Social Capital of Youth in a Modern City: Opportunities for Empirical Research

Modern megalopolis concentrates all groups of resources including economic, political, cultural, information, human resources, etc. The high population density, economic and geographic situation, complex multiethnic and multicultural structure of large cities contribute to certain types of values and behavioral models in the younger generation. The neo-institutional approach and social capital theory were chosen as a methodological basis. The article examines a number of methodological works devoted to various aspects of the social capital and explores the opportunity for this concept application for analysis of the protest behavior motivation and assessment of the protest potential of young people. Combination of the economic model of multilevel analysis for measuring social capital by S.А. Sysoev and socio-political parameters for the empirical part allowed to clearly defining the main categories and indicators of analysis. Measuring the levels of social capital of a megalopolis with the inclusion a network component expands the range of opportunities for assessing and identifying the protest potential of large Russian cities residents.

Defining the Rules and Basic Set of Funtional Elements for Effective Modeling of Communication Networks

Communication networks are complex information systems influenced by a vast amount of factors. It is critically important to forecast the paths that data take to verify the network, check its security and plan its updates. Model allows exploring processes that take place in the network without affecting performance and availability of a real network itself. With modelling it becomes possible to investigate the results of infrastructural changes introduced to the network before actually implementing them. It is important to be able to formally convert real network description into the model definition which preserves all data that is significant for network operation and skip data which is not. Outlining the rules for such conversion and using a limited set of basic functional components provide the ground for automatic model creation for the network of different levels of complexity.Proposed approach to modelling of communication networks is based on decomposition of the overall function of every particular real network component into a set of functions that belong to some predefined basic set. Functions of the basic set include L3 routing, L2 switching, packet filtering, NAT, etc. Model of a real network component is defined as a group of functional nodes each of which implements some function from the basic set.Configuration and current state of network components that influence its operation are also decomposed into elements each of which relates to some particular functional node. Configuration of network components is modelled as a set of configuration storage elements and current state is modelled as a set of current state storage elements.Links that connect real network components and links that connect functional nodes in the model are presented as singledirection channels that implement propagation of L2 frames thus simplifying the model due to excluding physical layer (L1) from the scope.Using the proposed approach to modelling may allow to formalize conversion of a real network descrip- tion to a model thus making automated modelling possible. By using a sufficient basic set of functional nodes it is possible to model the network containing components of any complexity level.

An Estimation and Evaluation of Network Availability in Link State Routing Networks

The internet is taking component in a developing feature in every non-public and professional activity. The real-time, delay sensitive and mission-essential purposes, community availability requirement is beforehand for internet carrier providers (ICPs). The loop-loose criterion (LLC) approach has been extensively deployed through numerous ICPs for handling the best network component failure state of affairs in fantastic internet through. The achievement of LLC lies in its inherent simplicity; however, this comes at the rate of letting certain failure. To reap complete failure safety with LLC without incurring significant extra, a singular link protection scheme, hybrid hyperlink protocol (HLP), to reap failure routing. In contrast with in advance schemes, HLP guarantees tall network in a greater surroundings pleasant way. HLP is carried out in stages. Initial level substances a surroundings pleasant LLC primarily based totally on (MNP-e). The complexity of the set of rules is decrease than that of Dijkstra’s set of rules and might gift similar to network availability with LCC (Loop-loose criterion). Moment level substances backup direction safety based on MNP-e, the area totally a minimum type of need to be protected, to fulfill the network requirement. We don't forget those algorithms in a massive spread of associated, real and actual, and the effects display that HLP can achieve lofty network without introducing apparent.

THE IMPACT OF MIGRATION PROCESSES ON THE FORMATION OF HUMAN POTENTIAL AND CAPITAL OF SEVASTOPOL

The article presents the results of the analysis of the impact of the migration factor on the dynamics of the human potential of the Sevastopol region. The huge migration growth in the city of Sevastopol over the past three years is of great interest for the study. This phenomenon cannot but influence the magnitude of the human potential of the region, the attitude of city residents to this phenomenon, as well as its network component. The conclusions made as a result of the study include: 1) migration processes occurring in the region have a huge impact on all components of regional human potential, strengthening or weakening its network social component, which underlies the structure of potential, 2) analysis and calculation of indicators showed that degradation (loss) of human potential indicators is taking place in Sevastopol, in particular, a number of factors influencing the migration growth, as well as the problems of the indigenous population associated with migration processes, were identified. 3) The study revealed a widespread hostility towards migrants among city dwellers, with whom many associate an increase in crime, a complication of the situation on the labor market and other negative trends.

OBJECT RECOGNITION FOR AUGMENTED REALITY APPLICATIONS

Developments in the field of neural networks, deep learning, and increases in computing systems’ capacity have allowed for a significant performance boost in scene semantic information extraction algorithms and their respective mechanisms. The work presented in this paper investigates the performance of various object classification- recognition frameworks and proposes a novel framework, which incorporates Super-Resolution as a preprocessing method, along with YOLO/Retina as the deep neural network component. The resulting scene analysis framework was fine-tuned and benchmarked using the COCO dataset, with the results being encouraging. The presented framework can potentially be utilized, not only in still image recognition scenarios but also in video processing.

Densely connected layer to improve VGGnet-based CRNN for Arabic handwriting text line recognition

In recent years, Deep neural networks (DNNs) have achieved great success in sequence modeling. Several deep models have been used for enhancing Handwriting Text Recognition (HTR). Among these models, Convolutional Neural Networks (CNNs) and Recurrent Neural network especially Long-Short-Term-Memory (LSTM) networks achieve state-of-the-art recognition accuracy. The recognition methods for Arabic text lines have been widely applied in many specific tasks. However, there are still some potential challenges as the lack of available and large Arabic text recognition dataset and the characteristics of Arabic script. In order to address these challenges, we propose an end-to-end recognition method based on convolutional recurrent neural networks (CRNNs), which adds feature reuse network component on the basis of a CRNN. The model is trained and tested on two Arabic text recognition datasets named KHATT and AHTID/MW. The experimental results demonstrate that the proposed method achieves better performance than other methods in the literature.

Evaluating and Improving a Content Delivery Network (CDN) Workflow using Stochastic Modelling

Content Delivery Networks (CDN) are the backbone of Internet. A lot of research has been done to make CDNs more reliable. Despite that, the world has suffered from CDN inefficiencies quite a few times, not just due to external hacking attempts but due to internal failures as well. In this research work the authors have analyzed the performance of a content delivery network through various reliability measures. Considering a basic CDN workflow they have calculated the reliability and availability of the proposed multi-state system using Markov process and Laplace transformation. Software/Hardware failures in any network component can affect the reliability of the whole system. Therefore, the authors have analyzed the obtained results to find major causes of failures in the system, which when avoided, can lead to a faster and more efficient distribution network.

Decision Factors behind Cisco Networking Hardware Acceptance in Business Environments

Networking hardware might be considered a relatively unexposed enabler of the enormous success of the modern digital economy, and information technology of a global reach. The COVID-19 traffic spike across e-commerce portals puts further pressure on computer network component vendors and raises the bar regarding both performance and reliability. Therefore, the authors undertake a challenge of identifying factors influencing the level of Cisco switches acceptance among network administrators in business environments. To achieve that, Structural Equation Modelling is introduced. The feedback gathered from 205 study contributors enabled the authors to evaluate the significance of two domain-specific factors—Technological Innovation (TI) and Availability of Professional Training (APT). The APT was confirmed to have a significant impact on networking hardware acceptance. The study contributes to extending the decision-making rationale regarding the procurement of networking switches and shows the added value of technology-oriented professional training for job satisfaction and working efficiency.