Aircraft Analysis Using the Layered and Extensible Aircraft Performance System (LEAPS)

The Layered and Extensible Aircraft Performance System (LEAPS) is a new air- craft analysis tool being developed by members of the Aeronautics Systems Analysis Branch (ASAB) and the Vehicle Analysis Branch (VAB) at NASA Langley Research Center. LEAPS will enable the analysis of advanced aircraft concepts and architec- tures that include electric and hybrid-electric propulsion systems. The development of LEAPS is motivated by the analysis gaps found in traditional aircraft analysis tools such as the Flight Optimization System (FLOPS). FLOPS has been the tool of choice of the ASAB for over 30 years and has proven to be a reliable analysis tool for conventional aircraft. However, FLOPS is not suitable to analyze the cur- rent unconventional vehicles that are of interest to industry, government agencies, and academia. In contrast, LEAPS is being developed with a flexible architecture that leverages new analysis methodologies that will enable the analysis of unconven- tional aircraft. This paper presents the first complete working version of LEAPS by showing the analysi at include fuel-based and hybrid-electric conceptual aircraft

Supporting community engagement through teaching, student projects and research

The Education Acts statutory obligations for ITPs are not supported by the Crown funding model. Part of the statutory role of an ITP is “... promotes community learning and by research, particularly applied and technological research ...” [The education act 1989]. In relation to this a 2017 TEC report highlighted impaired business models and an excessive administrative burden as restrictive and impeding success. Further restrictions are seen when considering ITPs attract < 3 % of the available TEC funding for research, and ~ 20 % available TEC funding for teaching, despite having overall student efts of ~ 26 % nationally. An attempt to improve performance and engage through collaboration (community, industry, tertiary) at our institution is proving successful. The cross-disciplinary approach provides students high level experience and the technical stretch needed to be successful engineers, technologists and technicians. This study presents one of the methods we use to collaborate externally through teaching, student projects and research

Occupation-Based Measures: an Overview and Discussion

Berufsbezogene Angaben gehören zu den vielseitigsten personenbezogenen Informationen, die in quantitativen Datensätzen zur Verfügung stehen. Ziel dieses Beitrags ist es, einen thematisch möglichst umfassenden Überblick über berufsbasierte Skalen und Instrumente zu geben. Im Mittelpunkt der Ausführungen stehen nicht nur die weit verbreiteten berufsbasierten Instrumente zur Analyse sozialer Schichtung, wie z. B. Prestigeskalen, sozioökonomische Indizes oder Klassenschemata, sondern wir behandeln auch Instrumente zur Erhebung beruflicher Tätigkeitsinhalte sowie Indikatoren zur Erfassung berufsspezifischer Gesundheitsrisiken, beruflicher Geschlechtersegregation oder beruflicher Schließung. Da die Qualität und Aussagekraft solcher Maßzahlen auch von der Qualität und Art der zugrunde liegenden Berufsinformationen abhängt, geben wir außerdem einen Überblick darüber, wie Berufe in Umfragen erfasst und codiert werden und welche Berufsklassifikationen dabei typischerweise zum Einsatz kommen. Wir hoffen, dadurch das Bewusstsein unserer Leserinnen und Leser für das Potenzial berufsbezogener Analysen zu schärfen sowie ihr Wissen über den richtigen Umgang mit berufsbasierten Skalen bei der Anwendung in empirischen Forschungsprojekten zu erhöhen.Occupational information is among the most versatile categories of information about a person available in quantitative data. The goal of this paper is to provide an overview of occupation-based measures in different topic areas. These include not only measures for analyzing social stratification, such as prestige scales, socioeconomic indices and class schemes but also measures of workplace tasks, occupation-specific health risks, gender segregation, and occupational closure. Moreover, as the quality of such data depends on the quality of the underlying occupational information, we also provide an overview of how to collect occupational information in surveys, how to code this information, and how occupational classifications are commonly used. By doing so, we hope to increase researchers’ awareness of the potential of occupation-based analyses, as well as their knowledge of how to properly handle such measures in empirical analyses

Mitigating the Risk of Knowledge Leakage in Knowledge Intensive Organizations: a Mobile Device Perspective

In the current knowledge economy, knowledge represents the most strategically significant resource of organizations. Knowledge-intensive activities advance innovation and create and sustain economic rent and competitive advantage. In order to sustain competitive advantage, organizations must protect knowledge from leakage to third parties, particularly competitors. However, the number and scale of leakage incidents reported in news media as well as industry whitepapers suggests that modern organizations struggle with the protection of sensitive data and organizational knowledge. The increasing use of mobile devices and technologies by knowledge workers across the organizational perimeter has dramatically increased the attack surface of organizations, and the corresponding level of risk exposure. While much of the literature has focused on technology risks that lead to information leakage, human risks that lead to knowledge leakage are relatively understudied. Further, not much is known about strategies to mitigate the risk of knowledge leakage using mobile devices, especially considering the human aspect. Specifically, this research study identified three gaps in the current literature (1) lack of in-depth studies that provide specific strategies for knowledge-intensive organizations based on their varied risk levels. Most of the analysed studies provide high-level strategies that are presented in a generalised manner and fail to identify specific strategies for different organizations and risk levels. (2) lack of research into management of knowledge in the context of mobile devices. And (3) lack of research into the tacit dimension of knowledge as the majority of the literature focuses on formal and informal strategies to protect explicit (codified) knowledge.Comment: The University of Melbourne PhD Thesi

Springs regarded as hydraulic features and interpreted in the context of basin-scale groundwater flow

Springs are sources of freshwater supply. Furthermore, they can also deliver valuable insight into the hydrogeologic processes of a mountainous region, a natural conservation area or a remote study site with no wells. In order to assess the appearance, peculiarities, quality, stability, longevity and resilience of springs and related ecosystems, they need to be regarded in the context of basin-scale groundwater flow systems. The application of spring data evaluation on a basin scale was demonstrated via the carbonate system of Transdanubian Mts., Hungary. The readily measurable physical parameters of springs, the elevation of spring orifice, temperature and volumetric discharge rate provided reasonable classification and characterisation of springs and the related groundwater flow systems. Applying these parameters seemed prospective in a basin-scale understanding of flow systems in data-scarce regions, as monitoring discharge rate and water temperature are cost-effective, requiring no specific tools and analysing procedures. The combined cluster and discriminant analysis (CCDA) can handle uneven data distribution, unequal length and spacing of time series, data gaps, and consider the time-dependent variability of parameters. The optimal number of groups can be determined based on frequently sampled springs (or other entities). The less monitored springs (or other entities) can be classified using a similarity-based approach and linear discriminant analysis (LDA). Diagnosing the relation of springs to groundwater flow systems can advance sustainable water resources management, considering the ecological water needs maintaining various ecosystem services, therefore enhancing the resilience of springs and groundwater-dependent ecosystems

The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study

Background: This paper examines the development of the Connected Health research landscape with a view on providing a historical perspective on existing Connected Health research. Connected Health has become a rapidly growing research field as our healthcare system is facing pressured to become more proactive and patient centred. Objective: We aimed to identify the extent and coverage of the current body of knowledge in Connected Health. With this, we want to identify which topics have drawn the attention of Connected health researchers, and if there are gaps or interdisciplinary opportunities for further research. Methods: We used a systematic mapping study that combines scientific contributions from research on medicine, business, computer science and engineering. We analyse the papers with seven classification criteria, publication source, publication year, research types, empirical types, contribution types research topic and the condition studied in the paper. Results: Altogether, our search resulted in 208 papers which were analysed by a multidisciplinary group of researchers. Our results indicate a slow start for Connected Health research but a more recent steady upswing since 2013. The majority of papers proposed healthcare solutions (37%) or evaluated Connected Health approaches (23%). Case studies (28%) and experiments (26%) were the most popular forms of scientific validation employed. Diabetes, cancer, multiple sclerosis, and heart conditions are among the most prevalent conditions studied. Conclusions: We conclude that Connected Health research seems to be an established field of research, which has been growing strongly during the last five years. There seems to be more focus on technology driven research with a strong contribution from medicine, but business aspects of Connected health are not as much studied

Applications of Affective Computing in Human-Robot Interaction: state-of-art and challenges for manufacturing

The introduction of collaborative robots aims to make production more flexible, promoting a greater interaction between humans and robots also from physical point of view. However, working closely with a robot may lead to the creation of stressful situations for the operator, which can negatively affect task performance. In Human-Robot Interaction (HRI), robots are expected to be socially intelligent, i.e., capable of understanding and reacting accordingly to human social and affective clues. This ability can be exploited implementing affective computing, which concerns the development of systems able to recognize, interpret, process, and simulate human affects. Social intelligence is essential for robots to establish a natural interaction with people in several contexts, including the manufacturing sector with the emergence of Industry 5.0. In order to take full advantage of the human-robot collaboration, the robotic system should be able to perceive the psycho-emotional and mental state of the operator through different sensing modalities (e.g., facial expressions, body language, voice, or physiological signals) and to adapt its behaviour accordingly. The development of socially intelligent collaborative robots in the manufacturing sector can lead to a symbiotic human-robot collaboration, arising several research challenges that still need to be addressed. The goals of this paper are the following: (i) providing an overview of affective computing implementation in HRI; (ii) analyzing the state-of-art on this topic in different application contexts (e.g., healthcare, service applications, and manufacturing); (iii) highlighting research challenges for the manufacturing sector