56 research outputs found
Roundtrip engineering of NoSQL databases
International audienceIn this article we present a framework describing a roundtrip engineering process for NoSQLdatabase systems. This framework, based on the Model Driven Engineering approach, is composed of aknowledge base guiding the roundtrip process. Starting from a roundtrip generic scenario, we proposeseveral roundtrip scenarios combining forward and reverse engineering processes. We illustrate ourapproach with an example related to a property graph database. The illustrative scenario consists ofsuccessive steps of model enrichment combined with forward and reverse engineering processes. Futureresearch will consist in designing and implementing the main components of the knowledge base
Omejevanje dostopa pri obvladovanju API-jev
With ever growing usage of World Wide Web, number of requests to web APIs is increasing rapidly. DoS attacks and service abuses are becoming easier to execute, and more common every day. Quality of service is becoming more important as competition is rising. To build robust and reliable services, software engineers have to take this into account when designing web APIs, to deliver end users with a pleasant and reliable experience. In this thesis we delve into rate limiting in web API management to deal with those problems on scale. We propose an approach to rate limiting when request weighting is key, and cannot be estimated/calculated upfront. We show how integration of such approach into a real working system can help in achieving high stability and performance improvements, while unlocking some advanced API monetisation opportunities.Strma rast uporabe svetovnega spleta je silovito poveΔala Ε‘tevilo spletnih zahtevkov, ki jih morajo procesirati zaledni sistemi. Napadi za zavrnitev storitev in zlorabe le-teh so vse bolj pogosti in enostavni za izvedbo. Kvaliteta in zanesljivost sistemov sta kljuΔnega pomena za ohranjanje konkurenΔnosti. Naloga razvijalcev programske opreme je, da z upoΕ‘tevanjem teh zahtev naΔrtujejo robustne sisteme, ki bodo uporabnikom omogoΔili prijetno in zane-sljivo uporabniΕ‘ko izkuΕ‘njo. V tej diplomski nalogi raziΕ‘Δemo pristop omejevanja dostopa pri obvladovanju API-jev za reΕ‘evanje omenjenih problemov. Predlagamo pristop pri katerem je obteΕΎevanje spletnih zahtevkov kljuΔnega pomena in ne more biti ocenjeno/izraΔunano pred procesiranjem zahtevka. PokaΕΎemo kako lahko integracija takΕ‘nega pristopa v delujoΔ sistem obΔutno izboljΕ‘a stabilnost in uΔinkovitost storitev ter odpre moΕΎnosti za nove naΔine trΕΎenja API-jev
SoK: Cryptographically Protected Database Search
Protected database search systems cryptographically isolate the roles of
reading from, writing to, and administering the database. This separation
limits unnecessary administrator access and protects data in the case of system
breaches. Since protected search was introduced in 2000, the area has grown
rapidly; systems are offered by academia, start-ups, and established companies.
However, there is no best protected search system or set of techniques.
Design of such systems is a balancing act between security, functionality,
performance, and usability. This challenge is made more difficult by ongoing
database specialization, as some users will want the functionality of SQL,
NoSQL, or NewSQL databases. This database evolution will continue, and the
protected search community should be able to quickly provide functionality
consistent with newly invented databases.
At the same time, the community must accurately and clearly characterize the
tradeoffs between different approaches. To address these challenges, we provide
the following contributions:
1) An identification of the important primitive operations across database
paradigms. We find there are a small number of base operations that can be used
and combined to support a large number of database paradigms.
2) An evaluation of the current state of protected search systems in
implementing these base operations. This evaluation describes the main
approaches and tradeoffs for each base operation. Furthermore, it puts
protected search in the context of unprotected search, identifying key gaps in
functionality.
3) An analysis of attacks against protected search for different base
queries.
4) A roadmap and tools for transforming a protected search system into a
protected database, including an open-source performance evaluation platform
and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac
Rate limiting in API management
With ever growing usage of World Wide Web, number of requests to web APIs is increasing rapidly. DoS attacks and service abuses are becoming easier to execute, and more common every day. Quality of service is becoming more important as competition is rising. To build robust and reliable services, software engineers have to take this into account when designing web APIs, to deliver end users with a pleasant and reliable experience. In this thesis we delve into rate limiting in web API management to deal with those problems on scale. We propose an approach to rate limiting when request weighting is key, and cannot be estimated/calculated upfront. We show how integration of such approach into a real working system can help in achieving high stability and performance improvements, while unlocking some advanced API monetisation opportunities
Rate limiting in API management
With ever growing usage of World Wide Web, number of requests to web APIs is increasing rapidly. DoS attacks and service abuses are becoming easier to execute, and more common every day. Quality of service is becoming more important as competition is rising. To build robust and reliable services, software engineers have to take this into account when designing web APIs, to deliver end users with a pleasant and reliable experience. In this thesis we delve into rate limiting in web API management to deal with those problems on scale. We propose an approach to rate limiting when request weighting is key, and cannot be estimated/calculated upfront. We show how integration of such approach into a real working system can help in achieving high stability and performance improvements, while unlocking some advanced API monetisation opportunities
From BPMN Models to Labelled Property Graphs
There\u27s a growing interest in leveraging the structured and formal nature of business process modeling languages in order to make them available not only for human analysis but also to machine-readable knowledge representation. Standard serializations of the past were predominantly XML based, with some of them seemingly discontinued, e.g., XPDL after the dissolution of the Workflow Management Coalition. Recent research has been investigating the interplay between knowledge representation and business process modeling, with the focus typically placed on standards such as RDF and OWL. In this paper we introduce a converter that translates the standards-compliant BPMN XML format to Neo4J labelled property graphs (LPG) thus providing an alternative to both traditional XML-based serialization and to more recent experimental RDF solutions, while ensuring conceptual alignment with the standard serialization of BPMN 2.0. A demonstrator was built to highlight the benefits of having such a parser and the completeness of coverage for BPMN models. The proposal facilitates graph-based processing of business process models in a knowledge intensive context, where procedural knowledge available as BPMN diagrams must be exposed to machines and LPG-driven applications
ΠΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠ΅ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ ΡΡ Π΅ΠΌ
The problem of extracting semantic information from an electronic document specified in the vector graphics format and containing a graphic model (diagram) built using a graphic editor is considered. The problem is to program retrieving certain structural properties and parametric circuit and entering them into a database for later use. Based on the analysis of the capabilities of graphic editors, a conclusion has made about the relevance of this task for universal editors that are not tied to specific graphic notations and use open graphic document formats, which allows program processing. The proposed approach considers graphic documents at three levels of abstraction: conceptual (semantic properties of a schema), logical (presentation of semantic properties at the internal level of the document) and physical (internal organization of a graphic document). The solution to the problem is based on the construction of a conceptual-logical mapping, i.e., mapping a conceptual model of a circuit to a logical model of a graphic document, according to its physical model. Within the framework of the approach, an algorithm for constructing the indicated mapping is developed, presented in the form of an object-oriented pseudocode. The study of internal markup in open graphic formats made it possible to build models for identifying circuit elements and their connections to each other, which is necessary for a specific application of the algorithm. Expressions for addressing schema elements and accessing their properties are obtained. The proposed approach is implemented on the base of a situation-oriented paradigm, within which the extraction process is driven by a hierarchical situational model. The processed data is specified in the situational model in the form of virtual documents displayed on heterogeneous external data sources. For the problem being solved, we consider the mapping to two variants of vector graphics formats: to a "flat" markup file and to a set of such files in an electronic archive. The practical use of the results is illustrated by the example of extracting semantic information from graphical models developed at various stages of database design.Π Π°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π·Π°Π΄Π°ΡΠ° ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠ³ΠΎ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°, Π·Π°Π΄Π°Π½Π½ΠΎΠ³ΠΎ Π² ΡΠΎΡΠΌΠ°ΡΠ΅ Π²Π΅ΠΊΡΠΎΡΠ½ΠΎΠΉ Π³ΡΠ°ΡΠΈΠΊΠΈ ΠΈ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π³ΠΎ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ (ΡΡ
Π΅ΠΌΡ), ΠΏΠΎΡΡΡΠΎΠ΅Π½Π½ΡΡ Ρ ΠΏΠΎΠΌΠΎΡΡΡ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ΅Π΄Π°ΠΊΡΠΎΡΠ°. ΠΠ°Π΄Π°ΡΠ° ΡΠΎΡΡΠΎΠΈΡ Π² ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠΌ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ
ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² ΡΡ
Π΅ΠΌΡ ΠΈ Π·Π°Π½Π΅ΡΠ΅Π½ΠΈΠΈ ΠΈΡ
Π² Π±Π°Π·Ρ Π΄Π°Π½Π½ΡΡ
Π΄Π»Ρ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅Π³ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ΅Π΄Π°ΠΊΡΠΎΡΠΎΠ² ΡΠ΄Π΅Π»Π°Π½ Π²ΡΠ²ΠΎΠ΄ ΠΎΠ± Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΠΈ ΡΡΠΎΠΉ Π·Π°Π΄Π°ΡΠΈ Π΄Π»Ρ ΡΠ½ΠΈΠ²Π΅ΡΡΠ°Π»ΡΠ½ΡΡ
ΡΠ΅Π΄Π°ΠΊΡΠΎΡΠΎΠ², Π½Π΅ ΠΏΡΠΈΠ²ΡΠ·Π°Π½Π½ΡΡ
ΠΊ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΡΠΌ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌ Π½ΠΎΡΠ°ΡΠΈΡΠΌ ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡΡΠΈΡ
ΠΎΡΠΊΡΡΡΡΠ΅ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠΎΡΠΌΠ°ΡΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΎΠ², ΡΡΠΎ Π΄ΠΎΠΏΡΡΠΊΠ°Π΅Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΡ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΡ. ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅Ρ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΡ Π½Π° ΡΡΡΡ
ΡΡΠΎΠ²Π½ΡΡ
Π°Π±ΡΡΡΠ°ΠΊΡΠΈΠΈ: ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎΠΌ (ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΡΡ
Π΅ΠΌΡ), Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΌ (ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² Π½Π° Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΌ ΡΡΠΎΠ²Π½Π΅ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°) ΠΈ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΎΠΌ (Π²Π½ΡΡΡΠ΅Π½Π½ΡΡ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°). Π Π΅ΡΠ΅Π½ΠΈΠ΅ Π·Π°Π΄Π°ΡΠΈ ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΎ Π½Π° ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠΈ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎ-Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ, ΡΠΎ Π΅ΡΡΡ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΡ
Π΅ΠΌΡ Π² Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ° Ρ ΡΡΠ΅ΡΠΎΠΌ Π΅Π³ΠΎ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ. Π ΡΠ°ΠΌΠΊΠ°Ρ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΡΠΊΠ°Π·Π°Π½Π½ΠΎΠ³ΠΎ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠΉ Π² Π²ΠΈΠ΄Π΅ ΠΎΠ±ΡΠ΅ΠΊΡΠ½ΠΎ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠ΅Π²Π΄ΠΎΠΊΠΎΠ΄Π°. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΉ ΡΠ°Π·ΠΌΠ΅ΡΠΊΠΈ Π² ΠΎΡΠΊΡΡΡΡΡ
Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΎΡΠΌΠ°ΡΠ°Ρ
ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ² ΡΡ
Π΅ΠΌΡ ΠΈ ΠΈΡ
ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΉ ΠΌΠ΅ΠΆΠ΄Ρ ΡΠΎΠ±ΠΎΠΉ, ΡΡΠΎ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ Π΄Π»Ρ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°. ΠΠΎΠ»ΡΡΠ΅Π½Ρ Π²ΡΡΠ°ΠΆΠ΅Π½ΠΈΡ Π΄Π»Ρ Π°Π΄ΡΠ΅ΡΠ°ΡΠΈΠΈ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ² ΡΡ
Π΅ΠΌΡ ΠΈ Π΄ΠΎΡΡΡΠΏΠ° ΠΊ ΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌ. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π½ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠΈΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΏΠ°ΡΠ°Π΄ΠΈΠ³ΠΌΡ, Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΏΡΠΎΡΠ΅ΡΡ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΠΏΡΠ°Π²Π»ΡΠ΅ΡΡΡ ΠΈΠ΅ΡΠ°ΡΡ
ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΡΡ. ΠΠ±ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ Π·Π°Π΄Π°ΡΡΡΡ Π² ΡΠΈΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π² Π²ΠΈΠ΄Π΅ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΎΠ², ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ°Π΅ΠΌΡΡ
Π½Π° ΡΠ°Π·Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π²Π½Π΅ΡΠ½ΠΈΠ΅ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΈ Π΄Π°Π½Π½ΡΡ
. ΠΠ»Ρ ΡΠ΅ΡΠ°Π΅ΠΌΠΎΠΉ Π·Π°Π΄Π°ΡΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠ΅ Π½Π° Π΄Π²Π° Π²Π°ΡΠΈΠ°Π½ΡΠ° ΡΠΎΡΠΌΠ°ΡΠΎΠ² Π²Π΅ΠΊΡΠΎΡΠ½ΠΎΠΉ Π³ΡΠ°ΡΠΈΠΊΠΈ: Π½Π° Β«ΠΏΠ»ΠΎΡΠΊΠΈΠΉΒ» ΡΠ°ΠΉΠ» ΡΠ°Π·ΠΌΠ΅ΡΠΊΠΈ ΠΈ Π½Π° Π½Π°Π±ΠΎΡ ΡΠ°ΠΊΠΈΡ
ΡΠ°ΠΉΠ»ΠΎΠ² Π² ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠΌ Π°ΡΡ
ΠΈΠ²Π΅. ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΈΠ»Π»ΡΡΡΡΠΈΡΡΠ΅ΡΡΡ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΡΡ
Π½Π° ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΡΠ°ΠΏΠ°Ρ
ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π±Π°Π· Π΄Π°Π½Π½ΡΡ
ΠΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠ΅ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ ΡΡ Π΅ΠΌ
Π Π°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π·Π°Π΄Π°ΡΠ° ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠ³ΠΎ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°, Π·Π°Π΄Π°Π½Π½ΠΎΠ³ΠΎ Π² ΡΠΎΡΠΌΠ°ΡΠ΅ Π²Π΅ΠΊΡΠΎΡΠ½ΠΎΠΉ Π³ΡΠ°ΡΠΈΠΊΠΈ ΠΈ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π³ΠΎ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ (ΡΡ
Π΅ΠΌΡ), ΠΏΠΎΡΡΡΠΎΠ΅Π½Π½ΡΡ Ρ ΠΏΠΎΠΌΠΎΡΡΡ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ΅Π΄Π°ΠΊΡΠΎΡΠ°. ΠΠ°Π΄Π°ΡΠ° ΡΠΎΡΡΠΎΠΈΡ Π²Β ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠΌ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ
ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² ΡΡ
Π΅ΠΌΡ ΠΈ Π·Π°Π½Π΅ΡΠ΅Π½ΠΈΠΈ ΠΈΡ
Π² Π±Π°Π·Ρ Π΄Π°Π½Π½ΡΡ
Π΄Π»Ρ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅Π³ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ΅Π΄Π°ΠΊΡΠΎΡΠΎΠ² ΡΠ΄Π΅Π»Π°Π½ Π²ΡΠ²ΠΎΠ΄ ΠΎΠ± Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΠΈ ΡΡΠΎΠΉ Π·Π°Π΄Π°ΡΠΈ Π΄Π»Ρ ΡΠ½ΠΈΠ²Π΅ΡΡΠ°Π»ΡΠ½ΡΡ
ΡΠ΅Π΄Π°ΠΊΡΠΎΡΠΎΠ², Π½Π΅ ΠΏΡΠΈΠ²ΡΠ·Π°Π½Π½ΡΡ
ΠΊ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΡΠΌ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌ Π½ΠΎΡΠ°ΡΠΈΡΠΌ ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡΡΠΈΡ
ΠΎΡΠΊΡΡΡΡΠ΅ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠΎΡΠΌΠ°ΡΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΎΠ², ΡΡΠΎ Π΄ΠΎΠΏΡΡΠΊΠ°Π΅Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΡ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΡ. ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅Ρ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΡ Π½Π° ΡΡΡΡ
ΡΡΠΎΠ²Π½ΡΡ
Π°Π±ΡΡΡΠ°ΠΊΡΠΈΠΈ: ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎΠΌ (ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΡΡ
Π΅ΠΌΡ), Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΌ (ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² Π½Π° Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΌ ΡΡΠΎΠ²Π½Π΅ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°) ΠΈ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΎΠΌ (Π²Π½ΡΡΡΠ΅Π½Π½ΡΡ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°). Π Π΅ΡΠ΅Π½ΠΈΠ΅ Π·Π°Π΄Π°ΡΠΈ ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΎ Π½Π°Β ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠΈ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎ-Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ, ΡΠΎ Π΅ΡΡΡ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΡ
Π΅ΠΌΡ Π² Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ° Ρ ΡΡΠ΅ΡΠΎΠΌ Π΅Π³ΠΎ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ. Π ΡΠ°ΠΌΠΊΠ°Ρ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΡΠΊΠ°Π·Π°Π½Π½ΠΎΠ³ΠΎ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠΉ Π² Π²ΠΈΠ΄Π΅ ΠΎΠ±ΡΠ΅ΠΊΡΠ½ΠΎ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠ΅Π²Π΄ΠΎΠΊΠΎΠ΄Π°. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΉ ΡΠ°Π·ΠΌΠ΅ΡΠΊΠΈ Π² ΠΎΡΠΊΡΡΡΡΡ
Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΎΡΠΌΠ°ΡΠ°Ρ
ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ² ΡΡ
Π΅ΠΌΡ ΠΈ ΠΈΡ
ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΉ ΠΌΠ΅ΠΆΠ΄Ρ ΡΠΎΠ±ΠΎΠΉ, ΡΡΠΎ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ Π΄Π»Ρ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°. ΠΠΎΠ»ΡΡΠ΅Π½Ρ Π²ΡΡΠ°ΠΆΠ΅Π½ΠΈΡ Π΄Π»Ρ Π°Π΄ΡΠ΅ΡΠ°ΡΠΈΠΈ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ² ΡΡ
Π΅ΠΌΡ ΠΈ Π΄ΠΎΡΡΡΠΏΠ° ΠΊ ΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌ. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π½ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠΈΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΏΠ°ΡΠ°Π΄ΠΈΠ³ΠΌΡ, Π²Β ΡΠ°ΠΌΠΊΠ°Ρ
ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΏΡΠΎΡΠ΅ΡΡ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΠΏΡΠ°Π²Π»ΡΠ΅ΡΡΡ ΠΈΠ΅ΡΠ°ΡΡ
ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΡΡ. ΠΠ±ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ Π·Π°Π΄Π°ΡΡΡΡ Π² ΡΠΈΡΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π² Π²ΠΈΠ΄Π΅ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΎΠ², ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ°Π΅ΠΌΡΡ
Π½Π° ΡΠ°Π·Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π²Π½Π΅ΡΠ½ΠΈΠ΅ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΈ Π΄Π°Π½Π½ΡΡ
. ΠΠ»ΡΒ ΡΠ΅ΡΠ°Π΅ΠΌΠΎΠΉ Π·Π°Π΄Π°ΡΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠ΅ Π½Π° Π΄Π²Π° Π²Π°ΡΠΈΠ°Π½ΡΠ° ΡΠΎΡΠΌΠ°ΡΠΎΠ² Π²Π΅ΠΊΡΠΎΡΠ½ΠΎΠΉ Π³ΡΠ°ΡΠΈΠΊΠΈ: Π½Π° Β«ΠΏΠ»ΠΎΡΠΊΠΈΠΉΒ» ΡΠ°ΠΉΠ» ΡΠ°Π·ΠΌΠ΅ΡΠΊΠΈ ΠΈ Π½Π° Π½Π°Π±ΠΎΡ ΡΠ°ΠΊΠΈΡ
ΡΠ°ΠΉΠ»ΠΎΠ² Π² ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠΌ Π°ΡΡ
ΠΈΠ²Π΅. ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΈΠ»Π»ΡΡΡΡΠΈΡΡΠ΅ΡΡΡ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΡΡ
Π½Π° ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΡΠ°ΠΏΠ°Ρ
ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π±Π°Π· Π΄Π°Π½Π½ΡΡ
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