Abstract: Systems and methods for query generation based on a logical data model with one-to-one joins are described. For example, methods may include accessing a join graph representing tables in a database; receiving a first query; selecting a connected subgraph of the join graph that includes the two or more tables referenced in the first query; accessing an indication that a directed edge of the connected subgraph corresponds to a one-to-one join; modifying the connected subgraph based on the indication to obtain a modified subgraph; generating one or more leaf queries based on the modified subgraph; generating a query graph that specifies joining of results from queries based on the one or more leaf queries; invoking a transformed query on the database that is based on the query graph and the queries based on the one or more leaf queries.

Abstract: The embodiments herein disclose a method for managing machine learning (ML) services in a wireless communication network. The method includes: storing a plurality of ML packages, each executing a network service request; receiving a trigger based on the network service request from a server; determining a plurality of parameters corresponding to the network service request, on receiving the trigger from the server; determining an ML package based on the trigger and the plurality of parameters corresponding to the network service request; and deploying the determined at least one ML package for executing the network service request.

Abstract: A method for detecting stressed plants in an indoor farm includes the steps of receiving two consecutively taken images of a plantation area in the indoor farm captured consecutively at a predetermined interval. The two images are combined to form a composite image. To the composite image is applied an object detection network to segment the composite image into images of single plants. Pre-trained convolution neuronal networks can be applied to the images of single plants classifying the single plants as healthy or stressed.