Applying Time Series for Background User Identification Based on Their Text Data Analysis
This study explores relationship between the Internet and the Russian national election of 2011-2012. In contrast to other studies, we focus on the blogosphere as a political factor. Our conclusions are based on a study of the LiveJournal blogging platform represented by a sample of political posts from the top 2000 bloggers for 13 week-long periods. Sampling from the population of about 180,000 posts was performed automatically with a topic modelling algorithm, while the analysis of the resulting 3690 texts was carried out manually by five coders. We found that the most influential Russian blogs perform the role of a media “stronghold” of the political opposition. Moreover, we established a relationship between the weekly pre-election ratings of the opposition parties and presidential candidates and the indicators of political activity in the blogosphere. Our results cautiously suggest that political activity on the Internet is not simply an online projection of offline political activity: it can itself provoke activity in offline political life.
Modeling the processes in a healthcare system plays a large role in understanding its activities and serves as the basis for increasing the efficiency of medical institutions. The tasks of analyzing and modeling large amounts of urban healthcare data using machine learning methods are of particular importance and relevance for the development of industry solutions in the framework of digitalization of the economy, where data is the key factor in production. The problem of automatic analysis and determination of clinical pathways groups of patients based on clustering methods is considered in this research. Existing projects in this area reflect a great interest on the part of the scientific community in such studies; however, there is a need to develop a number of methodological approaches for their further practical application in urban outpatient institutions, taking into account the specifics of the organization being analyzed. The aim of the study is to improve the quality of management and segmentation of patient input flow in urban medical institutions based on cluster analysis methods for the further development of recommendation services. One approach to achieving this goal is the development and implementation of clinical pathways, or patient trajectories. In general, the clinical pathway of a patient might be interpreted as the trajectory when receiving medical services in respective institutions. The approach of developing groups of patient routes by the hierarchical agglomerative algorithm with the Ward method and Additive Regularization of Topic Models (ARTM) is presented in this article. A computational experiment based on public data on the routes of patients with a diagnosis of sepsis is described. One feature of the proposed approach is not just the automation of the determination of similar groups of patient trajectories, but also the consideration of clinical pathways patterns to form recommendations for organizing the resource allocation of a medical institution. The proposed approach to segmenting the input heterogeneous flow of patients in urban medical institutions on the basis of clustering consists of the following steps: 1) preparing the data of the medical institution in the format of an event log; 2) encoding patient routes; 3) determination of the upper limit of the clinical pathway length; 4) hierarchical agglomerative clustering; 5) additive regularization of topic models (ARTM); 6) identifying popular patient route patterns. The resulting clusters of routes serve as the foundation for the further development of a simulation model of a medical institution and provide recommendations to patients. In addition, these groups may underlie the development of the robotic process automation system (RPA), which simulates human actions and allows you to automate the interpretation of data to manage the resources of the institution.
The book contains selected papers that were presented on PhD Summer schools on Scientific Computing jointly organized by Waterford Institute of Technology, Lomonosov Moscow State University, Kyiv National Taras Shevchenko University, Saint-Petersburg State University and Nanjing University of Technology. The schoold were mainly organized in teleconference mode and linked researchers and PhD students from several countries.
The paper reveals the topic structure of ethnic discussions in the Russian-speaking social media and explores how these topics are related to the post-Soviet ethnic groups. Analyzed more than 2.6 million texts from Russian-speak- ing social media published for two-year period from 2014 to 2015 and contained at least one of the post-Soviet ethnonyms, we conclude that ethnic discussions in these media are full of socially significant and potentially problematic topics (15 topics out of 97 can be regarded as problematic comparing to the 4 out of 150 topics on random sample from VK.com). The most salient topics are the topics about Ukraine-Russia relations over the recent conflict between two countries. We also found the racial bias in criminal topic towards peoples of the North Caucasus which are often mentioned in the context of crimes and terrorism.
The article deals with the problems of ensuring functional, informational and cyber security for vehicles and transport infrastructure facilities. The analysis of the factors causing the growth of threats to the transport sector has been carried out, the list of typical cyber attacks on the components of the transport infrastructure is given. The results of the analysis of the features of automated process control systems of technological processes of vehicles and transport infrastructure facilities are presented. Recommendations on the development of transport security systems are given taking into account the specifics of various types of transport
This volume contains the papers selected for presentation at the 18th European Symposium on Research in Computer Security (ESORICS 2013), held during September 9–13, 2013, in Egham, UK. In response to the symposium’s call for papers, 242 papers were submitted to the conference from 38 countries. These papers were evaluated on the basis of their significance, novelty, technical quality, as well as on their practical impact and/or their level of advancement of the field’s foundations. The Program Committee’s work was carri ed out electronically, yielding in- tensive discussions over a period of a few weeks. Of the papers submitted, 43 were selected for presentation at the conf erence (resulting in an acceptance rate of 18%). We note that many top-quality submissions were not selected for pre- sentation because of the high technical level of the overall submissions, and we are certain that many of these submissions will, nevertheless, be published at other competitive forums in the future.
It is well-known that the Dolev-Yao adversary is a powerful adversary. Besides acting as the network, intercepting, sending, and composing messages, he can remember as much information as he needs. That is, his memory is unbounded.
We recently proposed a weaker Dolev-Yao like adversary, which also acts as the network, but whose memory is bounded. We showed that this Bounded Memory Dolev-Yao adversary, when given enough memory, can carry out many existing protocol anomalies. In particular, the known anomalies arise for bounded memory protocols, where there is only a bounded number of concurrent sessions and the honest participants of the protocol cannot remember an unbounded number of facts nor an unbounded number of nonces at a time. This led us to the question of whether it is possible to infer an upper-bound on the memory required by the Dolev-Yao adversary to carry out an anomaly from the memory restrictions of the bounded protocol. This paper answers this question negatively (Theorem 2).
The second contribution of this paper is the formalization of Progressing Collaborative Systems that may create fresh values, such as nonces. In this setting there is no unbounded adversary, although bounded memory adversaries may be present. We prove the NP-completeness of the reachability problem for Progressing Collaborative Systems that may create fresh values.
The article analyzes the issues of legal regulation concerning liability for offences in the field of information technology (cybercrime). Author outlines the main issues of regulation in the field of information technology, examines current approaches of Russian lawyers and expressed her own proposals to resolve issues in the designated area.