ADLib: An Arduino Communication Framework for Ambient Displays

As computers become more and more a part of our everyday lives, the need to change the way in which people interact with them is also evolving. Ambient displays provide an effective way to move computers away from our main focus and into the periphery. ADLib is a small communication framework that aims to simplify the construction of ambient displays built using the Arduino prototyping platform. The ADLib framework provides an easy-to-use library for communicating with an Arduino, allowing the user to focus on the construction and development of the display. The framework consists of three main components: A protocol for encoding information to be sent from a host computer to the Arduino An Arduino library for receiving and parsing incoming data A desktop application for sending data to the Arduin

MPRAnalyze: statistical framework for massively parallel reporter assays.

Massively parallel reporter assays (MPRAs) can measure the regulatory function of thousands of DNA sequences in a single experiment. Despite growing popularity, MPRA studies are limited by a lack of a unified framework for analyzing the resulting data. Here we present MPRAnalyze: a statistical framework for analyzing MPRA count data. Our model leverages the unique structure of MPRA data to quantify the function of regulatory sequences, compare sequences' activity across different conditions, and provide necessary flexibility in an evolving field. We demonstrate the accuracy and applicability of MPRAnalyze on simulated and published data and compare it with existing methods

The great good place : coworking como espaço para aprender design uma framework exploratória

Abstract : In this paper we explore a conceptual framework based on three lines of thinking/work from Patrick Cohendet (Underground/Middleground/Upperground), Ray Oldenburg (The Great Good Place), and Fred Garneti (Heutagogy or Self-determined Learning). To demonstrate the relevance and feasibility of our proposed concept, we review the key factors and definitions of these authors and their work. Although not a theoretical framework, the present paper aims to help us map a part of our research work within the context of the Doctoral Programme in Design at IADE / Universidade Europeia, which triangulates Coworking, Design Learning, and Heutagogy or selfdetermined modes of learning. Ultimately, the aim is to generate new evidence on how such a model of Coworking Design Learning can benefit and betier suit contemporary Design learners.Neste artigo, exploramos uma estrutura conceptual baseada em três linhas de pensamento dos autores Patrick Cohendet (Underground / Middleground / Upperground), Ray Oldenburg (The Great Good Place) e Fred Garneti (Heutagogy or Self-determined Learning). Para demonstrar a relevância e a viabilidade da nossa proposta conceptual, revisitamos os principais fatores e definições destes autores e dos seus trabalhos. Embora não constitua uma framework teórica, o presente trabalho tem como objetivo ajudar a mapear parte do nosso trabalho de pesquisa no contexto do Programa de Doutoramento em Design do IADE / Universidade Europeia, que triangula Coworking, Aprendizagem de Design e Heutagogia ou modos autodeterminados de aprendizagem. Em última instância, o objetivo é tentar produzir novas evidências sobre como um modelo de aprendizagem de Design baseado em espaços de Coworking pode beneficiar e adequar-se melhor aos actuais alunos de Design.info:eu-repo/semantics/publishedVersio

ChimpCheck: Property-Based Randomized Test Generation for Interactive Apps

We consider the problem of generating relevant execution traces to test rich interactive applications. Rich interactive applications, such as apps on mobile platforms, are complex stateful and often distributed systems where sufficiently exercising the app with user-interaction (UI) event sequences to expose defects is both hard and time-consuming. In particular, there is a fundamental tension between brute-force random UI exercising tools, which are fully-automated but offer low relevance, and UI test scripts, which are manual but offer high relevance. In this paper, we consider a middle way---enabling a seamless fusion of scripted and randomized UI testing. This fusion is prototyped in a testing tool called ChimpCheck for programming, generating, and executing property-based randomized test cases for Android apps. Our approach realizes this fusion by offering a high-level, embedded domain-specific language for defining custom generators of simulated user-interaction event sequences. What follows is a combinator library built on industrial strength frameworks for property-based testing (ScalaCheck) and Android testing (Android JUnit and Espresso) to implement property-based randomized testing for Android development. Driven by real, reported issues in open source Android apps, we show, through case studies, how ChimpCheck enables expressing effective testing patterns in a compact manner.Comment: 20 pages, 21 figures, Symposium on New ideas, New Paradigms, and Reflections on Programming and Software (Onward!2017

Rapid prototyping for Martian space systems

With the clear path towards Mars for future human exploration missions, rapid prototyping tools may enhance different missions' architectural solutions. Such tools rapidly estimate mass, power and data budgets, providing quantitative figures of metrics to evaluate the most effective technical solutions in line with the stakeholders' needs. Politecnico di Torino is actively working on IDREAM an integrated framework with capabilities of sizing space systems, estimating their cost and building roadmaps for the maturation of the involved technologies. The iDREAM methodology consists of four main modules that can be used in a stand-alone mode and in an integrated activity flow, exploiting the implemented automatic connections. The first module consists of a well-structured MySQL database developed to support all the other modules, thanks to a unified connection guaranteed by an ad-hoc developed Database Management Library managing the operations of data input and output from/to the database throughout the tool modules. The second module consists of a vehicle design routine and a mission design routine, supporting the design of a new vehicle and mission concept and assessing the main performance of an already existing configuration. The third module is estimating the cost of the system. Once the design is defined, it is possible to run a subsystem-level cost estimation. Using the subsystems’ masses estimated in the design routine, the parametric cost model provides useful insights into the potential development, manufacturing, and operating costs, as well as the cost and price per flight. Eventually, the developed methodology gives the possibility to generate a technology roadmap (fourth module). Supported by a database connection, the tool estimates each technology readiness and risk assessment and indicates the necessary activities, missions, and future works. This presentation highlights the use of IDREAM to rapidly prototype Martian space systems

Semi Automated Partial Credit Grading of Programming Assignments

The grading of student programs is a time consuming process. As class sizes continue to grow, especially in entry level courses, manually grading student programs has become an even more daunting challenge. Increasing the difficulty of grading is the needs of graphical and interactive programs such as those used as part of the UNH Computer Science curriculum (and various textbooks). There are existing tools that support the grading of introductory programming assignments (TAME and Web-CAT). There are also frameworks that can be used to test student code (JUnit, Tester, and TestNG). While these programs and frameworks are helpful, they have little or no no support for programs that use real data structures or that have interactive or graphical features. In addition, the automated tests in all these tools provide only “all or nothing” evaluation. This is a significant limitation in many circumstances. Moreover, there is little or no support for dynamic alteration of grading criteria, which means that refactoring of test classes after deployment is not easily done. Our goal is to create a framework that can address these weaknesses. This framework needs to: 1. Support assignments that have interactive and graphical components. 2. Handle data structures in student programs such as lists, stacks, trees, and hash tables. 3. Be able to assign partial credit automatically when the instructor can predict errors in advance. 4. Provide additional answer clustering information to help graders identify and assign consistent partial credit for incorrect output that was not predefined. Most importantly, these tools, collectively called RPM (short for Rapid Program Management), should interface effectively with our current grading support framework without requiring large amounts of rewriting or refactoring of test code

Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study

Developing robot agnostic software frameworks involves synthesizing the disparate fields of robotic theory and software engineering while simultaneously accounting for a large variability in hardware designs and control paradigms. As the capabilities of robotic software frameworks increase, the setup difficulty and learning curve for new users also increase. If the entry barriers for configuring and using the software on robots is too high, even the most powerful of frameworks are useless. A growing need exists in robotic software engineering to aid users in getting started with, and customizing, the software framework as necessary for particular robotic applications. In this paper a case study is presented for the best practices found for lowering the barrier of entry in the MoveIt! framework, an open-source tool for mobile manipulation in ROS, that allows users to 1) quickly get basic motion planning functionality with minimal initial setup, 2) automate its configuration and optimization, and 3) easily customize its components. A graphical interface that assists the user in configuring MoveIt! is the cornerstone of our approach, coupled with the use of an existing standardized robot model for input, automatically generated robot-specific configuration files, and a plugin-based architecture for extensibility. These best practices are summarized into a set of barrier to entry design principles applicable to other robotic software. The approaches for lowering the entry barrier are evaluated by usage statistics, a user survey, and compared against our design objectives for their effectiveness to users