A Visual Programming Paradigm for Abstract Deep Learning Model Development

Deep learning is one of the fastest growing technologies in computer science with a plethora of applications. But this unprecedented growth has so far been limited to the consumption of deep learning experts. The primary challenge being a steep learning curve for learning the programming libraries and the lack of intuitive systems enabling non-experts to consume deep learning. Towards this goal, we study the effectiveness of a no-code paradigm for designing deep learning models. Particularly, a visual drag-and-drop interface is found more efficient when compared with the traditional programming and alternative visual programming paradigms. We conduct user studies of different expertise levels to measure the entry level barrier and the developer load across different programming paradigms. We obtain a System Usability Scale (SUS) of 90 and a NASA Task Load index (TLX) score of 21 for the proposed visual programming compared to 68 and 52, respectively, for the traditional programming methods

A Seamless Convergence of the Digital and Physical Factory Aiming in Personalized Product Emergence Process (PPEP) for Smart Products within ESB Logistics Learning Factory at Reutlingen University

AbstractA seamless convergence of the digital and physical factory aiming in personalized Product Emergence Process (PPEP) for smart products within ESB Logistics Learning Factory at Reutlingen University.A completely new business model with reference to Industrie4.0 and facilitated by 3D Experience Software in today's networked society in which customers expect immediate responses, delightful experience and simple solutions is one of the mission scenarios in the ESB Logistics Learning Factory at ESB Business School (Reutlingen University).The business experience platform provides software solutions for every organization in the company respectively in the factory. An interface with dashboards, project management apps, 3D - design and construction apps with high end visualization, manufacturing and simulation apps as well as intelligence and social network apps in a collaborative interactive environment help the user to learn the creation of a value end to end process for a personalized virtual and later real produced product.Instead of traditional ways of working and a conventional operating factory real workers and robots work semi-intuitive together. Centerpiece in the self-planned interim factory is the smart personalized product, uniquely identifiable and locatable at all times during the production process – a scooter with an individual colored mobile phone – holder for any smart phone produced with a 3D printer in lot size one. Smart products have in the future solutions incorporated internet based services – designed and manufactured - at the costs of mass products. Additionally the scooter is equipped with a retrievable declarative product memory. Monitoring and control is handled by sensor tags and a raspberry positioned on the product. The engineering design and implementation of a changeable production system is guided by a self-execution system that independently find amongst others esplanade workplaces.The imparted competences to students and professionals are project management method SCRUM, customization of workflows by Industrie4.0 principles, the enhancements of products with new personalized intelligent parts, electrical and electronic self-programmed components and the control of access of the product memory information, to plan in a digital engineering environment and set up of the physical factory to produce customer orders. The gained action-orientated experience refers to the chances and requirements for holistic digital and physical systems

Improving modularity of interactive software with the MDPC Architecture

International audienceThe "Model - Display view - Picking view - Controller" model is a refinement of the MVC architecture. It introduces the "Picking View" component, which offloads the need from the controller to analytically compute the picked element. We describe how using the MPDC architecture leads to benefits in terms of modularity and descriptive ability when implementing interactive components. We report on the use of the MDPC architecture in a real application : we effectively measured gains in controller code, which is simpler and more focused

CIDGIKc: Distance-Geometric Inverse Kinematics for Continuum Robots

The small size, high dexterity, and intrinsic compliance of continuum robots (CRs) make them well suited for constrained environments. Solving the inverse kinematics (IK), that is finding robot joint configurations that satisfy desired position or pose queries, is a fundamental challenge in motion planning, control, and calibration for any robot structure. For CRs, the need to avoid obstacles in tightly confined workspaces greatly complicates the search for feasible IK solutions. Without an accurate initialization or multiple re-starts, existing algorithms often fail to find a solution. We present CIDGIKc (Convex Iteration for Distance-Geometric Inverse Kinematics for Continuum Robots), an algorithm that solves these nonconvex feasibility problems with a sequence of semidefinite programs whose objectives are designed to encourage low-rank minimizers. CIDGIKc is enabled by a novel distance-geometric parameterization of constant curvature segment geometry for CRs with extensible segments. The resulting IK formulation involves only quadratic expressions and can efficiently incorporate a large number of collision avoidance constraints. Our experimental results demonstrate >98% solve success rates within complex, highly cluttered environments which existing algorithms cannot account for