203 research outputs found
Intensional Semantics for Syllogistics: what Leibniz and Vasiliev Have in Common
This article deals with an alternative interpretation of syllogistics, different from the classical (extensional) one: an intensional one, in which subject and predicate are not associated with a set of individuals (the extension of the concept) but a set of attributes (the content of the concept). The authors of the paper draw attention to the fact that this approach was first proposed by Leibniz in works on logical calculus, which for a long time remained in the shadow of his other philosophical works. Currently, the intensional approach is gaining more and more popularity due to the development of non-classical logics, and the article will present several existing intensional formal syllogistic semantics.
The paper will also consider another historical approach to syllogistics, associated with the name of the Russian logician Nikolai Vasiliev, who is not only one of the founders of non-classical (non-Aristotelian logic) but also of a different intensional interpretation of such logic. The authors, along with the already known formalizations of Vasilievβs ideas, present two new systems. One of them is a reconstruction of one type of imaginary logic with statements of three qualities: affirmative and two types of negative statements (with absolute and ordinary negation). The second system is the one that is adequate to semantics, in which instead of the four classical ones, only three types of statements are presented (two particular statements are replaced by one - accidental), and their significance is determined through the relation of the classical logical entailment. Both of them are interpreted intensionally.
The intensional approach in logic and, in particular, in syllogistics allows us to expand the class of accepted principles (which occurs due to the expansion of the class of correct moods of syllogisms)
Prospects of development of remote education in Russia on the example of the Universarium
This article considers the prospects for the development of distance learning in Russia on the example of the UniversariumΠ Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Ρ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π΄ΠΈΡΡΠ°Π½ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π² Π ΠΎΡΡΠΈΠΈ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ ΠΏΡΠΎΠ΅ΠΊΡΠ° Π£Π½ΠΈΠ²Π΅ΡΡΠ°ΡΠΈΡ
The value of tourist destinations in the management of regional development
Ericssonβs Region IPR & Licensing (RIPL) receives about 3000 thousands Invention Disclosures (IvDs) every year submitted by researchers as a result of their R&D activities. To decide whether an IvD has a good business value and a patent application should be filed; a rigorous evaluation process is carried out by a selected Patent Attorney (PA). One of most important elements of the evaluation process is to find prior art similar, including similar IvDs that have been evaluated before. These documents are not public and therefore canβt be searched using available search tools. For now the process of finding prior art is done manually (without the help of any search tools) and takes up significant amount of time. The aim of this Masterβs thesis is to develop and test an information retrieval search engine as a proof of concept to find similar Invention Disclosure documents and related patent applications. For this purpose, a SOLR database server is setup with up to seven thousand five hundred (7500) IvDs indexed. A similarity algorithm is implemented which is customized to weight different fields. LUCENE is then used to query the server and display the relevant documents in a web application
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Analysing Creative Image Search Information Needs
Creative professionals in advertising, marketing, design and journalism search for images to visually represent a concept for their project. The main purpose of this paper is to present search facets derived from an analysis of documents known as briefs, which are widely used in creative industries as requirement documents describing information needs. The briefs specify the type of image required, such as the content and context of use for the image and represent the topic from which the searcher builds an image query. We take three main sourcesβuser image search behaviour, briefs, and image search engine search facets to examine the search facets for image searching in order to examine the following research questionβare search facet schemes for image search engines sufficient for user needs, or is revision needed? We found that there are three main classes of user search facet, which include business, contextual and image related information. The key argument in the paper is that the facet βkeyword/tagβ is ambiguous and does not support user needs for more generic descriptions to broaden search or specific descriptions to narrow their search β we suggest that a more detailed search facet scheme would be appropriate
ΠΠ½ΠΎΠΌΠ°Π»ΡΠ½ΡΠΉ ΡΠΎΡΡ Π·Π΅ΡΠ΅Π½ Π² ΠΊΡΠΈΠΎΠ³Π΅Π½Π½ΠΎ-Π΄Π΅ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΌΠ΅Π΄ΠΈ
Structural changes in cryogenically deformed copper during long-term (up to two years) room-temperature ageing were investigated. It is found that the structure formed under high (e=8.2) cryogenic deformation is unstable and is characterized by abnormalous grain growth. It is shown that the grain growth is preceded by a long (up to a year) incubation period. It is revealed that the structure rapidly losses stability with an increase in accumulated cryogenic strain
ΠΡΠΈΠΎΠ³Π΅Π½Π½Π°Ρ Π΄Π΅ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΌΠ΅Π΄ΠΈ
The effect of cryogenic deformation on the structure refinement of copper was studied
Analysing creative image search information needs.
Creative professionals in advertising, marketing, design and journalism search for images to visually represent a concept for their project. The main purpose of this paper is to present an analysis of documents known as briefs to find search facets, which are widely used in creative industries as a requirements document to describe an information need. The briefs specify the type of image required, such as the content and context of use for the image, and represent the topic from which the searcher builds an image query. This research takes three main sources - user image search behaviour, briefs, search engine meta-data - to examine the search facets for image searching in order to examine the following research question - are meta-data schemes for image search engines sufficient for user needs, or is revision needed? This research found that there are three main classes of user search facet, which include business, contextual and image related information. The key argument in the paper is that the facet 'keyword/tag' is ambiguous and does not support user needs for more generic descriptions to broaden search or specific descriptions to narrow their search - we suggest that a more detailed search facet scheme would be appropriate
Π€ΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠΈΠΊΡΠΎΡΡΡΡΠΊΡΡΡΡ Π² Ρ ΠΎΠ΄Π΅ ΠΊΡΠΈΠΎΠ³Π΅Π½Π½ΠΎΠΉ ΠΏΡΠΎΠΊΠ°ΡΠΊΠΈ ΠΌΠ΅Π΄ΠΈ
ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΡΡΠ°ΡΠ΅Π»ΡΠ½Π°Ρ Π°ΡΡΠ΅ΡΡΠ°ΡΠΈΡ ΠΌΠΈΠΊΡΠΎΡΡΡΡΠΊΡΡΡΡ ΠΈ ΠΌΠ΅Ρ
Π°Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΠΎΠΉΡΡΠ² ΠΌΠ΅Π΄ΠΈ, ΠΏΠΎΠ΄Π²Π΅ΡΠ³Π½ΡΡΠΎΠΉ ΡΠ°Π·Π»ΠΈΡΠ½ΠΎΠΉ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΠΊΡΠΈΠΎΠ³Π΅Π½Π½ΠΎΠΉ ΠΏΡΠΎΠΊΠ°ΡΠΊΠΈ. ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ, ΡΡΠΎ ΡΠ²ΠΎΠ»ΡΡΠΈΡ Π·Π΅ΡΠ΅Π½Π½ΠΎΠΉ ΡΡΡΡΠΊΡΡΡΡ, Π² ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠΌ, ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»Π°ΡΡ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΡΡΠ΅ΠΊΡΠΎΠΌ Π΄Π΅ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠ΅ΠΊΡΡΡΡΠ½ΡΡ
Π΄Π°Π½Π½ΡΡ
Π±ΡΠ» ΡΠ΄Π΅Π»Π°Π½ Π²ΡΠ²ΠΎΠ΄, ΡΡΠΎ ΠΊΡΠΈΠΎΠ³Π΅Π½Π½ΡΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ Π΄Π΅ΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π½Π΅ ΠΏΡΠΈΠ²Π΅Π»ΠΈ ΠΊ ΡΡΠ½Π΄Π°ΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΠΎΠΌΡ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ° ΠΏΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ, ΠΈ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠΎΠΌ Π΄Π΅ΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π±ΡΠ»ΠΎ Π΄ΠΈΡΠ»ΠΎΠΊΠ°ΡΠΈΠΎΠ½Π½ΠΎΠ΅ {111} ΡΠΊΠΎΠ»ΡΠΆΠ΅Π½ΠΈΠ΅. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΊΡΠΈΠΎΠ³Π΅Π½Π½Π°Ρ ΠΏΡΠΎΠΊΠ°ΡΠΊΠ° ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΌΡ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΡ ΠΏΡΠΎΡΠ½ΠΎΡΡΠΈ ΠΈ Π½Π΅ΠΊΠΎΡΠΎΡΠΎΠΌΡ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠ»Π°ΡΡΠΈΡΠ½ΠΎΡΡΠΈ
ΠΠ»ΠΈΡΠ½ΠΈΠ΅ ΠΊΡΠΈΠΎΠ³Π΅Π½Π½ΠΎΠΉ ΠΎΡΠ°Π΄ΠΊΠΈ Π½Π° ΠΌΠΈΠΊΡΠΎΡΡΡΡΠΊΡΡΡΡ ΠΊΠ°ΡΠ°Π½ΠΎΠΉ ΠΌΠ΅Π»ΠΊΠΎΠ·Π΅ΡΠ½ΠΈΡΡΠΎΠΉ ΠΌΠ΅Π΄ΠΈ
ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΈΠ·ΠΌΠ΅Π»ΡΡΠ΅Π½ΠΈΡ Π·Π΅ΡΠ΅Π½ Π² ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈ ΡΠΈΡΡΠΎΠΉ ΠΌΠ΅Π΄ΠΈ ΠΏΡΡΠ΅ΠΌ ΠΊΡΠΈΠΎΠ³Π΅Π½Π½ΠΎΠΉ ΠΎΡΠ°Π΄ΠΊΠΈ. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠ²ΠΎΠ»ΡΡΠΈΡ ΡΡΡΡΠΊΡΡΡΡ Π² ΡΠ΅Π»ΠΎΠΌ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»Π°ΡΡ ΡΠΏΠ»ΡΡΠΈΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΈΡΡ
ΠΎΠ΄Π½ΡΡ
Π·Π΅ΡΠ΅Π½ Π² Ρ
ΠΎΠ΄Π΅ Π΄Π΅ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. ΠΠ½Π°Π»ΠΈΠ· ΡΠ΅ΠΊΡΡΡΡΠ½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΠΈ ΡΠΏΠ΅ΠΊΡΡΠ° ΡΠ°Π·ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²ΠΎΠΊ ΠΏΠΎΠΊΠ°Π·Π°Π», ΡΡΠΎ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠΎΠΌ ΠΏΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΡΠ²Π»ΡΠ»ΠΎΡΡ ΠΎΠ±ΡΡΠ½ΠΎΠ΅ {111} Π΄ΠΈΡΠ»ΠΎΠΊΠ°ΡΠΈΠΎΠ½Π½ΠΎΠ΅ ΡΠΊΠΎΠ»ΡΠΆΠ΅Π½ΠΈΠ΅ ΠΏΡΠΈ Π½Π΅ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΌ Π²ΠΊΠ»Π°Π΄Π΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π΄Π²ΠΎΠΉΠ½ΠΈΠΊΠΎΠ²Π°Π½ΠΈΡ
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