The article deals with the problems of increasing the efficiency of enterprises and developing a system for assessing the rating of employees of an enterprise. Aspects of motivation for compliance ...with standards by employees and structural divisions are also considered; they were studied because employees are the main driving force of any enterprise. In order to properly evaluate it, many companies need rating systems. In this article, the authors conducted a study and developed a software package for assessing employees of an enterprise. This article describes how to develop a ranking prediction system. MongoDB is used as a database, as the fastest way to innovate, providing the flexibility and ease of use of a database.
The study answers the question which database is the best choice for efficient data storage of UML models. Three products were considered: MongoDB, PostgreSQL and Neo4J. The effectiveness test ...consists of measurement the response time of queries that save and load data. This study also take into account the memory increase ratio during data insertion and the level of complexity of the implementation of the test data mappers used in database queries.
A sudden change in global and regional environmental conditions has triggered the invasion of Sargassum algae in parts of the Caribbean coasts since 2014. To date, it has not been possible to revert ...the trend of seasonal Sargassum invasion, but some public institutions of subtropical countries are in the process of building monitoring systems based on satellite earth observation. Algorithms applied on high spatial resolution (but low revisiting frequency) data have been reported successful for Sargassum detection. GOES-16, MODIS (Aqua & Terra) and VIIRS imagery are acquired daily at the reception station of the National Laboratory for Earth Observation (LANOT), hosted in the Geography Institute, National Autonomous University of Mexico (UNAM). In this research, we implement a near real time Sargassum monitoring platform off the shore of Honduras, Belize and Mexico, based on the above-mentioned satellite imagery. The system design of this platform is first described, including the Big Data infrastructure for image acquisition and storage. Then, Sargassum potential presence is mapped from each of the three sensors, using Python-based processing tools and Sargassum detection algorithms. The coarse spatial resolution products obtained could complement higher spatial resolution studies by providing inputs for temporal modelling of propagation and onshore accumulation of Sargassum.
EAST experiment device uses MDSPlus database to store a large number of experimental data. The users access the data through the API provided by MDSPlus. However, due to the large amount of internal ...data and the lack of unified resource directory, it is difficult to browse experimental data quickly. This paper proposes a metadata management system based on MongoDB to construct resource directory for data. Firstly, the system uses C++ language to scan the entire MDSPlus database to extract and build metadata. Secondly, based on the basic document in BSON format, the system adopts the form of document nested document array, collects all the metadata of each shot in the same document, constructs single metadata using stream document, and establishes metadata database. Thirdly, encapsulates the interface of typical query and cross cut statistics, and performs performance optimization based on index. Finally, a Web project is constructed based on "Spring Boot+Bootstrap" to provide users with database resource directory navigation services. The realization of Metadata database and metadata management system helps users quickly understand the database resource overview, and supports efficient and convenient access to experimental data.
Natural products (NPs) are small molecules produced by living organisms with potential applications in pharmacology and other industries as many of them are bioactive. This potential raised great ...interest in NP research around the world and in different application fields, therefore, over the years a multiplication of generalistic and thematic NP databases has been observed. However, there is, at this moment, no online resource regrouping all known NPs in just one place, which would greatly simplify NPs research and allow computational screening and other
in silico
applications. In this manuscript we present the online version of the COlleCtion of Open Natural prodUcTs (COCONUT): an aggregated dataset of elucidated and predicted NPs collected from open sources and a web interface to browse, search and easily and quickly download NPs. COCONUT web is freely available at
https://coconut.naturalproducts.net
.
The scientific article deals with a comparison of the query speed of two NoSQL databases. Described databases will be MongoDB and CouchDB. The work presents speed comparisons of such queries as ...adding data to the database, editing database data, deleting data from the database, and searching data in the database. Also a general comparison of bases will be presented, with the answer to the question of which of the tested NoSQL databases is faster.
Indoor thermal comfort has been the subject of several studies in the last years, aiming to create a satisfying work environment for the occupants inside a building. However, thermal comfort is ...strongly related to the occupants. Accordingly, it is necessary to take into consideration the user’s thermal preferences when adjusting the thermal conditions in buildings. This work aims to develop an innovative and smart solution, based on BIM, IoT, Machine Learning, and the user experience, to build a thermal comfort model.
A BIM model was designed to ingest data streams from the IoT devices together with the user’s thermal preferences specified via a mobile application. The study area was divided into a three-dimensional grid where, for each voxel, the Predicted Mean Vote (PMV) was calculated. The occupant indicates his thermal sensation, noted as Personal Vote (PV), associated with his profile and his position. These measures were used to train a logistic regression model to find the correlation between the PMV and PV. Ultimately, an LSTM Deep Learning model was trained to forecast the optimal temperature of the study area in the next working hours. The results were visualized both on the mobile application and in the BIM environment.
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