Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1-the summer 2015 and winter 2016 growing seasons-of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project's goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs

Global Chassis Control: Integration Synergy of Brake and Suspension Control for Active Safety

The paper deals with the investigation of integration synergy of brake and suspension control for reduction of the stopping distance. The basic idea is to take a controllable suspension and to optimize it for decrease of road-tyre force fluctuation. A nonlinear suspension control is proposed for this task. The outlined concept is implemented in a multibody simulation environment and simulation experiments verify its contribution

Overview of Coupling of Multibody and Control Engineering Tools

The role of Computer Aided Engineering in vehicle development has been significantly increased during the last decade. Specialised simulation tools became very complex, however, growing demands on complexity and particularly interdisciplinary of vehicles and their simulation models have led to a number of approaches trying either to develop multidisciplinary simulation tools or to connect various specialised simulation tools by interfaces. This paper addresses some aspects of interconnection of the specialised simulation tools as one possibility for simulating complex mechatronic vehicle systems. It classifies the interfaces between specialised software packages in general, mentions some historical development of the interfacing and further discusses the examples of the implemented couplings between the Multibody System codes and Computer Aided Control Engineering tools. Finally, the performance of selected interfaces is compared on an example simulation of a controlled vehicle suspension

Worlds and transformations: Supporting the sharing and reuse of engineering design knowledge

Design involves the formulation of a solution, such as a product specification, from initial requirements. Design in industrial and other contexts often involves the building and use of models that allow the designer to test hypotheses and learn from possible design decisions prior to building the physical product. The building and testing of models is a design process in its own right. Previous work in knowledge management, design rationale and the psychology of design has demonstrated that designers often vary from prescriptive methodologies of the design process and have problems appropriately describing their design activity in order to support design collaboration and the reuse of design artefacts. Drawing on this work, we support design collaboration and reuse structured according to key transformational episodes in the design process and the design artefacts they produce. To support this, we characterise the design task as progressing through a series of worlds, each comprising its own concepts and vocabulary, and supported by its own design tools. The design process can then be described in terms of important transformations that are made from one world to the next. This allows a targeted approach to rationale capture integrated with work practice and associated with products of the design process. This approach has been successfully deployed and tested in two industrial engineering companies. Findings included improved collaboration in design teams, effective reuse and improved training for new members of the design team. This work has more general implications for the development of design rationale methods and tools to support the design process

Improving the diagnosis of menstrual dysfunction through quality improvement

Introduction: Prevalence of menstrual dysfunction (MD) in high school athletes ranges from 7% to 54%. Early recognition and intervention are crucial to prevent future consequences. The purpose of this Quality Improvement project was to optimize the institution\u27s Epic Best Practice Advisory (BPA) screening tool and synthesize new patient questionnaires to diagnose MD in athletes greater than 12 years of age presenting to a pediatric sports medicine clinic. Methods: Using Quality Improvement methodology, we evaluated clinic flow, the Epic BPA tool, and actions by the physician following the appropriate triggering of the BPA. Diagnoses targeted were primary amenorrhea, oligomenorrhea, or irregular menstruation unspecified. Areas for intervention were global staff education, patient education, and provider alert fatigue. Our team implemented interventions using monthly Plan-Do-Study-Act cycles to address our key drivers. Proper implementation of questionnaire data and restructuring of the Epic BPA promoted identification and diagnosis of MD. The clinician discussed the diagnosis with the patient and family and provided an educational handout on MD. Results: The rate of appropriate diagnosis of MD in athletes greater than 12 years of age seen at a pediatric sports medicine clinic increased from a baseline of 2.1% to 30% over ten months. Identification of three key drivers ultimately drove the success and achievement of our aim. Conclusions: Using Quality Improvement methodology, we optimized the EPIC BPA and subsequently increased the rate of appropriate diagnosis of MD. Identification of the proper diagnosis improves our patient education. Ultimately, this project provided the framework for applicable discussion, interventions, and work-up for at-risk athletes