A ReRAM Memory Compiler for Monolithic 3D Integrated Circuits in a Carbon Nanotube Process

We present a ReRAM memory compiler for monolithic 3D (M3D) integrated circuits (IC). We develop ReRAM architectures for M3D ICs using 1T-1R bit cells and single and multiple tiers of transistors for access and peripheral circuits. The compiler includes an automated flow for generation of subarrays of different dimensions and larger arrays of a target capacity by integrating multiple subarrays. The compiler is demonstrated using an M3D process design kit (PDK) based on a Carbon Nanotube Transistor technology. The PDK includes multiple layers of transistors and back-end-of-the-line integrated ReRAM. Simulations show the compiled ReRAM macros with multiple tiers of transistors reduces footprint and improves performance over the macros with single-tier transistors. The compiler creates layout views that are exported into library exchange format or graphic data system for full-array assembly and schematic/symbol views to extract per-bit read/write energy and read latency. Comparison of the proposed M3D subarray architectures with baseline 2D subarrays, generated with a custom-designed set of bit cells and peripherals, demonstrate up to 48% area reduction and 13% latency improvement.

Processing of the Results of Satellite Inland Positioning Transport using Mobile Devices and their Visualization

The issue of spatial data visualization is currently an important element in the positioning and navigation process. The constant trend in increasing the accuracy and availability of position modules affects the widespread use of the mobile devices in transport. The paper presents creation of a three-dimensional visualization model based on ground tracks recorded in NMEA (National Marine Electronics Association) and GPX (GPS Exchange Format) formats. Additionally, the study presents an analysis of the positioning accuracy including the sky obstructions presence and the instantaneous state of the satellite constellation. The significant deterioration in positioning accuracies was noted due to the presence of sky obstructions and low movement speed during data recording. The analysis of these parameters showed the dependence of the positioning accuracy with the number of visible satellites and the HDOP (Horizontal Dilution of Precision) parameter.

An OpenBIM workflow to support collaboration between Acoustic Engineers and Architects

Architects require the insight of acoustic engineers to understand how to improve and/or optimize the acoustic performance of their buildings. Normally this is supported by the architect providing digital models of the design to the acoustic engineer for analysis in the acoustician’s disciplinary software, for instance Odeon. This current workflow suffers from the following challenges: (1) architects typically require feedback on architectural disciplinary models that have too much geometric information unnecessarily complicating the acoustic analysis process; (2) the acoustician then has to waste time simplifying that geometry, (3) finally, this extra work wastes money which could otherwise be spent on faster design iterations supported by frequent feedback between architects and acousticians early in the design process. This paper focuses on the architect / acoustician workflow, however similar challenges can be found in other disciplines. OpenBIM workflows provide opportunities to increase the standardization of processes and interfaces between disciplines by reducing the reliance on the proprietary discipline specific file formats and tools. This paper lays the foundation for an OpenBIM workflow to enable the acoustic engineer to provide near real time feedback on the acoustic performance of the architectural design. The proposed workflow investigates the use of the international standard IFC as a design format rather than simply an exchange format. The workflow is presented here with the intention that this will be further explored and developed by other researchers, architects and acousticians.

RCX – an R package adapting the Cytoscape Exchange format for biological networks

Motivation: The Cytoscape Exchange (CX) format is a JSON-based data structure designed for the transmission of biological networks using standard web technologies. It was developed by the network data exchange (NDEx), which itself serves as online commons to share and collaborate on biological networks. The Cytoscape software for the analysis and visualization of biological networks contributes further elements to capture the visual layout within the CX format. However, there is a fundamental difference between web standards and R of how data has to be structured. Results: Here we present a software package to create, handle, validate, visualize and convert networks in CX format to standard data types and objects within R. Networks in this format can serve as a source for biological knowledge, and also capture the results of the analysis of those while preserving the visual layout across all platforms. The RCX package connects the R environment for statistical computing with platforms for collaboration, analysis and visualization of biological networks. Availability: RCX is a free and open-source R package, available via GitHub (https://github.com/frankkramer-lab/RCX) and submitted to Bioconductor.

EnzymeML – a data exchange format for biocatalysis and enzymology

EnzymeML is an XML–based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modelling tools, and databases. EnzymeML supports the scientific community by introducing a standardised data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An Application Programming Interface in Python and Java supports the integration of applications. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modelling using the modelling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO-RK.

Camtrap DP: A frictionless data exchange format for camera trapping data

Camera trapping is one of the most important technologies in conservation and ecological research and a well-established, non-invasive method of collecting field data on animal abundance, distribution, behaviour, temporal activity, and space use (Wearn and Glover-Kapfer 2019). Collectively, camera trapping projects are generating a massive and continuous flow of data, consisting of images and videos (with and without animal observations) and associated identifications (Scotson et al. 2017, Kays et al. 2020). In recent years, significant progress has been made by the global camera trapping community to resolve the challenges this brings, from the development of specialized data management tools and analytical packages, to the application of cloud computing and artificial intelligence to automate species recognition (Tabak et al. 2018). However, to effectively exchange camera trap data between infrastructures and to (automatically) harmonize data into large-scale wildlife datasets, there is a need for a common data exchange format—one that captures the essential information about a camera trap study, allows expression of different study and identification approaches, and aligns well with existing biodiversity standards such as Darwin Core (Wieczorek et al. 2012). Here we present Camera Trap Data Package (Camtrap DP), a data exchange format for camera trap data. It is managed by the Machine Observations Interest Group of Biodiversity Information Standards (TDWG) and developed publicly, soliciting community feedback for every change. Camtrap DP is built on Frictionless Standards, a set of generic specifications to describe and package (tabular) data and metadata. Camtrap DP extends these with specific requirements and constraints for camera trap data. By building on an existing framework, users can employ existing open source software to read and validate Camtrap DP formatted data. Validation especially is useful to automatically check if provided data meets the requirements set forth by Camtrap DP, before analysis or integration. Supported by the major camera trap data management systems e.g. Agouti, TRAPPER, eMammal, and Wildlife Insights, Camtrap DP is reaching its first stable version. The first Camtrap DP dataset was published on Zenodo (Cartuyvels et al. 2021b). This dataset was also published to the Global Biodiversity Information Facility (GBIF) (Cartuyvels et al. 2021a), demonstrating the ability and limitations of transforming the data to the Darwin Core standard.