides a suitable method to define the location privacy preference

Flux Approximation Scheme for the Incompressible Navier-Stokes Equations Using Local Boundary Value Problems

We present a flux approximation scheme for the incompressible Navier- Stokes equations, that is based on a flux approximation scheme for the scalar advection-diffusion-reaction equation that we developed earlier. The flux is computed from local boundary value problems (BVPs) and is expressed as a sum of a homogeneous and an inhomogeneous part. The homogeneous part depends on the balance of the convective and viscous forces and the inhomogeneous part depends on source terms included in the local BVP.</p

Online Independent Set Beyond the Worst-Case: Secretaries, Prophets, and Periods

We investigate online algorithms for maximum (weight) independent set on graph classes with bounded inductive independence number like, e.g., interval and disk graphs with applications to, e.g., task scheduling and spectrum allocation. In the online setting, it is assumed that nodes of an unknown graph arrive one by one over time. An online algorithm has to decide whether an arriving node should be included into the independent set. Unfortunately, this natural and practically relevant online problem cannot be studied in a meaningful way within a classical competitive analysis as the competitive ratio on worst-case input sequences is lower bounded by $\Omega(n)$. As a worst-case analysis is pointless, we study online independent set in a stochastic analysis. Instead of focussing on a particular stochastic input model, we present a generic sampling approach that enables us to devise online algorithms achieving performance guarantees for a variety of input models. In particular, our analysis covers stochastic input models like the secretary model, in which an adversarial graph is presented in random order, and the prophet-inequality model, in which a randomly generated graph is presented in adversarial order. Our sampling approach bridges thus between stochastic input models of quite different nature. In addition, we show that our approach can be applied to a practically motivated admission control setting. Our sampling approach yields an online algorithm for maximum independent set with competitive ratio $O(\rho^2)$ with respect to all of the mentioned stochastic input models. for graph classes with inductive independence number $\rho$. The approach can be extended towards maximum-weight independent set by losing only a factor of $O(\log n)$ in the competitive ratio with $n$ denoting the (expected) number of nodes