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Institute
Die Positionsbestimmung im Indoor-Bereich
ermöglicht im Vergleich zu GPS komplett neue
Anwendungsszenarien. Hierfür ist Technologie notwendig,
welche immer weiter untersucht werden muss, um dessen
Systemgrenzen aufzuzeigen. Die Firma Decawave stellt mit dem
DWM1001 ein Ultrabreitbandmodul zur Verfügung, welches
eine Positionsbestimmung bis zu 10 Zentimetern Genauigkeit
erfüllen soll. Wie sich herausstellt, trifft dies nicht für die Höheninformation der Position zu.
Mikroskopische Simulationen zur Fahrzeugsimulation sind eine wichtige Komponente zur Entwicklung für Algorithmen autonomer Fahrzeuge. Die Generierung notwendiger Szenarien mit synthetischen Methoden ist zeitaufwendig oder bildet die Realität nicht ausreichend nach. Ziel dieser Forschungsarbeit ist die Entwicklung eines Toolsets zur Generierung realistischer Szenarien aus realen Messdaten für die Simulationsumgebung LGSVL. Das Resultat dieser Arbeit ist ein Prototyp zur Extraktion und Vorverarbeitung der Messdaten, die Generierung einer Karte aus Kartendaten
und Integration dieser in eine Simulation. Weiterhin wurde eine Anbindungsmöglichkeit zur Steuerung der Fahrzeuge und dem Datenaustausch mit der Softwarebibliothek ROS untersucht.
Gestationsdiabetes mellitus (GDM) ist eine der häufigsten Komplikationen in der Schwangerschaft mit einer weltweit steigenden Prävalenz. Betroffene Schwangere und haben gegenüber gesunden Schwangeren ein höheres Risiko an perinataler Morbidität und Mortalität und eine höhere Rate an operativen Entbindungen. Für die Kinder von Frauen mit GDM impliziert dieser schon in der Schwangerschaft erhebliche neonatale und im Folgenden deutlich höhere Langzeitrisiken für (multi-) Morbidität.
Im Hinblick auf eine Risikoreduktion für betroffene Frauen und Kinder sind Präventionsmaßnahmen durch Lebensstilveränderungen der gesunden Ernährung und Anpassung bzw. Erhöhung der mütterlichen körperlichen Aktivität innerhalb der Schwangerschaft, welche sich im besten Falle nachhaltig über die Schwangerschaft hinaus etabliert, essentiell. Im besonderen Fokus steht der Einbezug der fachlich involvierten Berufsgruppe der Hebammen, welche im geburtshilflichen Aufgabenfeld der (Sekundär-) Prävention etabliert sind und somit betroffenen Schwangeren professionelle Hilfestellungen anbieten können.
Die folgende Ausarbeitung fokussiert die Gesundheitsförderung von Frauen mit GDM und deren Ungeborenen in der Schwangerschaft und darüber hinaus. Im Mittelpunkt steht dabei die ethische Reflexion eines von der Hochschule Esslingen beantragten For-schungsprojektes in Vorbereitung des erforderlichen ethischen Clearings durch die Ethikkommission der Deutschen Gesellschaft für Pflegewissenschaft (DGP).
Gestationsdiabetes mellitus (GDM) ist eine der häufigsten Komplikationen in der Schwangerschaft mit einer weltweit steigenden Prävalenz. Betroffene Schwangere haben gegenüber gesunden Schwangeren ein höheres Risiko an perinataler Morbidität und Mortalität und eine höhere Rate an operativen Entbindungen. Zudem besteht für diese Frauen ein siebenfach höheres Risiko, nach der Geburt einen Diabetes mellitus Typ II zu entwickeln. Für die Kinder von Frauen mit GDM bestehen schon in der Schwangerschaft erhebliche neonatale Risiken, zudem haben Kinder betroffener Schwangerer deutlich höhere Langzeitrisiken der Adipositas und eines manifesten Diabetes mellitus Typ I/II.
Die Risikobelastung von Schwangeren mit GDM und ihren Kindern besitzt gesamtgesell-schaftliche Relevanz, die die Notwendigkeit von Präventionsmaßnahmen ersichtlich machen. Durch gelungene Präventionsmaßnahmen wie ein veränderter Lebensstil im Hinblick auf eine gesunde Ernährung und ausreichend Bewegung/körperliche Aktivität können Mütter und deren Kinder profitieren.
Das Berufsbild der Hebamme ist im geburtshilflichen Aufgabenfeld der (Sekundär-) Prävention etabliert. Hebammen bieten Schwangeren professionelle Hilfestellungen an, die diese in der Wahrnehmung ihrer körpereigenen Prozesse unterstützen und für die Identifizierung eigener Bedürfnisse befähigen.
Die folgende Abhandlung beschreibt, ob und inwiefern Hebammen im Rahmen der Betreuung von Schwangeren mit GDM auf der Basis aktueller Evidenzen betroffene Frauen zukünftig in neuen, sekundärpräventiven Versorgungskonzepten begleiten könnten.
Inwieweit wird die Drogenprohibitionspolitik im Fachdiskurs problematisiert
und wie lässt sich demgegenüber eine politische Position für das Arbeitsfeld
Sucht- und Drogenhilfe im Sinne einer kritischen und menschenrechtsorientierten Sozialen Arbeit entwickeln?
Diese Arbeit befasst sich zunächst mit dem Inhalt der Drogenprohibitionspolitik
sowie deren historischen Entwicklung. Danach werden Beiträge aus unterschiedlichen wissenschaftlichen Disziplinen beschrieben, die sich mit den negativen Auswirkungen der prohibitiven Drogenpolitik befassen: die sozialen und gesundheitlichen Folgen des Drogenverbots auf Drogenkonsumierende, die direkt und indirekt ausgelösten Menschenrechtsverletzungen, die rechtstheoretische Kritik am Beispiel des deutschen Verfassungsrechts sowie die Vorstellung zweier Studien, die die überproportionale Kriminalisierung von gesellschaftlichen Minderheiten und Armut am Beispiel Österreich und USA aufzeigen.
Darauffolgend wird der Wandel in der Sucht- und Drogenhilfe der Sozialen Arbeit vom
Abstinenzparadigma zur Akzeptanzorientierung kurz dargestellt und diese beiden Arbeitsprinzipien erläutert. Anschließend wird aufgezeigt, inwiefern auch die akzeptanzorientierte
Drogenarbeit Teil von sozialer Kontrollpolitik sein kann.
Um einen theoretischen Rahmen für die politische Einflussnahme durch die Soziale Arbeit
aufzuzeigen, befasst sich diese Bachelorarbeit anschließend mit den Theorien der Kritischen Sozialen Arbeit des
Trippelmandats von Silvia Staub-Bernasconi sowie der Radikalen Praxis für Gesellschaftsveränderung von David G. Gil.
Darauffolgend wird der theoretische Rahmen der politischen Einflussnahme durch die Soziale
Arbeit mit einem ethik-basierten Rahmen ergänzt. Dazu werden die auf die Verwirklichung
der Menschenrechte bezogene Theorien der Alteritätsethik von Emmanuel Lévinas (Recht
des Anderen), der Diskursethik von Rainer Forst (Recht auf Rechtfertigung) sowie der
Anerkennungsethik von Hannah Arendt (Recht, Rechte zu haben) und die daraus resultierende Implikationen für politisches Engagement durch die Soziale Arbeit beschrieben.
Zum Ende hin wird die aktuelle Problematisierung der Drogenprohibition
in der Praxis dargestellt. Hierzu wird untersucht, inwieweit die Berufsverbände der Sozialen Arbeit sowie die deutschen Fachverbände der Sucht- und Drogenhilfe sich drogenpolitisch positionieren sowie der Alternative Drogen- und Suchtbericht vorgestellt.
This master thesis shows a holistic approach for the optimization of the energy management task for a plug-in hybrid electric vehicle. The ‘Equivalent Consumption Minimization Strategy’ (‘ECMS’) as a local optimal approach is implemented into an embedded controller and applied to a system simulation model in ‘GT-SUITE’, which integrates a hybrid drivetrain and the associated control structure with a thermal management model. Two modifications and one extension to the basic ‘equivalent consumption’ cost function are proposed for the favor of an unambiguous interpretation of the penalty factor term, an enhanced applicability of the ‘ECMS’ close to the battery state of charge limit and an effective applicability of the ‘EMCS’ to the thermal management task. All proposed modifications and extensions prove their applicability in the virtual test environment and recommend themselves for the utilization in further application areas, like the integration of exhaust aftertreatment system, the holistic evaluation of a fuel cell drivetrain or the holistic evaluation of a hybrid ship propulsion system.
Partizipative Forschung
(2020)
Dieser Open-Access-Sammelband bietet eine gute Grundlage für den Einstieg in die partizipative Forschung allgemein und in die Partizipative Gesundheitsforschung. Es werden Forschungsansätze und Methoden für die Erhebung und Auswertung in partizipativen Forschungsprozessen vorgestellt und anhand von Beispielstudien diskutiert. Partizipativ forschen heißt, die Menschen, deren Lebens- und Arbeitsbereiche erforscht werden, über alle Phasen des Forschungsprozesses zu beteiligen. Partizipation dient dem Erkenntnisgewinn, aber auch dem Ziel, die soziale Wirklichkeit der Menschen, ihr Leben und Wohlbefinden zu verbessern.
Slips and stumbles are main causes of falls and result in serious injuries. Balance training is widely applied for preventing falls across the lifespan. Subdivided into two main intervention types, biomechanical characteristics differ amongst balance interventions tailored to counteract falls: conventional balance training (CBT) referring to a balance task with a static ledger pivoting around the ankle joint versus reactive balance training (RBT) using externally applied perturbations to deteriorate body equilibrium. This study aimed to evaluate the efficacy of reactive, slip-simulating RBT compared to CBT in regard to fall prevention and to detect neuromuscular and kinematic dependencies. In a randomized controlled trial, 38 participants were randomly allocated either to CBT or RBT. To simulate stumbling scenarios, postural responses were assessed to posterior translations in gait and stance perturbation before and after 4 weeks of training. Surface electromyography during short- (SLR), medium- (MLR), and long-latency response of shank and thigh muscles as well as ankle, knee, and hip joint kinematics (amplitudes and velocities) were recorded. Both training modalities revealed reduced angular velocity in the ankle joint (P < 0.05) accompanied by increased shank muscle activity in SLR (P < 0.05) during marching in place perturbation. During stance perturbation and marching in place perturbation, hip angular velocity was decreased after RBT (P from TTEST, Pt < 0.05) accompanied by enhanced thigh muscle activity (SLR, MLR) after both trainings (P < 0.05). Effect sizes were larger for the RBT-group during stance perturbation. Thus, both interventions revealed modified stabilization strategies for reactive balance recovery after surface translations. Characterized by enhanced reflex activity in the leg muscles antagonizing the surface translations, balance training is associated with improved neuromuscular timing and accuracy being relevant for postural control. This may result in more efficient segmental stabilization during fall risk situations, independent of the intervention modality. More pronounced modulations and higher effect sizes after RBT in stance perturbation point toward specificity of training adaptations, with an emphasis on the proximal body segment for RBT. Outcomes underline the benefits of balance training with a clear distinction between RBT and CBT being relevant for training application over the lifespan.
Das Jahr 2020 wurde von der Weltgesundheitsorganisation aus Anlass des 200. Geburtstags von Florence Nightingale – Pionierin der Pflege(wissenschaft) – zum »Jahr der Pf lege und des Hebammenwesens« ausgeru-fen. Gleichzeitig läuft beim International Council of Nursing (ICN) die Kampagne »Nursing Now«. Damit will der ICN auf die entscheidende Rolle der Pflegefachkräfte für die Gesundheit aller Menschen weltweit hinweisen. Parallel und unabhängig davon wird in Deutschland derzeit ein öffentlicher und politischer Diskurs im Kontext des »Fachkräfteman-gels« in der beruflichen Pflege geführt, der stark vom Thema »Berufs-attraktivität« dominiert ist. So wichtig sowohl die Diskussionen über Attraktivitätsfaktoren wie beispielsweise das Gehalt als auch die ent-sprechenden Reformanstrengungen sind, erscheinen sie doch verkürzt. Berufsattraktivität in der Pflege kann nicht ohne Betrachtung von Profes-sionalisierungsprozessen und Ökonomisierungslogiken als relevante Ent-wicklungen in der Pf lege sowie deren widersprüchlichem Spannungsverhältnis diskutiert werden. Sowohl in wissenschaftlichen als auch in politischen Diskursen werden diese beiden Prozesse meist unabhängig voneinander verhandelt. Sie stehen jedoch in einem für die Berufsattraktivität äußerst problematischen Wechselverhältnis. Dies zu berücksichtigen, erscheint für die Zukunft der beruflichen Pflege von hoher Relevanz. Dieser Beitrag erweitert den Diskurs um Fachkräftemangel beziehungs-weise -bedarf in der Pf lege um eine differenzierte Betrachtung des hoch-
komplexen wechselseitigen Spannungsverhältnisses zwischen Ökonomie und Professionalisierung sowie dessen Auswirkungen auf die Berufsattraktivität.Um das Thema in seiner Komplexität darstellen zu können, erfolgt zunächst ein Abriss des Professionalisierungsprozesses der Alten- und (Kinder-)Krankenpflege in Deutschland. Anschließend werden die Ökonomisierung des Gesundheitswesens und deren Auswirkung auf den Berufsalltag dargestellt. Die Folgen der Ökonomisierung auf den Professionalisierungsprozess und schließlich auch für die Berufsattraktivität werden anhand empirischer Daten des Forschungsverbundes ZAFH care4care – Fachkräftebedarf in der Pflege im Zeichen von Alterung, Vielfalt und Zufriedenheit1 analysiert. Daraus abgeleitet werden abschließend exemplarisch Ansatzpunkte für weitere Aushandlungsprozesse skizziert.
Vor dem Hintergrund des bundesweiten Fachkräftemangels in der Pflege verwundert es, dass Zeitarbeit innerhalb der Pflegebranche als Beschäftigungsform eine wachsende Bedeutung erhält. Allerdings funktioniert Zeitarbeit in der Pflege im Vergleich zu anderen Branchen nach anderen Logiken: Während beispielsweise im verarbeitenden Gewerbe durch den Einsatz von Zeitarbeitskräften bei schwankender Konjunktur Flexibilität gewährleistet oder Personalkosten gesenkt werden können, besteht in der Pflege ein anhaltend hoher Personalbedarf und die Kosten für Zeitarbeiter*innen übersteigen häufig die des Stammpersonals. Das in anderen Branchen üblicherweise als prekär bewertete Arbeitsverhältnis bietet Pflegefachkräften hingegen die Möglichkeit, sich dem zunehmenden Druck des Arbeitsalltags geprägt von Fachkräftemangel als individuelle (Teil-)Exitstrategie zu entziehen und gleichzeitig passende Rahmenbedingungen für den Einsatz mit den Zeitarbeitsagenturen auszuhandeln. Durch die Pflegepersonaluntergrenzen-Verordnung sind Pflegeeinrichtungen gesetzlich verpflichtet, Fachkraftquoten trotz Fachkräftemangel einzuhalten, was den Zeitarbeitskräften entsprechende Verhandlungsmacht verleiht. Anhand empirischer Daten wird beleuchtet, wie Zeitarbeit aus der Perspektive der Einrichtungsleitungen und des Stammpersonals eingeordnet und aus welchen Gründen sie von Beschäftigten gewählt wird. Zudem wird der Frage nachgegangen, welche Bedeutung diese Entwicklung für die Pflegebranche insgesamt haben kann.
Durch die Reduzierung der Wertschöpfungstiefe in vielen Unternehmen nehmen die Herausforderungen an das Qua-litätsmanagement in der Lieferkette stetig zu. Der Zuwachs an nationalen, aber auch internationalen Lieferanten lässt auch die Anzahl der Auditierungen, die notwendig sind, um diese Lieferanten zu qualifizieren und zu entwickeln, stetig steigen. In diesem Zusammenhang müssen Lösungs-ansätze entwickelt werden, um die notwendigen Ressour-cen optimal zu nutzen und die entstehenden Kosten mög-lichst gering zu halten. Obwohl der Begriff Audit auf audire, hören, zurückzuführen ist, ist das Sehen aber für uns Menschen von Zentraler Bedeutung. Mit heutiger Tech-nologie kann es, auch im Audit, aus der Distanz erfolgen. Dabei gilt es, einige technische, organisatorische und sozi-ale Voraussetzungen zu beachten.
Der Beitrag skizziert einleitend grundlegende Defizite in Lerneinheiten der Automatisierungstechnik. Als Lösungskonzept werden Digitale Zwillinge der Maschinen vorgeschlagen, die mit realer Steuerungsalgorithmik und AR/VR kombiniert werden. Die informationstechnische Umsetzung dieses Konzepts in der `Digital Twin as a Service ́ Plattform ermöglicht die Entwicklung und Bereitstellung von AR/VR-Lernszenarien. Auf Basis der technologischen Beschreibung werden vier Lernszenarien aus der Robotik aufgezeigt, die bereits in der beruflichen Bildung, der Hochschulbildung und der industriellen Bildung erfolgreich eingesetzt werden. Am Beispiel eines ausgewählten Lernszenarios werden die Lernziele und das didaktische Design detailliert betrachtet. Abschließend wird auf die Evaluierung eingegangen. Ergänzend zu diesem schriftlichen Beitrag ist unter https://www.virtual-automation-lab.de/avril2020 ein Kurzvideo über das Lösungskonzept, die Software-Plattform sowie die Lernszenarien abrufbar.
Die Diplompädagogin und Kinder- und Jugendpsychotherapeutin Katrin Boger arbei-tet seit 2010 in eigener Praxis in Aalen und hat eine eigene Methode der Traumaarbeit mit Säuglingen, Kleinkindern und Vorschul-kindern entwickelt (die Integrative Bindungs-orientierte Traumaarbeit I.B.T.). In den letzten Jahren behandelte sie immer mehr Säuglinge und Kleinkinder in ihrer Praxis, die stress-reiche Ereignisse erlebt hatten, unter denen sie noch immer zu leiden schienen. Die Ereignisse erstreckten sich von einer kom-plizierten Geburt, über Frühgeburten, frühe Erkrankungen, Unfälle und Operationen u.v.m., wodurch sie sich mehr und mehr auf diese Zielgruppe spezialisiert hat. Auch der Facharzt für Kinder- und Jugendpsychiatrie und -psychotherapie Steffen Bambach hat eine eigene Praxis in Eisenach, in der er eine psychotherapeutische Behandlung für trau-matisierte Patient*innen und ihre Familien anbietet. In den letzten Jahren hat er sich ebenfalls auf Traumatisierungen durch medizinisch notwendige Eingriffe spezialisiert. Im Interview berichten die beiden von ihren Erfahrungen und ihrem sehr ähnlichen thera-peutischen Ansatz in der Arbeit mit den trau-matisierten Kindern und ihren Eltern.
Lasst uns nicht alleine!
(2020)
In einer Serie von Artikeln stellen wir im IGA-Boten die Ergebnisse eines koope-rativen Forschungsprojektes der IGA e.V. mit der Hochschule Esslingen vor – hier liegt nun der dritte Teil vor. In den letzten IGA-Boten (siehe Nr. 55 und 56) wurden zunächst die Belastungen und die potentiell traumatisierenden Situationen sowie mögliche daraus entstandene Folgen in den Blick genommen. In dieser Ausgabe soll es nun um einen ganz wichtigen Faktor gehen, der mit darüber bestimmt, wie eine belastende Situation erlebt wird und ob sie im Nachhinein verarbeitet werden kann: die soziale Unterstützung. Oder mit den Worten von Eckart von Hirschhau-sen, Arzt, Wissenschaftsjournalist und Fernsehmoderator (2020: 11): „Manchmal braucht es nur jemanden, der dich einfach in den Arm nimmt und pustet! [...] Wis-sen ohne Zuwendung bleibt kalt. Und Zuwendung ohne Wissen bleibt manchmal unter unseren Möglichkeiten.“ Daher wollen wir uns im Folgenden mit beidem beschäftigen.
In einer Serie von Artikeln stellen wir im IGA Boten die Ergebnisse einer kleinen Studie vor – hier liegt nun der zweite Teil vor Ihnen. Im letzten IGA Boten (siehe Nr. 55) wurden zunächst die Belastungen und potentiell traumatisierenden Situationen in den Blick genommen. In dieser Ausgabe sollen nun die Folgen, die aus den Erfahrungen entstanden sind, beschrieben werden. Warum ist das ein so wichtiges Thema für die Interessengemeinschaft Arthrogryposis? Andreas Krüger, ein Facharzt für Kinderund Jugendpsychiatrie und Psychotherapie beschreibt in seinem Buch „Erste Hilfe für traumatisierte Kinder“ (2017) sehr klar, wie wichtig diese Erkenntnisse für Familien sind und stellt die Frage, warum ein gewisses Grundwissen über eine medizinische Notfallversorgung eine Selbstverständlichkeit ist, während wir so wenig über den »psychischen Notfall« und dessen Versorgung wissen.
The root area of a wind turbine rotor is usually constructed by very thick airfoils with a relative thickness of more than 35%. An airfoil at that thickness is characterized with strong flow separation. To solve this issue, vortex generators can be used as an active control in order to stabilize the airflow and improve the aerodynamic performance, consequently. Boundary layer control however, investigated employing numerical techniques, strongly depend on the employed method as well as the mesh especially due to a weak vortex conservation in the RANS model. Using the method of Delayed detached eddy simulation (DDES) the solution can benefit from effort-efficient boundary layer modeling as well as LES vortex resolving apart from the surface. The present studies aims to investigate suitable numerical approach mesh dependencies in comparison to experimental data, for application to thick airfoil in future studies.
Application and machine learning methods for dynamic load point controls of electric vehicles (xEVs)
(2020)
From the customer's perspective, the appeal of electric vehicles depends on the simplicity and ease of their use, such as flexible access to electric power from the grid to recharge the batteries of their vehicles. Therefore, the expansion of charging infrastructure will be an important part of electric mobility. The related charging infrastructure is a big challenge for the load capacity of the grid connection without additional intelligent charge management: if the control of the charging process is not implemented, it is necessary to ensure the total of the maximum output of all xEVs at the grid connection point, which requires huge costs. This paper proposes to build a prediction module for forecasting dynamic charging load using machine learning (ML) techniques. The module will be integrated into a real charge management concept with optimization procedures for controlling the dynamic load point. The value of load forecasting through practical load data of a car park were taken to illustrate the proposed methods. The prediction performance of different ML methods under the same data condition (e.g., holiday data) are compared and evaluated.
Recently the production of electric cars is increasing worldwide. The main target is to lower the greenhouse gas emissions. Even if an electrified vehicle is locally emission-free the manufacturing of lithium ion batteries are producing significant amounts of CO2. In order to decrease the air pollution governments are considering recycling programs to extend battery life and usage of important raw materials. A new approach to recover LiNixMnyCozO2 (NMC) particles while saving the chemical and morphological properties using water was presented by Tim Sieber et al. [1]. With the presented study, we are focusing on the analysis of the effects on the Global Warming Potential (GWP) for the water based recycling process based on a reuse of NMC material in new batteries.
It is possible to reduce the ecological damage of the manufacturing process of Li-Ion battery cells even with little amounts of recovered cathode material that is used for the production of new battery cells. Based on the suggestion that 95% of the NMC cathode material can be recovered by the hydrometallurgical recovery and the reuse of 10% within the production of new batteries a reduction of the GWP by 7% ,can be identified for the cathode materials. For other impact categories such as Acidification Potential (AP), Eutrophication Potential (EP), and Photochemical Ozone Creation Potential (POCP), savings of 10%, 11%, and 8 % can be achieved respectively.
The studied water based recycling process can be quoted as environment-friendly and leads to a reduction of all impact categories by a re-use of 10% recovered NMC material. Based on this knowledge an additional recycling on substance level is recommended.
Menschen wachsen lassen!
(2020)
The large gap in political participation between well-educated and wealthy citizens on the one hand and less educated and poorer citizens, on the other hand, has in recent years gained new attention. Several authors argue that unequal participation leads to unequal political representation and responsiveness and results in policy decisions that are tilted against the interests of disadvantaged groups, thus further increasing inequality. This paper takes a different starting point by turning the old question why people do not participate in politics around and asking why people participate. We hypothesize that enduring engagement with politics requires individuals to be resilient in the face of frustration and to possess strong, perhaps even delusional, efficacy beliefs. Using data from the German GESIS Panel we demonstrate positive correlations between individual resilience, internal and external efficacy, and political participation. We conclude by pointing to the possibility that resilience and efficacy beliefs help privileged groups to overcome collective action problems to achieve disproportionate influence on political decisions and point to avenues for further research.
Deep learning approaches can uncover complex patterns in data. In particular, variational autoencoders (VAEs) achieve this by a non-linear mapping of data into a low-dimensional latent space. Motivated by an application to psychological resilience in the Mainz Resilience Project (MARP), which features intermittent longitudinal measurements of stressors and mental health, we propose an approach for individualized, dynamic modeling in this latent space. Specifically, we utilize ordinary differential equations (ODEs) and develop a novel technique for obtaining person-specific ODE parameters even in settings with a rather small number of individuals and observations, incomplete data, and a differing number of observations per individual. This technique allows us to subsequently investigate individual reactions to stimuli, such as the mental health impact of stressors. A potentially large number of baseline characteristics can then be linked to this individual response by regularized regression, e.g., for identifying resilience factors. Thus, our new method provides a way of connecting different kinds of complex longitudinal and baseline measures via individualized, dynamic models. The promising results obtained in the exemplary resilience application indicate that our proposal for dynamic deep learning might also be more generally useful for other application domains.
Resilience is the maintenance and/or quick recovery of mental health during and after periods of adversity. It is conceptualized to result from a dynamic process of successful adaptation to stressors. Up to now, a large number of resilience factors have been proposed, but the mechanisms underlying resilience are not yet understood. To shed light on the complex and time-varying processes of resilience that lead to a positive long-term outcome in the face of adversity, the Longitudinal Resilience Assessment (LORA) study has been established. In this study, 1191 healthy participants are followed up at 3- and 18-month intervals over a course of 4.5 years at two study centers in Germany. Baseline and 18-month visits entail multimodal phenotyping, including the assessment of mental health status, sociodemographic and lifestyle variables, resilience factors, life history, neuropsychological assessments (of proposed resilience mechanisms), and biomaterials (blood for genetic and epigenetic, stool for microbiome, and hair for cortisol analysis). At 3-monthly online assessments, subjects are monitored for subsequent exposure to stressors as well as mental health measures, which allows for a quantitative assessment of stressor-dependent changes in mental health as the main outcome. Descriptive analyses of mental health, number of stressors including major life events, daily hassles, perceived stress, and the ability to recover from stress are here presented for the baseline sample. The LORA study is unique in its design and will pave the way for a better understanding of resilience mechanisms in humans and for further development of interventions to successfully prevent stress-related disorder.
The occurrence of daily hassles is associated with increased subsequent levels of negative affect. Neuroticism has been found to exacerbate this effect. So far, most research used single‐item measures for the assessment of daily hassles or relied on daily diary studies. This study aimed to examine the interrelations of daily hassles, negative affect reactivity, and neuroticism in daily life employing an extensive inventory of daily hassles. Seventy participants (18–30 years; M = 23.9 years, 59% female) completed a 4‐week smartphone‐based ecological momentary assessment study reporting the occurrence and perceived strain of daily hassles as well as negative affect at five semi‐random signals between 9 a.m. and 8 p.m. Multilevel analyses revealed significant associations between elevated levels of negative affect and higher cumulative daily hassle strain ratings per signal in concurrent and time‐lagged analyses. Contrary to our expectations, there was no moderation by neuroticism on these associations. The results suggest that daily hassles can accumulate in their impact on mood in daily life and exert a prolonged effect on negative affect. The absence of a significant moderation by neuroticism may be interpreted in the light of methodological specifics of this study.
Background: Few data are available on the characteristics of inpatient treatment and subsequent outpatient treatment for depression in Germany. In this study, we aimed to characterize the inpatient and outpatient treatment phases, to determine the rates of readmission and mortality, and to identify risk factors.
Methods: We carried out a descriptive statistical analysis of routine administrative data from a large health-insurance carrier (BARMER). All insurees aged 18 to 65 who were treated in 2015 as inpatients on a psychiatry and psychotherapy service or on a psychosomatic medicine and psychotherapy service with a main diagnosis of depression were included in the analysis. Risk factors for readmission and death were determined with the aid of mixed logistic regression.
Results: Of the 22 893 patients whose data were analyzed, 78% had been hospitalized on a psychiatry and psychotherapy service and 22% on a psychosomatic medicine and psychotherapy service. The median length of hospital stay was 42 days. Follow-up care in the outpatient setting failed to conform with the recommendations of the pertinent guidelines in 92% of the patients with a main diagnosis of severe depression during hospitalization, and in 50% of those with moderate depression. 21% of the patients were readmitted within a year. The mortality at one year was 961 per 100 000 individuals (adjusted for the age and sex structure of the German population), or 3.4 times the mortality of the population at large. In the regression model, more treatment units during hospitalization and subsequent treatment with psychotherapy were associated with a lower probability of readmission, while longer hospitalization with subsequent pharmacotherapy or psychotherapy was associated with lower mortality.
Conclusion: The recommendations of the national (German) S3 guidelines for the further care of patients who have been hospitalized for depression are inadequately implemented at present in the sectored structures of in- and outpatient care in the German health care system. This patient group has marked excess mortality.
Background: Many existing scales for microstressor assessment do not differentiate between objective (ie, observable) stressor events and stressful cognitions or concerns. They often mix items assessing objective stressor events with items measuring other aspects of stress, such as perceived stressor severity, the evoked stress reaction, or further consequences on health, which may result in spurious associations in studies that include other questionnaires that measure such constructs. Most scales were developed several decades ago; therefore, modern life stressors may not be represented. Ecological momentary assessment (EMA) allows for sampling of current behaviors and experiences in real time and in the natural habitat, thereby maximizing the generalization of the findings to real-life situations (ie, ecological validity) and minimizing recall bias. However, it has not been used for the validation of microstressor questionnaires so far.
Objective: The aim is to develop a questionnaire that (1) allows for retrospective assessment of microstressors over one week, (2) focuses on objective (ie, observable) microstressors, (3) includes stressors of modern life, and (4) separates stressor occurrence from perceived stressor severity.
Methods: Cross-sectional (N=108) and longitudinal studies (N=10 and N=70) were conducted to evaluate the Mainz Inventory of Microstressors (MIMIS). In the longitudinal studies, EMA was used to compare stressor data, which was collected five times per day for 7 or 30 days with retrospective reports (end-of-day, end-of-week). Pearson correlations and multilevel modeling were used in the analyses.
Results: High correlations were found between end-of-week, end-of-day, and EMA data for microstressor occurrence (counts) (r≥.69 for comparisons per week, r≥.83 for cumulated data) and for mean perceived microstressor severity (r≥.74 for comparisons per week, r≥.85 for cumulated data). The end-of-week questionnaire predicted the EMA assessments sufficiently (counts: beta=.03, 95% CI .02-.03, P<.001; severity: beta=.73, 95% CI .59-.88, P<.001) and the association did not change significantly over four subsequent weeks.
Conclusions: Our results provide evidence for the ecological validity of the MIMIS questionnaire.
Keywords: daily hassles; ecological momentary assessment; microstressor; validation.
Background
Resilience can be defined as maintaining or regaining mental health during or after significant adversities such as a potentially traumatising event, challenging life circumstances, a critical life transition or physical illness. Healthcare students, such as medical, nursing, psychology and social work students, are exposed to various study‐ and work‐related stressors, the latter particularly during later phases of health professional education. They are at increased risk of developing symptoms of burnout or mental disorders. This population may benefit from resilience‐promoting training programmes.
Objectives:
To assess the effects of interventions to foster resilience in healthcare students, that is, students in training for health professions delivering direct medical care (e.g. medical, nursing, midwifery or paramedic students), and those in training for allied health professions, as distinct from medical care (e.g. psychology, physical therapy or social work students).
Search methods:
We searched CENTRAL, MEDLINE, Embase, 11 other databases and three trial registries from 1990 to June 2019. We checked reference lists and contacted researchers in the field. We updated this search in four key databases in June 2020, but we have not yet incorporated these results.
Selection criteria:
Randomised controlled trials (RCTs) comparing any form of psychological intervention to foster resilience, hardiness or post‐traumatic growth versus no intervention, waiting list, usual care, and active or attention control, in adults (18 years and older), who are healthcare students. Primary outcomes were resilience, anxiety, depression, stress or stress perception, and well‐being or quality of life. Secondary outcomes were resilience factors.
Data collection and analysis:
Two review authors independently selected studies, extracted data, assessed risks of bias, and rated the certainty of the evidence using the GRADE approach (at post‐test only).
Main results:
We included 30 RCTs, of which 24 were set in high‐income countries and six in (upper‐ to lower‐) middle‐income countries. Twenty‐two studies focused solely on healthcare students (1315 participants; number randomised not specified for two studies), including both students in health professions delivering direct medical care and those in allied health professions, such as psychology and physical therapy. Half of the studies were conducted in a university or school setting, including nursing/midwifery students or medical students. Eight studies investigated mixed samples (1365 participants), with healthcare students and participants outside of a health professional study field.
Participants mainly included women (63.3% to 67.3% in mixed samples) from young adulthood (mean age range, if reported: 19.5 to 26.83 years; 19.35 to 38.14 years in mixed samples). Seventeen of the studies investigated group interventions of high training intensity (11 studies; > 12 hours/sessions), that were delivered face‐to‐face (17 studies). Of the included studies, eight compared a resilience training based on mindfulness versus unspecific comparators (e.g. wait‐list).
The studies were funded by different sources (e.g. universities, foundations), or a combination of various sources (four studies). Seven studies did not specify a potential funder, and three studies received no funding support.
Risk of bias was high or unclear, with main flaws in performance, detection, attrition and reporting bias domains.
At post‐intervention, very‐low certainty evidence indicated that, compared to controls, healthcare students receiving resilience training may report higher levels of resilience (standardised mean difference (SMD) 0.43, 95% confidence interval (CI) 0.07 to 0.78; 9 studies, 561 participants), lower levels of anxiety (SMD −0.45, 95% CI −0.84 to −0.06; 7 studies, 362 participants), and lower levels of stress or stress perception (SMD −0.28, 95% CI −0.48 to −0.09; 7 studies, 420 participants). Effect sizes varied between small and moderate. There was little or no evidence of any effect of resilience training on depression (SMD −0.20, 95% CI −0.52 to 0.11; 6 studies, 332 participants; very‐low certainty evidence) or well‐being or quality of life (SMD 0.15, 95% CI −0.14 to 0.43; 4 studies, 251 participants; very‐low certainty evidence).
Adverse effects were measured in four studies, but data were only reported for three of them. None of the three studies reported any adverse events occurring during the study (very‐low certainty of evidence).
Authors' conclusions:
For healthcare students, there is very‐low certainty evidence for the effect of resilience training on resilience, anxiety, and stress or stress perception at post‐intervention.
The heterogeneous interventions, the paucity of short‐, medium‐ or long‐term data, and the geographical distribution restricted to high‐income countries limit the generalisability of results. Conclusions should therefore be drawn cautiously. Since the findings suggest positive effects of resilience training for healthcare students with very‐low certainty evidence, high‐quality replications and improved study designs (e.g. a consensus on the definition of resilience, the assessment of individual stressor exposure, more attention controls, and longer follow‐up periods) are clearly needed.
Background
Resilience can be defined as the maintenance or quick recovery of mental health during or after periods of stressor exposure, which may result from a potentially traumatising event, challenging life circumstances, a critical life transition phase, or physical illness. Healthcare professionals, such as nurses, physicians, psychologists and social workers, are exposed to various work‐related stressors (e.g. patient care, time pressure, administration) and are at increased risk of developing mental disorders. This population may benefit from resilience‐promoting training programmes.
Objectives:
To assess the effects of interventions to foster resilience in healthcare professionals, that is, healthcare staff delivering direct medical care (e.g. nurses, physicians, hospital personnel) and allied healthcare staff (e.g. social workers, psychologists).
Search methods:
We searched CENTRAL, MEDLINE, Embase, 11 other databases and three trial registries from 1990 to June 2019. We checked reference lists and contacted researchers in the field. We updated this search in four key databases in June 2020, but we have not yet incorporated these results.
Selection criteria:
Randomised controlled trials (RCTs) in adults aged 18 years and older who are employed as healthcare professionals, comparing any form of psychological intervention to foster resilience, hardiness or post‐traumatic growth versus no intervention, wait‐list, usual care, active or attention control. Primary outcomes were resilience, anxiety, depression, stress or stress perception and well‐being or quality of life. Secondary outcomes were resilience factors.
Data collection and analysis:
Two review authors independently selected studies, extracted data, assessed risks of bias, and rated the certainty of the evidence using the GRADE approach (at post‐test only).
Main results:
We included 44 RCTs (high‐income countries: 36). Thirty‐nine studies solely focused on healthcare professionals (6892 participants), including both healthcare staff delivering direct medical care and allied healthcare staff. Four studies investigated mixed samples (1000 participants) with healthcare professionals and participants working outside of the healthcare sector, and one study evaluated training for emergency personnel in general population volunteers (82 participants). The included studies were mainly conducted in a hospital setting and included physicians, nurses and different hospital personnel (37/44 studies).
Participants mainly included women (68%) from young to middle adulthood (mean age range: 27 to 52.4 years). Most studies investigated group interventions (30 studies) of high training intensity (18 studies; > 12 hours/sessions), that were delivered face‐to‐face (29 studies). Of the included studies, 19 compared a resilience training based on combined theoretical foundation (e.g. mindfulness and cognitive‐behavioural therapy) versus unspecific comparators (e.g. wait‐list). The studies were funded by different sources (e.g. hospitals, universities), or a combination of different sources. Fifteen studies did not specify the source of their funding, and one study received no funding support.
Risk of bias was high or unclear for most studies in performance, detection, and attrition bias domains.
At post‐intervention, very‐low certainty evidence indicated that, compared to controls, healthcare professionals receiving resilience training may report higher levels of resilience (standardised mean difference (SMD) 0.45, 95% confidence interval (CI) 0.25 to 0.65; 12 studies, 690 participants), lower levels of depression (SMD −0.29, 95% CI −0.50 to −0.09; 14 studies, 788 participants), and lower levels of stress or stress perception (SMD −0.61, 95% CI −1.07 to −0.15; 17 studies, 997 participants). There was little or no evidence of any effect of resilience training on anxiety (SMD −0.06, 95% CI −0.35 to 0.23; 5 studies, 231 participants; very‐low certainty evidence) or well‐being or quality of life (SMD 0.14, 95% CI −0.01 to 0.30; 13 studies, 1494 participants; very‐low certainty evidence). Effect sizes were small except for resilience and stress reduction (moderate). Data on adverse effects were available for three studies, with none reporting any adverse effects occurring during the study (very‐low certainty evidence).
Authors' conclusions:
For healthcare professionals, there is very‐low certainty evidence that, compared to control, resilience training may result in higher levels of resilience, lower levels of depression, stress or stress perception, and higher levels of certain resilience factors at post‐intervention.
The paucity of medium‐ or long‐term data, heterogeneous interventions and restricted geographical distribution limit the generalisability of our results. Conclusions should therefore be drawn cautiously. The findings suggest positive effects of resilience training for healthcare professionals, but the evidence is very uncertain. There is a clear need for high‐quality replications and improved study designs.
One-dimensional objects as nanowires have been proven to be building blocks in novel applications due to their unique functionalities. In the realm of magnetic materials, iron-oxides form an important class by providing potential solutions in catalysis, magnetic devices, drug delivery, or in the field of sensors. The accurate composition and spatial structure analysis are crucial to describe the mechanical aspects and optimize strategies for the design of multi-component NWs. Atom probe tomography offers a unique analytic characterization tool to map the (re-)distribution of the constituents leading to a deeper insight into NW growth, thermally-assisted kinetics, and related mechanisms. As NW-based devices critically rely on the mechanical properties of NWs, the appropriate mechanical modeling with the resulting material constants is also highly demanded and can open novel ways to potential applications. Here, we report a compositional and structural study of quasi-ceramic one-dimensional objects: α-Fe ⊕ α-FeOOH(goethite) ⊕ Pt and α-Fe ⊕ α-Fe3O4(magnetite) ⊕ Pt core–shell NWs. We provide a theoretical model for the elastic behavior with terms accounting for the geometrical and mechanical nonlinearity, prior and subsequent to thermal treatment. The as-deposited system with a homogeneous distribution of the constituents demonstrates strikingly different structural and elastic features than that of after annealing, as observed by applying atom probe tomography, energy-dispersive spectroscopy, analytic electron microscopy, and a micromanipulator nanoprobe system. During annealing at a temperature of 350 °C for 20 h, (i) compositional partitioning between phases (α-Fe, α-Fe3O4 and in a minority of α-Fe2O3) in diffusional solid–solid phase transformations takes place, (ii) a distinct newly-formed shell formation develops, (iii) the degree of crystallinity increases and (iv) nanosized precipitation of evolving phases is detected leading to a considerable change in the description of the elastic material properties. The as-deposited nanowires already exhibit a significantly large maximum strain (1–8%) and stress (3–13 GPa) in moderately large bending tests, which become even more enhanced after the annealing treatment resulting at a maximum of about 2.5–10.5% and 6–18 GPa, respectively. As a constitutive parameter, the strain-dependent stretch modulus undoubtedly represents changes in the material properties as the deformation progresses.
The theories of multi-criteria decision-making (MCDM) and fuzzy logic both aim to model human thinking. In MCDM, aggregation processes and preference modeling play the central role. This paper suggests a consistent framework for modeling human thinking by using the tools of both fields: fuzzy logical operators as well as aggregation and preference operators. In this framework, aggregation, preference, and the logical operators are described by the same unary generator function. Similarly to the implication being defined as a composition of the disjunction and the negation operator, preference operators were introduced as a composition of the aggregative operator and the negation operator. After a profound examination of the main properties of the preference operator, our main goal is the implementation into neural networks. We show how preference can be modeled by a perceptron, and illustrate the results in practical neural applications.
Interpretable neural networks based on continuous-valued logic and multicriteria decision operators
(2020)
Combining neural networks with continuous logic and multicriteria decision-making tools can reduce the black-box nature of neural models. In this study, we show that nilpotent logical systems offer an appropriate mathematical framework for hybridization of continuous nilpotent logic and neural models, helping to improve the interpretability and safety of machine learning. In our concept, perceptrons model soft inequalities; namely membership functions and continuous logical operators. We design the network architecture before training, using continuous logical operators and multicriteria decision tools with given weights working in the hidden layers. Designing the structure appropriately leads to a drastic reduction in the number of parameters to be learned. The theoretical basis offers a straightforward choice of activation functions (the cutting function or its differentiable approximation, the squashing function), and also suggests an explanation to the great success of the rectified linear unit (ReLU). In this study, we focus on the architecture of a hybrid model and introduce the building blocks for future applications in deep neural networks.
The current study describes analyses of the WINSENT wind energy test sitelocated in complex terrain in Southern Germany by highly resolved numerical simulations.The resolved atmospheric turbulence is simulated with Delayed Detached Eddy Simulations bythe flow solver FLOWer without consideration of the research wind turbines.The mean inflow and wind direction of the analysed time period is provided by precursorsimulations of project partners. The simulation model chain consists of three codes with differenttime scales and resolutions. The model chain provides a data transfer from mesoscale WRFsimulations to OpenFOAM. As a next step OpenFOAM provides inflow data in the valleyof the terrain site for the present FLOWer simulations, the code with the highest resolutionin space and time. The mean velocity field provided by OpenFOAM is superimposed withfluctuations that are based on measurements to obtain the small turbulent scales within theFLOWer simulations, which the previous tools of the model chain can not resolve.Comparisons with the two already installed met masts clarify that the current FLOWersimulations provide an adequate agreement with measured data. The results are verified withthe application of a second simulation, in which a homogeneous velocity profile is superimposedwith turbulence. Thus, comparisons with measured data showed that the benefit of using theinflow data of this model chain is especially evident near the ground.
In this paper, new automated processes for applying the commercial Computational Fluid Dynamics (CFD) tools ANSYS Fluent and ANSYS CFX to wind modelling in complex terrain are developed with the goal of decreasing the Actual Total Costs (ATC) related to planning wind energy projects. Simulations are carried out at the complex terrain site Stotten in southern Germany using ANSYS Fluent and ANSYS CFX, and the ATCs related to the simulations estimated. The simulation set-up and post-processing effort are identified as having the highest effect on the ATC, and therefore the automated processes focus on reducing the effort of these tasks. Simulations of the same test site are carried out with the new automated processes, and compared to the manual processes as well as to an industry-standard tool, WindSim. The new automated tools are found to reduce the ATC of this case by a factor of 12 for Fluent and seven for CFX, to approximately half the value of WindSim. All three simulations show similar deviations compared to measurements and therefore these results are comparable. It should be noted that these results are highly specific to this case, and the absolute cost-saving values cannot be directly transferred to other cases. Nevertheless, it can be concluded that these new processes have significantly reduced the Actual Total Cost and are likely to have a large effect on the choice of the most cost-effective model for a given wind energy project. On-going work involves quantifying the effect of these cost savings on the choice of most app
Micrometeorological observations from a tower, an eddy-covariance (EC) station and an unmanned aircraft system (UAS) at the WINSENT test-site are used to validate a computational fluid dynamics (CFD) model, driven by a mesoscale model. The observation site is characterised by a forested escarpment in a complex terrain. A two-day measurement campaign with a flow almost perpendicular to the escarpment is analysed. The first day is dominated by high wind speeds, while, on the second one, calm wind conditions are present. Despite some minor differences, the flow structure, analysed in terms of horizontal wind speeds, wind direction and inclination angles shows similarities for both days. A real-time strategy is used for the CFD validation with the UAS measurement, where the model follows spatially and temporally the aircraft. This strategy has proved to be successful. Stability indices such as the potential temperature and the bulk Richardson number are calculated to diagnose atmospheric boundary layer (ABL) characteristics up to the highest flight level. The calculated bulk Richardson values indicate a dynamically unstable region behind the escarpment and near the ground for both days. At higher altitudes, the ABL is returning to a near neutral state. The same characteristics are found in the model but only for the first day. The second day, where shear instabilities are more dominant, is not well simulated. UAS proves its great value for sensing the flow over complex terrains at high altitudes and we demonstrate the usefulness of UAS for validating and improving models.
This document specifies a YANG model for TCP on devices that are configured by network management protocols. The YANG model defines a container for all TCP connections and groupings of some of the parameters that can be imported and used in TCP implementations or by other models that need to configure TCP parameters. The model includes definitions from YANG Groupings for TCP Client and TCP Servers (I-D.ietf-netconf-tcp-client-server). The model is NMDA (RFC
8342) compliant.
This document defines three YANG 1.1 [RFC7950] modules to support the configuration of TCP clients and TCP servers, either as standalone or in conjunction with a stack protocol layer specific configuration.
TCP Usage Guidance in the Internet of Things (IoT), draft-ietf-lwig-tcp-constrained-node-networks-13
(2020)
This document provides guidance on how to implement and use the Transmission Control Protocol (TCP) in Constrained-Node Networks(CNNs), which are a characteristic of the Internet of Things (IoT).Such environments require a lightweight TCP implementation and may not make use of optional functionality. This document explains a number of known and deployed techniques to simplify a TCP stack as well as corresponding tradeoffs. The objective is to help embedded
developers with decisions on which TCP features to use.
A number of planetary boundaries, including climate change as a result of greenhouse gas emissions, has already been exceeded. This situation has deleterious consequences for public health. Paradoxically, 4.4% of these emissions are attributable to the healthcare sector. These problems have not been sufficiently acknowledged in health professions curricula. This paper addresses two main issues, humanistic learning and the application of knowledge acquisition to clinical practice. Humanistic learning principles can be used to emphasize learner-centered approaches, including knowledge acquisition and reflection to increase self-awareness. Applying humanistic principles in everyday life and clinical practice can encourage stewardship, assisting students to become agents for change. In terms of knowledge and skills application to clinical practice, an overview of varied and novel approaches of how sustainable education can be integrated at different stages of training across several health care professions is provided. The Health and Environment Adaptive Response Taskforce (HEART) platform as an example of creating empowered learners, the NurSusTOOLKIT, a multi-disciplinary collaboration offering free adaptable educational resources for educators and the Greener Anaesthesia and Sustainability Project (GASP), an example of bridging the transition to clinical practice, are described.
Negotiations are a relevant and highly complex business skill. Therefore, extensive training is required to become a good negotiator. Such training is offered by universities for their students and by companies for their employees. The present paper designs gamified feedback features in electronic negotiation training and evaluates their potential and their effects. Following a design science research method, feedback mechanisms in electronic negotiation training are derived from literature. An assessment regarding their relevance for e-negotiation training shows a preparation quiz, set and track goals and expert reviews to be the most useful gamified feedback mechanisms. Dedicated mock-ups implementing these feedback mechanisms are designed and evaluated in semi-structured interviews showing their capability to improve relevant negotiation skills, as well as motivation and competence of the learners. Out of the three mock-ups, the interviewees prefer the feedback mechanisms “expert review” and “set and track goals”; both mechanisms provide a competence-confirming learning experience and an autonomous learning experience.
Coverage Probability of Methods for Steady-State Availability Inference with a Confidence Interval
(2020)
The quality of a repairable system can be described using its availability. Typically, a high degree of availability is demanded by the customer. To analyze the availability of a repairable system, the specification of reliability and maintainability are needed. Usually, they are demonstrated based on limited sample sizes, e.g., by analyzing the failure times of a life time test. The evaluation of the test results yields a mean-value distribution of reliability and maintainability as well as its confidence interval. Consequently, the calculated availability based on these inputs also need to be expressed including a confidence interval.
In this paper, firstly several approaches to calculate the confidence interval of steady-state availability based on reliability and maintainability are presented. Afterwards, a procedure to investigate and evaluate the quality and accuracy of the confidence intervals calculated with the presented methods is shown. Therefore, the coverage probability as the most common indicator is used. Based on an exemplary parameter study which is performed, the accuracy of the confidence intervals determined with the methods is investigated and evaluated in the case of exponentially distributed failure and repair times. Finally, several hints for an effective availability calculation with confidence intervals are given.
Reliability demonstration is performed before a product is released to the market. Often, this demonstration is based on accelerated life testing of samples with limited sample size. Accelerated life testing aims to parameterize a statistical life-stress model. Based on such a model, the reliability demonstration is performed for the stress a product is experiencing during operation. The reliability needs to be inferred with a confidence interval so that the uncertainty, which stems from limited sample data, can be considered. Typically, the load conditions of a field population show a significant variation of stress. A method to consider the comprehensive statistical uncertainty and distribution of stress and life-stress model was recently published. However, this method is limited to applications with constant stress over time. In this paper we present a first approach for a method that is able to consider the distribution of load spectra and statistical lifetime model as well as their uncertainties due to limited sample sizes and allows the consideration of non-constant, i.e. time-varying, stresses for the reliability demonstration. The presented method enables the reliability inference at use condition with confidence interval for cases in which the data consists of accelerated life testing results and a sample of load spectra. The result of an illustrational evaluation is shown and concepts for further extensions of the method are introduced.
This paper focuses on data-driven remaining useful life prediction using ensemble methods for prognostics and health management. An important factor for the performance of an ensemble method is the diversity within the ensemble. An effective neural network ensemble method that emphasizes the generation of diversity is negative correlation learning. It is argued that for both diagnosis and prognosis, the consideration of uncertainties has a substantial added benefit over a simple point estimate. For this reason, a prediction interval is derived for the ensemble method negative correlation learning using the delta method. In the delta method, the neural network is treated as a nonlinear regression model, which is approximated by a Taylor series. A look at the derived formula of the prediction interval, emphasizes that negative correlation learning behaves inversely to a regularization. Furthermore, the formula for a diversity parameter of zero is equal to the prediction interval of the regular multilayer perceptron.
Die Nachfrage nach Dienstleistungen von Beratungsgesellschaften verzeichnet einen kontinuierlichen Anstieg. Vor dem Hintergrund des steigenden Wettbewerbsdrucks müssen sich Dienstleister neue Wege in der Kundenbetreuung, -bindung und -akquirierung suchen. Der Weg zum Erfolg geht über die Qualität. Spitzenleistungen im Wettbewerb können nur erbracht werden, wenn Verbesserungen und Innovationen in allen Bereichen der Organisation erfolgen. Ein nachhaltiger, aktueller und zukünftiger Erfolg stellt sich ein, wenn auf allen betrieblichen Ebenen ein Bewusstsein für hohe und stetige Leistungen geschaffen wird.
Ziel des wissenschaftlichen Projekts ist es, eine Einführung in das Thema des Erfolgsfaktors Dienstleistungsqualität im Management eines Dienstleisters und explizit im Beratungssektor aus verschiedenen Betrachtungsweisen zu geben und den Wettbewerbsvorteil durch Dienstleistungsqualität hervorzuheben.
Anhand des EFQM Modells 2020 wird die Konzeptentwicklung zur Integration eines exzellenten Qualitätsmanagements für Beratungsgesellschaften mithilfe ausgewählter Kriterien aus dem Modell dargestellt. So sollen durch einen Führungsrahmen nachhaltig exzellente Ergebnisse bezüglich strategisch und operativer Leistungen in Anlehnung an die Wahrnehmung der Interessengruppen als Ergebnisse erzielt werden, die den Zweck, die Vision, die Strategie in Einbeziehung der Organisationskultur und Führung, mit Hilfe der eingebundenen Interessensgruppen, unter Schaffung von nachhaltigen Nutzen und unter dem Aspekt von Leistungsfähigkeit und Transformation umsetzen.
In einer dynamischen Geschäftswelt werden alle Organisationen mit kontinuierlichen Veränderungen konfrontiert. Das Streben nach Excellence ist für Organisationen ein Erfolgsfaktor, um sich im zunehmenden Verdrängungswettbewerb zu bewähren. Erfolge in allen Organisationsbereichen können nur erzielt werden, wenn Business Excellence als umfassende Ambition und als ganzheitliches, integratives Konzept von allen Akteuren und Interessengruppen einer Organisation verstanden wird. Das EFQM Modell 2020 für Business Excellence der European Foundation for Quality Management (EFQM) hilft Organisationen ihre Produkt- und Servicequalität zu sichern und ihre zukünftige Entwicklung zu fördern. Das Modell unterstützt die Gefahren im Ecosystem der Organisation zu erkennen und agil, effektiv und effizient damit umzugehen.
Mit dem Einsatz der Software von simcision, wird das EFQM Modell 2020 zur Nutzung in Entwicklungssimulationen abgebildet. Es beinhaltet dabei die von der European Foundation for Quality Management, EFQM, gegebenen Kriterien. Mit dem Modelleinsatz wird der aktuelle Ist-Zustand einer Organisation erfasst. Mit dem System als eine Organisation, mit dem man die jeweilige Organisationsentwicklung simulieren kann, lässt sich ermitteln, welche Maßnahmen ein positives Ergebnis bezogen auf die Excellence erbringen. Grundlage bildet eine allgemeine Version des Modells, das Template. Auf Grundlage des erstellten Template, erfolgt die Erprobung und Simulation an zwei gesonderten Modellen. Die erprobten Unternehmen sind das Industrieunternehmen Lapp Gruppe, Stuttgart und die IT-Beratungsgesellschaft iCONDU GmbH, Ingolstadt. Kennzeichnende Unterlagen zu den Organisationen befinden sich im Anhang. Ganz nach dem Systemgedanken werden die Haupt- und Teilkriterien des EFQM Modells 2020 als Systemelemente mit Beziehungen untereinander eingesetzt.
The growth and sustainability of a manufacturing company extensively relies on customer satisfaction regarding the quality of its products. An exemplary study on the customer quality claim management of an international manufacturing company determined that one major reason for customer dissatisfaction was the inability to prioritize the reported quality problems. Therefore, the company’s focus was set to enhancing the customer claim resolution process by overcoming the challenges in the prioritization process. Considering the various factors which influence the prioritization process, this study provides a solution by using a unique prioritization technique for the management of customer quality claims. It also focuses on the implementation of the derived solution by providing an explicit evaluation method for each of the prioritization factors.