309 research outputs found
Ways for reducing mortality from cardiovascular diseases: A review
Ways for reducing mortality from cardiovascular diseases The article analyzes the possible ways to further reduce cardiovascular disease mortality in the Russian Federation by eliminating shortcomings and pitfalls, introducing known but not used opportunities, and new organizational and medical technologies based on the accumulated experience of "best practice"
ΠΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΌΡΠ»ΡΡΠΈΠΊΠ»ΠΈΠ΅Π½ΡΡΠΊΠΎΠ³ΠΎ ΠΊΠ»Π°ΡΡΠ΅ΡΠ° Π±Π°Π· Π΄Π°Π½Π½ΡΡ
One of the main trends of recent years in software design is a shift to a Software as a Service (SaaS) paradigm which brings a number of advantages for both software developers and end users. However, along with these benefits this transition brings new architectural challenges. One of such challenges is the implementation of a data storage that would meet the needs of a service-provider, at the same time providing a fairly simple application programming interface for software developers. In order to develop effective solutions in this area, the architectural features of cloud-based applications should be taken into account. Among others, such key features are the need for scalability and quick adaptation to changing conditions. This paper provides a brief analysis of the problems in the field of cloud data storage systems based on the relational model and it proposes the concept of database cluster designed for applications with a multi-tenant architecture. Besides, the article describes a simulation model of such a cluster, as well as the main stages of its development and the main principles forming its foundation.ΠΠ΄Π½ΠΎΠΉ ΠΈΠ· Π³Π»Π°Π²Π½ΡΡ
ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΉ ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΡ
Π»Π΅Ρ Π² ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ ΡΡΠ°Π» ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄ ΠΊ ΠΏΠ°ΡΠ°Π΄ΠΈΠ³ΠΌΠ΅ Software as a Service (SaaS), ΠΊΠΎΡΠΎΡΠ°Ρ Π½Π΅ΡΠ΅Ρ ΡΡΠ΄ Π½Π΅ΠΎΡΠΏΠΎΡΠΈΠΌΡΡ
ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ² ΠΊΠ°ΠΊ Π΄Π»Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ-ΡΠ°Π·ΡΠ°Π±ΠΎΡΡΠΈΠΊΠΎΠ² ΠΠ, ΡΠ°ΠΊ ΠΈ Π΄Π»Ρ ΠΊΠΎΠ½Π΅ΡΠ½ΡΡ
ΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΠ΅Π»Π΅ΠΉ. ΠΠ΄Π½Π°ΠΊΠΎ Π²ΠΌΠ΅ΡΡΠ΅ Ρ ΡΡΠΈΠΌΠΈ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π°ΠΌΠΈ Π΄Π°Π½Π½ΡΠΉ ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄ Π½Π΅ΡΠ΅Ρ ΠΈ Π½ΠΎΠ²ΡΠ΅ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ½ΡΠ΅ Π²ΡΠ·ΠΎΠ²Ρ, ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· ΠΊΠΎΡΠΎΡΡΡ
ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡ Ρ
ΡΠ°Π½ΠΈΠ»ΠΈΡΠ° Π΄Π°Π½Π½ΡΡ
, ΠΊΠΎΡΠΎΡΠΎΠ΅ ΠΌΠΎΠ³Π»ΠΎ Π±Ρ ΡΠ΄ΠΎΠ²Π»Π΅ΡΠ²ΠΎΡΠΈΡΡ Π½ΡΠΆΠ΄Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΈ-ΠΏΡΠΎΠ²Π°ΠΉΠ΄Π΅ΡΠ° ΡΡΠ»ΡΠ³, ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ² Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎ ΠΏΡΠΎΡΡΠΎΠΉ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡ Π΄Π»Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΡΠΈΠΊΠΎΠ². ΠΠ»Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π² Π΄Π°Π½Π½ΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΡΠ»Π΅Π΄ΡΠ΅Ρ ΠΏΡΠΈΠ½ΠΈΠΌΠ°ΡΡ Π²ΠΎ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΠΎΠ±Π»Π°ΡΠ½ΡΡ
ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ, ΠΊΠ»ΡΡΠ΅Π²ΡΠΌΠΈ ΠΈΠ· ΠΊΠΎΡΠΎΡΡΡ
ΡΠ²Π»ΡΡΡΡΡ ΠΏΠΎΡΡΠ΅Π±Π½ΠΎΡΡΡ Π² ΠΏΡΠΎΡΡΠΎΠΌ ΠΌΠ°ΡΡΡΠ°Π±ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΈ Π±ΡΡΡΡΠΎΠΉ Π°Π΄Π°ΠΏΡΠ°ΡΠΈΠΈ ΠΊ ΠΌΠ΅Π½ΡΡΡΠΈΠΌΡΡ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌ. Π Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΡΡΡ ΠΊΡΠ°ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΡ
ΠΏΡΠΎΠ±Π»Π΅ΠΌ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΈ ΠΎΠ±Π»Π°ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ Ρ
ΡΠ°Π½Π΅Π½ΠΈΡ Π΄Π°Π½Π½ΡΡ
, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΡ
Π½Π° ΡΠ΅Π»ΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΡΠ΅Π΄Π»Π°Π³Π°Π΅ΡΡΡ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ ΠΊΠ»Π°ΡΡΠ΅ΡΠ° Π Π‘Π£ΠΠ, ΠΏΡΠ΅Π΄Π½Π°Π·Π½Π°ΡΠ΅Π½Π½ΠΎΠ³ΠΎ Π΄Π»Ρ ΠΎΠ±ΡΠ»ΡΠΆΠΈΠ²Π°Π½ΠΈΡ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ Ρ ΠΌΡΠ»ΡΡΠΈΠΊΠ»ΠΈΠ΅Π½ΡΡΠΊΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠΎΠΉ. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π² ΡΡΠ°ΡΡΠ΅ Π΄Π°Π΅ΡΡΡ ΠΎΠΏΠΈΡΠ°Π½ΠΈΠ΅ ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎΠ΄ΠΎΠ±Π½ΠΎΠ³ΠΎ ΠΊΠ»Π°ΡΡΠ΅ΡΠ°, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΡΠ°ΠΏΠΎΠ² Π΅Π΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΎΠ², Π·Π°Π»ΠΎΠΆΠ΅Π½Π½ΡΡ
Π² Π΅Π΅ ΠΎΡΠ½ΠΎΠ²Ρ
ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΡΠΎΡ Π°ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΌΠ΅ΡΠ°ΡΠ²ΡΠΈΡΡΠΈΠΊ Π² Π·Π°Π΄Π°ΡΠ΅ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ Π΄Π°Π½Π½ΡΠΌΠΈ Π² ΠΌΡΠ»ΡΡΠΈΠΊΠ»ΠΈΠ΅Π½ΡΡΠΊΠΎΠΌ ΠΊΠ»Π°ΡΡΠ΅ΡΠ΅ Π±Π°Π· Π΄Π°Π½Π½ΡΡ
A multi-tenant database cluster is a concept of a data-storage subsystem for cloud applications with the multi-tenant architecture. The cluster is a set of relational database servers with the single entry point, combined into one unit with a cluster controller. This system is aimed to be used by applications developed according to Software as a Service (SaaS) paradigm and allows to place tenants at database servers so that providing their isolation, data backup and the most effective usage of available computational power. One of the most important problems about such a system is an effective distribution of data into servers, which affects the degree of individual cluster nodes load and faulttolerance. This paper considers the data-management approach, based on the usage of a load-balancing quality measure function. This function is used during initial placement of new tenants and also during placement optimization steps. Standard schemes of metaheuristic optimization such as simulated annealing and tabu search are used to find a better tenant placement.ΠΡΠ»ΡΡΠΈΠΊΠ»ΠΈΠ΅Π½ΡΡΠΊΠΈΠΉ ΠΊΠ»Π°ΡΡΠ΅Ρ Π±Π°Π· Π΄Π°Π½Π½ΡΡ
β ΡΡΠΎ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ Ρ
ΡΠ°Π½ΠΈΠ»ΠΈΡΠ° Π΄Π°Π½Π½ΡΡ
Π΄Π»Ρ ΠΎΠ±Π»Π°ΡΠ½ΡΡ
ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ Ρ ΠΌΡΠ»ΡΡΠΈΠΊΠ»ΠΈΠ΅Π½ΡΡΠΊΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠΎΠΉ. ΠΠ»Π°ΡΡΠ΅Ρ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅Ρ ΡΠΎΠ±ΠΎΠΉ Π½Π°Π±ΠΎΡ ΡΠ΅ΡΠ²Π΅ΡΠΎΠ² ΡΠ΅Π»ΡΡΠΈΠΎΠ½Π½ΡΡ
Π±Π°Π· Π΄Π°Π½Π½ΡΡ
Ρ Π΅Π΄ΠΈΠ½ΠΎΠΉ ΡΠΎΡΠΊΠΎΠΉ Π²Ρ
ΠΎΠ΄Π°, ΠΎΠ±ΡΠ΅Π΄ΠΈΠ½Π΅Π½Π½ΡΡ
Π² ΠΎΠ΄Π½ΠΎ ΡΠ΅Π»ΠΎΠ΅ ΠΈ ΡΠ°Π±ΠΎΡΠ°ΡΡΠΈΡ
ΠΏΠΎΠ΄ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ΠΌ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΠΊΠ»Π°ΡΡΠ΅ΡΠ°. ΠΠ°Π½Π½Π°Ρ ΡΠΈΡΡΠ΅ΠΌΠ° Π½Π°ΡΠ΅Π»Π΅Π½Π° Π½Π° ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡΠΌΠΈ, ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΡΠΌΠΈ Π² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΠΏΠ°ΡΠ°Π΄ΠΈΠ³ΠΌΠΎΠΉ Software as a Service (SaaS), ΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΠ°Π·ΠΌΠ΅ΡΡΠΈΡΡ Π½Π° ΠΏΡΠ΅Π΄ΠΎΡΡΠ°Π²Π»Π΅Π½Π½ΡΡ
ΡΠ΅ΡΠ²Π΅ΡΠ°Ρ
Π΄Π°Π½Π½ΡΠ΅ Π±ΠΎΠ»ΡΡΠΎΠ³ΠΎ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π° ΠΊΠ»ΠΈΠ΅Π½ΡΠΎΠ² ΡΠ°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, ΡΡΠΎΠ±Ρ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΡΡ ΠΈΡ
ΠΈΠ·ΠΎΠ»ΡΡΠΈΡ, ΡΠ΅Π·Π΅ΡΠ²ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄ΠΎΡΡΠ°Π²Π»Π΅Π½Π½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΌΠΎΡΠ½ΠΎΡΡΠ΅ΠΉ. ΠΠ΄Π½ΠΎΠΉ ΠΈΠ· Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²Π°ΠΆΠ½ΡΡ
Π·Π°Π΄Π°Ρ ΠΏΡΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠΎΠ΄ΠΎΠ±Π½ΠΎΠ³ΠΎ ΡΠΎΠ΄Π° ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π΄Π°Π½Π½ΡΡ
ΠΏΠΎ ΡΠ΅ΡΠ²Π΅ΡΠ°ΠΌ, ΠΊΠΎΡΠΎΡΠΎΠ΅ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅Ρ ΡΡΠ΅ΠΏΠ΅Π½Ρ Π·Π°Π³ΡΡΠΆΠ΅Π½Π½ΠΎΡΡΠΈ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΡΠ·Π»ΠΎΠ², Π° ΡΠ°ΠΊΠΆΠ΅ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡ ΡΠΈΡΡΠ΅ΠΌΡ ΠΊ ΡΠ±ΠΎΡΠΌ. Π ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΊ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ Π΄Π°Π½Π½ΡΠΌΠΈ, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π° ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΡΡΠ½ΠΊΡΠΈΠΈ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π±Π°Π»Π°Π½ΡΠΈΡΠΎΠ²ΠΊΠΈ Π½Π°Π³ΡΡΠ·ΠΊΠΈ. ΠΠ°Π½Π½Π°Ρ ΡΡΠ½ΠΊΡΠΈΡ ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΡΡΡ ΠΊΠ°ΠΊ ΠΏΡΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΠ°Π·ΠΌΠ΅ΡΠ΅Π½ΠΈΠΈ ΠΊΠ»ΠΈΠ΅Π½ΡΠΎΠ², ΡΠ°ΠΊ ΠΈ Π΄Π»Ρ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΆΠ΅ ΠΈΠΌΠ΅ΡΡΠ΅Π³ΠΎΡΡ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΊΠ»ΠΈΠ΅Π½ΡΠΎΠ². ΠΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡ ΡΠ°Π·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ Π²Π΅Π΄Π΅ΡΡΡ ΠΏΠΎ ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠΌ ΡΡ
Π΅ΠΌΠ°ΠΌ ΡΡΠΎΡ
Π°ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠ°ΡΠ²ΡΠΈΡΡΠΈΠΊ: ΠΈΠΌΠΈΡΠ°ΡΠΈΠΈ ΠΎΡΠΆΠΈΠ³Π° (simulated annealing) ΠΈ ΠΏΠΎΠΈΡΠΊΠ° Ρ Π·Π°ΠΏΡΠ΅ΡΠ°ΠΌΠΈ (tabu search)
Possibilities of dispensary observation in reducing mortality from coronary heart disease
Dispensary observation of patients with coronary artery disease can significantly reduce the likelihood of cardiovascular complications onset. Active outpatient monitoring allows to correct the main risk factors for cardiovascular complications, to estimate the risk of unfavorable cardiovascular events onset and to identificate patients who will get benefit of coronary revascularization. The introduction of a comprehensive assessment of cardiovascular risk and the development of remote monitoring technologies will improve the long-term results of outpatient follow-up of patients with coronary artery disease at high cardiovascular risk
Enriching a Situation Awareness Framework for IoT with Knowledge Base and Reasoning Components
Theimportanceofsystem-levelcontext-andsituationaware- ness increases with the growth of the Internet of Things (IoT). This paper proposes an integrated approach to situation awareness by providing a semantically rich situation model together with reliable situation infer- ence based on Context Spaces Theory (CST) and Situation Theory (ST). The paper discusses benefits of integrating the proposed situation aware- ness framework with knowledge base and efficient reasoning techniques taking into account uncertainty and incomplete knowledge about situa- tions. The paper discusses advantages and impact of proposed context adaptation in dynamic IoT environments. Practical issues of two-way mapping between IoT messaging standards and CST are also discussed
Prospects for development of initiative budgeting in mobilization economy
In modern Russia, the initiative budgeting mechanism has been developing systematically since 2015. The practice has been launched in 51 out of 85 constituent entities of the Russian Federation. This phenomenon is an urgent topic for research, in connection with its priority for the state as one of the important directions for the openness of the budget system development and degree of citizensβ satisfaction with the results of the budget policy improvement. The purpose of this study is to analyze the possibilities of the initiative budgeting practice development in the mobilization economy, which, apparently, for a certain time will become the main model of economic development in Russia. Such general scientific methods of research as comparison, analysis, statistics, and induction were used in the article. The study concludes that the initiative budgeting should be developed in the current state of the Russian economy as the social and managerial positive effects exceed the possible costs of the suspension of the practice
SberQuAD β Russian Reading Comprehension Dataset: Description and Analysis
The paper presents SberQuAD β a large Russian reading comprehension (RC) dataset created similarly to English SQuAD. SberQuAD contains about 50K question-paragraph-answer triples and is seven times larger compared to the next competitor. We provide its description, thorough analysis, and baseline experimental results. We scrutinized various aspects of the dataset that can have impact on the task performance: question/paragraph similarity, misspellings in questions, answer structure, and question types. We applied five popular RC models to SberQuAD and analyzed their performance. We believe our work makes an important contribution to research in multilingual question answering. Β© 2020, Springer Nature Switzerland AG.We thank Peter Romov, Vladimir Suvorov, and Ekaterina Arte-mova (Chernyak) for providing us with details about SberQuAD preparation. We also thank Natasha Murashkina for initial data processing. PB acknowledges support by Ural Mathematical Center under agreement No. 075-02-2020-1537/1 with the Ministry of Science and Higher Education of the Russian Federation
Reasoning over Knowledge-based Generation of Situations in Context Spaces to Reduce Food Waste
Abstract. Situation awareness is a key feature of pervasive computing and requires external knowledge to interpret data. Ontology-based reasoning approaches allow for the reuse of predefined knowledge, but do not provide the best reasoning capabilities. To overcome this problem, a hybrid model for situation awareness is developed and presented in this paper, which integrates the Situation Theory Ontology into Context Space Theory for inference. Furthermore, in an effort to rely as much as possible on open IoT messaging standards, a domain-independent framework using the O-MI/O-DF standards for sensor data acquisition is developed. This framework is applied to a smart neighborhood use case to reduce food waste at the consumption stage
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