Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

A classification and review of tools for developing and interacting with machine learning systems

[Abstract] In this paper we aim to bring some order to the myriad of tools that have emerged in the field of Artificial Intelligence (AI), focusing on the field of Machine Learning (ML). For this purpose, we suggest a classification of the tools in which the categories are organized following the development lifecycle of an ML system and we make a review of the existing tools within each section of the classification. We believe this will help to better understand the ecosystem of tools currently available and will also allow us to identify niches in which to develop new tools to aid in the development of AI and ML systems. After reviewing the state-of-the-art of the tools, we have identified three trends in them: the incorporation of humans into the loop of the machine learning process, the movement from ad-hoc and experimental approaches to a more engineering perspective and the ability to make it easier to develop intelligent systems for people without an educational background in the area, in order to move the focus from the technical environment to the domain-specific problem.This work has been supported by the State Research Agency of the Spanish Government, grant (PID2019-107194GB-I00 / AEI / 10.13039/501100011033) and by the Xunta de Galicia, grant (ED431C 2018/34) with the European Union ERDF funds. We wish to acknowledge the support received from the Centro de Investigación de Galicia “CITIC”, funded by Xunta de Galicia and the European Union (European Regional Development Fund-Galicia 2014-2020 Program), by grant ED431G 2019/01Xunta de Galicia; ED431C 2018/34Xunta de Galicia; ED431G 2019/0

How To Create An App

Mobile Computing is booming and everyone has ideas how to profit from it. But only few people know how to build an app that will make those ideas a reality. Businesses are looking for innovative ways to generate revenue from this rapidly growing technology while taking the advantage of the immediacy and convenience that mobile technology has to offer. Mobile apps play a vital role, and have changed the focus from what's on the Web, to the apps on mobile devices, and it is no longer an option but an imperative. The purpose of this article is to provide information on how to create an app and to explore the commonly used tools and technologies to create an app

Using Genetic Algorithms on Groundwater Modeling Problems in a Consulting Setting

This paper presents a practical application for writing and applying simple genetic algorithms (GAs) for the common groundwater flow model, MODFLOW. The method employed by GAs is derived from the driving forces of evolution in the natural world. They employ functions that mimic natural evolutionary processes including selection, mutation, and genetic crossover. A GA solves mathematical problems where a desired outcome to the problem is defined (for example, calibration targets or remediation goals), but the inputs needed to arrive at this outcome are unknown. Our paper includes an introduction to genetic algorithms, the pseudocode of our genetic algorithm for MODFLOW, and the results of an experiential application. Due to the lack of commercially available GAs for MODFLOW, we coded a simple algorithm in Visual Basic Script and applied it to an example model. In the example model, the GA was used to conduct parameter estimation on a MODFLOW model of a river basin in New England that we had previously developed and calibrated in our practice. The calibration target used was net groundwater flow into the river. Four model input parameters were selected as chromosomes for the GA to act on: recharge, river conductance, and two general head boundaries. An initial population of 100 models was developed by varying the value of the gene parameters. The GA ran a MODFLOW simulation for each member of the population, extracted each output file, and established the error of each model from the calibration target. It then evolved the entire population of models towards the calibration target. The GA converged on a single set of input parameter that established best-fit values for all of the chromosome parameters. Genetic algorithms provide a practical alternative to trial-and-error and automated statistical calibration procedures, and can also be used for optimization

The BioLighthouse: Reusable Software Design for Bioinformatics

Advances in next-generation sequencing have accelerated the field of microbiology by making accessible a wealth of information about microbiomes. Unfortunately, microbiome experiments are among the least reproducible in terms of bioinformatics. Software tools are often poorly documented, under-maintained, and commonly have arcane dependencies requiring significant time investment to configure them correctly. Microbiome studies are multidisciplinary efforts but communication and knowledge discrepancies make accessibility, reproducibility, and transparency of computational workflows difficult. The BioLighthouse uses Ansible roles, playbooks, and modules to automate configuration and execution of bioinformatics workflows. The roles and playbooks act as virtual laboratory notebooks by documenting the provenance of a bioinformatics workflow. The BioLighthouse was tested for platform dependence and data-scale dependence with a microbial profiling pipeline. The microbial profiling pipeline consisted of Cutadapt, FLASH2, and DADA2. The pipeline was tested on 3 canola root and soil microbiome datasets with differing orders of magnitude of data: 1 sample, 10 samples, and 100 samples. Each dataset was processed by The BioLighthouse with 10 unique parameter sets and outputs were compared across 8 computing environments for a total of 240 pipeline runs. Outputs after each step in the pipeline were tested for identity using the Linux diff command to ensure reproducible results. Testing of The BioLighthouse suggested no platform or data-scale dependence. To provide an easy way of maintaining environment reproducibility in user-space, Conda and the channel Bioconda were used for virtual environments and software dependencies for configuring bioinformatics tools. The BioLighthouse provides a framework for developers to make their tools accessible to the research community, for bioinformaticians to build bioinformatics workflows, and for the broader research community to consume these tools at a high level while knowing the tools will execute as intended

Human-Centric Tools for Navigating Code

All software failures are fundamentally the fault of humansthe software\u27s design was flawed. The high cost of such failures ultimately results in developers having to design, implement, and test fixes, which all take considerable time and effort, and may result in more failures. As developers work on software maintenance tasks, they must navigate enormous codebases that may comprise millions of lines of code organized across thousands of modules. However, navigating code carries with it a plethora of problems for developers. In the hopes of addressing these navigation barriers, modern code editor and development environments provide a variety of features to aid in navigation; however, they are not without their limitations. Code navigations take many forms, and in this work I focus on three key types of code navigation in modern software development: navigating the working set, navigating among versions of code, and navigating the code structure. To address the challenges of navigating code, I designed three novel software development tools, one to enhance each type of navigation. First, I designed and implemented Patchworks, a code editor interface to support developers in navigating the working set. Patchworks aims to make these more efficient by providing a fixed grid of open code fragments that developers can quickly navigate. Second, I designed and implemented Yestercode, a code editor extension to support navigating among versions of code. Yestercode does so by providing a comparison view of the current code and a previous version of the same code. Third, I designed and implemented Wandercode, a code editor extension to enable developers to efficiently navigate the structure of their code. Wandercode aims to do so by providing a visualization of the code\u27s call graph overlayed on the code editor. My approach to designing these tools for more efficient code navigation was a human-centric onethat is, based on the needs of actual developers performing real software development tasks. Through user study evaluations, I found that these tools significantly improved developer productivity by reducing developers\u27 time spent navigating and mental effort during software maintenance tasks