Design of a compliant wheel for a miniature rover to be used on Mars

The Jet Propulsion Laboratory has identified the need for a compliant wheel for a miniature martian rover vehicle. This wheel must meet requirements of minimum mass, linear radial deflection, and reliability in cryogenic conditions over a five year lifespan. Additionally, axial and tangential deflections must be no more than 10 percent of the radial value. The team designed a wheel by use of finite element and dimensionless parameter analysis. Due to the complex geometry of the wheel, a finite element model describing its behavior was constructed to investigate different wheel configurations. Axial and tangential deflections were greatly reduced but did not meet design criteria. A composite material was selected for its high strength, toughness, fatigue resistance, and damping characteristics. The team chose a Kevlar fiber filled thermoplastic composite. This report is divided into four primary sections. First, the introduction section gives background information, defines the task, and discusses the scope and limitations of the project. Second, the alternative designs section introduces alternative design solutions, addresses advantages and disadvantages of each, and identifies the parameters used to determine the best design. Third, the design solution section introduces the methods used to evaluate the alternates, and gives a description of the design process used. Finally, the conclusion and recommendations section evaluates the wheel design, and offers recommendations pertaining to improvement of the design solution

Data Persistence in Eiffel

This dissertation describes an extension to the Eiffel programming language that provides automatic object persistence (the ability of programs to store objects and later recreate those objects in a subsequent execution of a program). The mechanism is orthogonal to other aspects of the Eiffel language. The mechanism serves four main purposes: 1) it gives Eiffel programmers a needed service, filling a gap between serialization, which provides limited persistence functions and database-mapping, which is cumbersome to use; 2) it greatly reduces the coding burden incurred by the programmer when objects must persist, allowing the programmer to focus instead on the business model; 3) it provides a platform for testing the benefits of orthogonal persistence in Eiffel, and 4) it furnishes a model for orthogonal persistence in other object-oriented languages. During my research, I created a prototype implementation of the persistence mechanism using it effectively in several programs. Performance measurements showed acceptable performance with some increase in program memory usage. The prototype gives the programmer the ability to add automatic persistence to existing code with the addition of only a few lines of code. The size of this additional code remains constant regardless of the total number of lines of code in the project. Eiffel syntax remains unchanged and nonpersistent Eiffel code runs as is while incur- ring only a very small speed penalty

Tolerability, safety, and efficacy of adjunctive brivaracetam for focal seizures in older patients: A pooled analysis from three phase III studies

Introduction: This analysis was conducted to assess the tolerability, safety, and efficacy of brivaracetam (BRV) for adjunctive treatment of focal (partial-onset) seizures in patients aged ≥65 years. Methods: Safety/tolerability and efficacy data for patients aged ≥65 years were pooled from three randomized, double-blind, placebo-controlled, fixed-dose Phase III studies (NCT00490035, NCT00464269, and NCT01261325). Data were pooled by treatment group: placebo or the proposed therapeutic dose range of 50–200 mg/day: BRV 50, 100, 200 mg/day. Results: Thirty-two patients aged ≥65 years were randomized to placebo or BRV 50–200 mg/day. Of these, 30 patients (93.8%) completed their respective study. In the safety population (n = 32), 87.5% placebo- vs 73.3% BRV-treated patients reported treatment-emergent adverse events (TEAEs) during the treatment period; most commonly, headache (25.0% vs 12.5%), paresthesia (0% vs 12.5%), and somnolence (50.0% vs 12.5%) for placebo- vs BRV-treated patients, respectively. During the treatment period, drug-related TEAEs were reported by 62.5% of placebo- vs 53.3% of BRV-treated patients, and serious TEAEs (SAEs) were reported by 0% of placebo- and 4.2% of BRV-treated patients; there were no drug-related SAEs and no deaths. Three SAEs (placebo 1/8; BRV 2/24) and two deaths (placebo 1/8; BRV 1/24) occurred in the post-treatment period. In the efficacy population (n = 31), median percent reduction from baseline in focal seizure frequency/28 days was 14.0% for placebo vs 25.5%, 49.6%, and 74.9% for BRV 50, 100, and 200 mg/day, respectively. The ≥50% responder rate was 14.3% for placebo vs 25.0%, 50.0%, and 66.7% for BRV 50, 100, and 200 mg/day, respectively. Conclusions: Safety/tolerability and efficacy findings in this small subgroup of older patients treated with adjunctive BRV are consistent with those observed in the much larger overall pooled population. BRV may be a suitable adjunctive treatment for older patients with uncontrolled focal seizures. Further larger studies in this population are warranted

AI Radar Sensor: Creating Radar Depth Sounder Images Based on Generative Adversarial Network

This work is licensed under a Creative Commons Attribution 4.0 International License.Significant resources have been spent in collecting and storing large and heterogeneous radar datasets during expensive Arctic and Antarctic fieldwork. The vast majority of data available is unlabeled, and the labeling process is both time-consuming and expensive. One possible alternative to the labeling process is the use of synthetically generated data with artificial intelligence. Instead of labeling real images, we can generate synthetic data based on arbitrary labels. In this way, training data can be quickly augmented with additional images. In this research, we evaluated the performance of synthetically generated radar images based on modified cycle-consistent adversarial networks. We conducted several experiments to test the quality of the generated radar imagery. We also tested the quality of a state-of-the-art contour detection algorithm on synthetic data and different combinations of real and synthetic data. Our experiments show that synthetic radar images generated by generative adversarial network (GAN) can be used in combination with real images for data augmentation and training of deep neural networks. However, the synthetic images generated by GANs cannot be used solely for training a neural network (training on synthetic and testing on real) as they cannot simulate all of the radar characteristics such as noise or Doppler effects. To the best of our knowledge, this is the first work in creating radar sounder imagery based on generative adversarial network

Cloud-Based Learning Tools: Supporting the Invisible Learner (Silent Sufferers) with Socioeconomic Challenges

Today\u27s students are learning at unprecedented speeds. There are a pockets of learners who may be isolated/silent sufferers who face tremendous socioeconomic challenges while seeking higher education. Providing cloud-based technology solutions to strengthen support services and family learning engagement through a series of student family portals will provide the support needed to make student learning opportunities family-based projects or community-based projects successful in graduation completion rates and job placement opportunities

Simon Mono Producciones “Generadora de Audiencias”

Simon Mono Comunicaciones se puede resumir como una proveedora de audiencias nicho a través de contenidos audiovisuales digitales. El objetivo general de la empresa para los clientes es analizar cualitativamente el comportamiento de audiencias en plataformas digitales para el desarrollo de productos audiovisuales. La oferta más exitosa consiste en la generación de contenidos nicho audiovisuales que ayuden a los clientes a captar audiencias

If I Could Be With You

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