Microsoft Excel

Summary

Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS. It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA). Excel forms part of the Microsoft 365 suite of software. Features Basic operation Spreadsheet Microsoft Excel has the basic features of all spreadsheets, using a grid of cells arranged in numbered rows and letter-named columns to organize data manipulations like arithmetic operations. It has a battery of supplied functions to answer statistical, engineering, and financial needs. In addition, it can display data as line graphs, histograms and charts, and with a very limited three-dimensional graphical display. It allows sectioning of data to view its dependencies on various factors for different perspectives (using pivot tables and the scenario manager). A PivotTable is a tool for data analysis. It d

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LaMBERT: Light and Multigranular BERT

Ljupche Milosheski

Pre-training complex language models is essential for the success of the recent methods such as BERT or OpenAI GPT. Their size makes not only the pre-training phase, but also consecutive applications to be computationally expensive. BERT-like models excel at token-level tasks as they provide reliable token embeddings, but they fall short when it comes to sentence or higher-level structure embeddings. The reason is that these models do not have a built-in mechanism that explicitly provides such representations. We introduce Light and Multigranural BERT that has similar complexity to BERT in the number of parameters, but is about 3 times faster by modifying the input representation, which consequently introduces changes to the attention mechanism and at the same time produces reliable segment embeddings as it is one of our training objectives. The model we publish achieves 70.7% on the MNLI task, which is promising bearing in mind there were two major issues with it.

2020

This paper introduces a new task termed low-latency speaker spotting (LLSS). Related to security and intelligence applications, the task involves the detection, as soon as possible, of known speakers within multi-speaker audio streams. The paper describes differences to the established fields of speaker diarization and automatic speaker verification and proposes a new protocol and metrics to support exploration of LLSS. These can be used together with an existing, publicly available database to assess the performance of LLSS solutions also proposed in the paper. They combine online diarization and speaker detection systems. Diarization systems include a naive, over-segmentation approach and fully-fledged online diarization using segmental i-vectors. Speaker detection is performed using Gaussian mixture models, i-vectors or neural speaker embeddings. Metrics reflect different approaches to characterise latency in addition to detection performance. The relative performance of each solution is dependent on latency. When higher latency is admissible, i-vector solutions perform well; embeddings excel when latency must be kept to a minimum. With a need to improve the reliability of online diarization and detection, the proposed LLSS framework provides a vehicle to fuel future research in both areas. In this respect, we embrace a reproducible research policy; results can be readily reproduced using publicly available resources and open source codes.

2018

Design tools for large networks

Bryn Andrew Martin

The Atlas TDAQ network consists of four separate networks which together total over 8000 ports at 1 Gbit/s, 60 ports at 10 Gbit/s, 200 Ethernet switches at the edge of the network, 6 multi-blade chassis switches at the core and over 20 km of copper and fiber cabling. The NetDesign suite was developed to provide a comprehensive set of tools that permits the generation of a navigable network design, automates a number of routine tasks and provides the user with a powerful and flexible reporting system. NetDesign is an add-on extension to the basic functionality of the Microsoft Visio tool. It features: automatic labeling of cables, media/port connection validation, navigation along a cable, hierarchical schematics, cross-page and vertical navigation, overall verification of the network diagram and hyperlinks to other equipment databases. The internal network structure can be exported to a third party database from which a large variety of reports can be obtained. The reports are defined using a special user-friendly meta-language and are written to a Microsoft Excel sheet. The database representation can also be used for consistency checks with the other ATLAS equipment data repositories.

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