Search results for: G. Reiter

Authors: Christian Meinecke, Bernd Scholz-Reiter

Abstract:

The integrated problem of production and distribution scheduling is relevant in many industrial applications. Thus, many heuristics to solve this integrated problem have been developed in the last decade. Most of these heuristics use a sequential working principal or a single decomposition and integration approach to separate and solve sub-problems. A heuristic using a multi-step decomposition and integration approach is presented in this paper and evaluated in a case study. The result show significant improved results compared with sequential scheduling heuristics.

Keywords: production and outbound distribution, integrated planning, heuristic, decomposition, integration

Procedia PDF Downloads 389

Authors: O. Hinrichs, H. Franz, G. Reiter

Abstract:

Electron guns have a key function in a series of thermal processes, like EB (electron beam) melting, evaporation or welding. These techniques need a high-intensity continuous electron beam that defocuses itself due to high space charge forces. A proper beam transport throughout the magnetic focusing system can be ensured by a space charge compensation via residual gas ions. The different pressure stages in the EB gun cause various degrees of compensation. A numerical model was installed to simulate realistic charge distributions within the beam by using CST-Particle Studio code. We will present current status of beam dynamic simulations. This contribution will focus on the creation of space charge ions and their influence on beam and gun components. Furthermore, the beam transport in the gun will be shown for different beam parameters. The electron source allows to produce beams with currents of 3 A to 15 A and energies of 40 keV to 45 keV.

Keywords: beam dynamic simulation, space charge compensation, thermionic electron source, EB melting, EB thermal processing

Procedia PDF Downloads 307

Authors: Sat Sharma, Antonella Conflitti, Hilary Reiter

Abstract:

Introduction: The study's purpose was to assess the efficacy of the oral appliance device O2Vent Optima + ExVent as compared to Optima in the treatment of OSA. Methods: A prospective, open-label study conducted at 3 sites included subjects with mild to moderate OSA (AHI ≥ 5 and ≤ 30). Screening Phase: A diagnostic in-lab PSG study was performed to confirm a diagnosis of mild to moderate OSA. Treatment I: Subjects used O2Vent Optima for 6 weeks and underwent an in-lab PSG sleep night while using the O2Vent Optima. Treatment II: Subjects used O2Vent Optima + ExVent for 6 weeks and underwent an in-lab PSG sleep night while using the O2Vent Optima + ExVent Primary Effectiveness Measure: Change in AHI between baseline vs. O2Vent Optima MAD vs. O2Vent Optima + ExVent. Results: Treatment with Optima, Optima + ExVent reduced AHI from 22.5±6.4/hr to 12.6±4.5/hr to 5.9±2.7 (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima MAD vs. Optima + ExVent). The average reduction in AHI with Optima was 43%, and with Optima + ExVent was 72%. The lowest oxygen during sleep increased from 84.6±2.7% to 88.6±2.9% to 91.6±3.2% (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima vs. Optima + ExVent). During the trial, patients on treatment with Optima and Optima + ExVent demonstrated no excessive adverse events or device malfunction. Conclusion: Treatment with O2Vent Optima and O2Vent Optima + ExVent significantly improved OSA compared to the baseline. An even greater benefit was observed with the addition of ExVent to the Optima in mild to moderate OSA.

Keywords: oral appliance, O2Vent, sleep dentistry, sleep apnea

Procedia PDF Downloads 38

Authors: Karina Reiter, Stefan Dullinger, Christoph Plutzar, Dietmar Moser

Abstract:

Due to population growth and changing patterns of production and consumption, the demand for natural resources and, as a result, the pressure on Earth’s ecosystems are growing. Biodiversity mapping can be a useful tool for assessing species endangerment or detecting hotspots of extinction risks. This paper explores the benefits of using the change in trophic energy flows as a consequence of the human alteration of the biosphere in biodiversity mapping. To this end, multiple linear regression models were developed to explain species richness in areas where there is no human influence (i.e. wilderness) for three taxonomic groups (birds, mammals, amphibians). The models were then applied to predict (I) potential global species richness using potential natural vegetation (NPPpot) and (II) global ‘actual’ species richness after biomass appropriation using NPP remaining in ecosystems after harvest (NPPeco). By calculating the difference between predicted potential and predicted actual species numbers, maps of estimated species richness loss were generated. Results show that biomass appropriation for human use can indeed be linked to biodiversity loss. Areas for which the models predicted high species loss coincide with areas where species endangerment and extinctions are recorded to be particularly high by the International Union for Conservation of Nature and Natural Resources (IUCN). Furthermore, the analysis revealed that while the species distribution maps of the IUCN Red List of Threatened Species used for this research can determine hotspots of biodiversity loss in large parts of the world, the classification system for threatened and extinct species needs to be revised to better reflect local risks of extinction.

Keywords: biodiversity loss, biomass harvest, human appropriation of net primary production, species richness

Procedia PDF Downloads 98

Authors: F. Lazzeri, I. Reiter

Abstract:

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 267

Authors: Elizabeth Grier, Meg Gemmill, Mary Martin, Leora Reiter, Herman Tang, Alexandra Donaldson, Isis Lunsky, Mia Wu

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Background: Individuals with Cerebral Palsy (CP) and/or IDD face numerous physical and mental health challenges, including difficulty accessing effective palliative care. The aim of this study is to assess the knowledge and comfort of healthcare providers in providing community-based palliative care for patients with Cerebral Palsy (CP) and severe to profound Intellectual and Developmental Disabilities (IDD). Methods: This study includes a mixed methods approach obtaining both quantitative and qualitative data. Quantitative data from palliative care practitioners was obtained through an online survey assessing comfort in symptom management, grief assessment, and goals of care discussion. This survey was distributed to physicians and allied health practitioners across Canada through the College of Family Physicians of Canada Member Interest Groups for Palliative Care and for IDD. Survey results guided the development of a semi-structured interview template, which was used to conduct a focus group on the same topic. Participants were four palliative care providers (3 physicians and one spiritual care practitioner). The focus group transcript is currently undergoing thematic analysis using NVivo 12 software. Results: 57 palliative care practitioners completed the survey. 87% of participants indicated they have provided palliative care services for persons with CP and/or IDD. Findings suggest practitioners are somewhat confident in identifying specific physical symptoms (dyspnea, pressure ulcers) but less confident in identifying physical/emotional pain, addressing grief, and prognosticating life expectancy in this population. 54% of responses indicated they had little/no training on palliating those with CP or IDD, and 45% somewhat or strongly disagree members of their profession can manage symptoms for this population. Focus group analysis is underway, and results will be available at the time of the poster presentation. Conclusion: Persons with CP and IDD are more likely to experience severe health inequities when accessing palliative care. Results of this study suggest further education is needed for palliative care professionals to address the barriers and challenges in providing palliative care to this patient population.

Keywords: palliative care, symptom management, health equity, community healthcare, intellectual and developmental disabilities

Procedia PDF Downloads 102