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公开(公告)号:US20240070354A1
公开(公告)日:2024-02-29
申请号:US18078538
申请日:2022-12-09
Applicant: SAP SE
Inventor: Jochen Mayerle , Astrid Graeber , Veit Spaegele , Raffael Lutz
IPC: G06F30/28
CPC classification number: G06F30/28
Abstract: Mechanisms are disclosed for modelling and quantitatively characterizing emissions inflows and outflows. Scoping inputs are received including a physical process defined scope of emission-producing physical inputs. Modeling inputs are received, including footprints associated with physical manufacturing inputs. The model energy flows may be provided via a graphical modeling user interface and support allocation rule definitions for distributing emissions footprint definitions. An estimated emission flow is calculated based on combined energy flows. The material flows may be derived from aggregated transaction data associated with emission-producing physical inputs. The calculated emission flow may be based on a calculated emission footprint at stages along a production process. Analytics user interfaces associated with the calculated emissions flows may provide insight into the highest emission producing emission drivers along the production chain in connection with a technical report.
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公开(公告)号:US20220101212A1
公开(公告)日:2022-03-31
申请号:US17039439
申请日:2020-09-30
Applicant: SAP SE
Inventor: Astrid Graeber , Jochen Mayerle
Abstract: In one aspect, there is disclosed a computer-implemented method that includes extending an existing first data model of an enterprise resource planning system to include a second data model, wherein the first and second data models provide a greenhouse gas emissions model; providing the extended greenhouse gas emissions model to enable a calculation that allocates to the product or the service an amount of greenhouse gas emissions; and causing display of a user interface including the amount of greenhouse gas emissions allocated to the product or the service. Related systems, methods, and articles of manufacture are also disclosed.
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公开(公告)号:US20210150484A1
公开(公告)日:2021-05-20
申请号:US16689434
申请日:2019-11-20
Applicant: SAP SE
Inventor: Jochen Mayerle , Udo Klein , Vladislav Bezrukov
Abstract: Provided is a system and method for generating job posting content through machine learning. In one example, the method may include storing text content of previous postings, receiving target attributes of a candidate that is a subject of a new posting, identifying, via a machine learning model, a subset of previous postings from among the previous postings which are most closely related to the new posting based on the target attributes of the candidate with respect to content of the previous postings, and detecting text objects from the identified subset of previous postings and outputting a display of the detected text objects.
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公开(公告)号:US20240386356A1
公开(公告)日:2024-11-21
申请号:US18665299
申请日:2024-05-15
Applicant: SAP SE
Inventor: Miklos Zoltan Szabo , Matthias Saettele , Jochen Mayerle , Christoph Ehrhardt , Stefan Feickert , Bastian Distler , Christoph Ernst , Edrilan Berisha , Florence Jungnickel
IPC: G06Q10/0637 , G06F16/18
Abstract: Various examples are directed to systems and methods of using a database management system (DBMS) to post a transaction. An enterprise resource planning (ERP) application may receive first transaction data associated with a first transaction including acquisition of a first component of a first component type. The first transaction data may describe an indicator of the first component, a cost of the first component of a first component type, and a first environmental metric associated with the first component. The ERP application may write a first transaction entry to a universal journal table of the DBMS, the first transaction entry comprising a description of the first transaction, and a component breakdown key. The ERP application may also write a first component breakdown entry to a component breakdown table of the DBMS.
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公开(公告)号:US11551187B2
公开(公告)日:2023-01-10
申请号:US16689434
申请日:2019-11-20
Applicant: SAP SE
Inventor: Jochen Mayerle , Udo Klein , Vladislav Bezrukov
Abstract: Provided is a system and method for generating job posting content through machine learning. In one example, the method may include storing text content of previous postings, receiving target attributes of a candidate that is a subject of a new posting, identifying, via a machine learning model, a subset of previous postings from among the previous postings which are most closely related to the new posting based on the target attributes of the candidate with respect to content of the previous postings, and detecting text objects from the identified subset of previous postings and outputting a display of the detected text objects.
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