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This study is about estimating the reproducibility of finding palpation points of three different anatomical landmarks in the human body (Xiphoid Process and the 2 Hip Crests) to support a navigated ultrasound application. On 6 test subjects with different body mass index the three palpation points were located five times by two examiners. The deviation from the target position was calculated and correlated to the fat thickness above each palpation point. The reproducibility of the measurements had a mean error of ≈13.5 mm +- 4 mm, which seems to be sufficient for the desired application field.
In der Orthopädie werden Robotersysteme bereits seit mehreren Jahren erfolgreich unterstützend eingesetzt. Dieser Ansatz erfordert die vorgelagerte Erstellung eines digitalen Modells auf Basis von medizinischen Bilddatensätzen. Die Erstellung und Überprüfung der Modelle soll in einer browserbasierten Client- Server-Anwendung erfolgen. Hierfür ist die Darstellung von zweidimensionalen und dreidimensionalen Datensätzen erforderlich. Basis dieses Papers ist die Entwicklung eines Ansatzes zur interaktiven, browserbasierten dreidimensionalen Darstellung medizinischer Planungsdaten. Die Anwendung stellt ein Proof of Concept dar, ob die bestehenden Desktopanwendungen zur Darstellung von Planungsdaten ersetzt werden können. Mit Hilfe des Frameworks AMI.js wurde die Anwendung umgesetzt. Sie erfüllt alle definierten Anforderungen und kann somit die aktuellen Desktopanwendungen ersetzen.
Zur Unterstützung des Operateurs wird eine patientennahe Informationsanzeige entwickelt, die kontextrelevante Informationen entsprechend der aktuellen Situation bereitstellen kann. Hierfür soll eine Situationserkennung konzipiert werden, die auf unterschiedliche intraoperative Prozesse übertragen werden kann. Ziel der adaptiven Situationserkennung ist das Erkennen spezifischer Situationen durch intraoperative Informationen unterschiedlicher Datenquellen im Operationssaal. Innerhalb der Datenerhebung und -analyse wurden Anwendungsfälle für die Situationserkennung definiert sowie chirurgische Prozessmodelle erstellt, die intraoperative Ereignisse abbilden. Auf Basis dieser Informationen wurde ein Konzept entworfen, das sich zunächst auf die Erkennung abstrakter generalisierter Phasen, unabhängig vom Eingriff, fokussiert und sich Schritt für Schritt auf granulare Prozessschritte spezifizieren lässt. Diese Flexibilität soll die Übertragbarkeit des Konzepts auf intraoperative Prozesse ermöglichen und den Operateur dadurch gezielt mit kontextrelevanten Informationen unterstützen. Das Konzept wird in zukünftigen Schritten weiterentwickelt.
Mammographie-Geräte werden in der Diagnostik von Mammakarzinomen eingesetzt. Die ursprüngliche Technik wurde in den letzten Jahren von analogen Röntgenfilmen zu digital integrierten Systemen weiterentwickelt. Durch die Tomosynthese, bei der in einem Schnittbildverfahren mehrere Schichten des Organismus untersucht werden können, können auch überlagerte Strukturen sichtbar gemacht werden. Um als adäquate Grundlage zur Diagnostik von malignen Tumoren dienen zu können, müssen einige qualitative Anforderungen erfüllt werden. Bisher gibt es wenig Literatur, die Anforderungen und den Aufbau solcher Geräte systematisch beschreiben. Im Rahmen dieser Arbeit werden auf Basis der Literatur und bestehender Systeme die qualitativen Anforderungen identifiziert. Der prinzipielle Aufbau solcher Systeme wird anhand der einzelnen Systembausteine in der semiformalen Notationssprache SysML gezeigt. Die grundlegende Funktionsweise eines tomosynthesefähigen Mammographie Gerätes wird in dieser Arbeit zusammenfassend und anhand der einzelnen Systembausteine beschrieben. Diese Arbeit dient der Vermittlung eines umfassenden Verständnisses für die digitale Mammographie, um als Grundlage für die Dokumentation von qualitativen Anforderungen dienen zu können.
Telemetrie und Homemonitoring werden bereits in vielen Gesundheitsbereichen erfolgreich genutzt. Moderne Herzschrittmacher ermöglichen durch telemetrische Datenübertragung das Homemonitoring aktueller Gesundheits- und Zustandsdaten durch PatientInnen und ÄrztInnen. Für die Weiterentwicklung existierender Produkte ist ein grundlegendes Verständnis der Anforderungen an und des Aufbaus solcher Systeme notwendig. Bisher existieren
herstellerunabhängige Betrachtungen dieser noch nicht. Durch die Verwendung von SysML als semiformale Notationssprache wird das System Herzschrittmacher und Homemonitoring modelliert. Die Anforderungen an ein solches System lassen sich aus bestehenden Produkten ableiten. Die vorliegende Arbeit beschreibt die Systemarchitektur solcher Systeme, anhand derer die Anbindung an Informationssysteme über das Homemonitoringsystem und die dadurch umgesetzten Funktionen gezeigt werden.
Private equity (PE) firms are investment firms that acquire equity shares in companies. The goal of PE firms is to exit the investment after few years with a substantial increase in value. PE firms often claim to outperform the market, i.e. to create alpha.
The overall aim of this paper is to unravel the mystery of value creation in the PE industry. First, the author presents a conceptual framework for value creation in the PE industry based on a multiple valuation model that breaks down value creation into different elements. Second, the paper evaluates whether PE firms really create value by analysing and combining results from prior empirical studies based on the conceptual framework.
The results show that existing empirical evidence is mixed but that there is indeed a tendency toward a positive evidence that PE firms create economic value in average. However, there are methodological difficulties in measuring the value creation and studies are often subject to bias. Finally, it is pointed out that the question whether PE firms really create value has to be viewed from different perspectives such as the perspective of the PE firm, the investors and the portfolio companies.
Companies are constantly changing their business process models. In team environments, different versions of a process model are created at the same time. These versions of a process model need to be merged from time to time to consolidate changes and create a new common version.
In this short paper, we propose a solution for modifying a merge result. The goal is to create a meaningful merge result by adding connector nodes to the model at specific locations. This increases the amount of possible result models and reduces additional implementation effort.
While several service-based maintainability metrics have been proposed in the scientific literature, reliable approaches to automatically collect these metrics are lacking. Since static analysis is complicated for decentralized and technologically diverse microservice-based systems, we propose a dynamic approach to calculate such metrics from runtime data via distributed tracing. The approach focuses on simplicity, extensibility, and broad applicability. As a first prototype, we implemented a Java application with a Zipkin integrator, 23 different metrics, and five export formats. We demonstrated the feasibility of the approach by analyzing the runtime data of an example microservice based system. During an exploratory study with six participants, 14 of the 18 services were invoked via the system’s web interface. For these services, all metrics were calculated correctly from the generated traces.
Microservices are a topic driven mainly by practitioners and academia is only starting to investigate them. Hence, there is no clear picture of the usage of Microservices in practice. In this paper, we contribute a qualitative study with insights into industry adoption and implementation of Microservices. Contrary to existing quantitative studies, we conducted interviews to gain a more in-depth understanding of the current state of practice. During 17 interviews with software professionals from 10 companies, we analyzed 14 service-based systems. The interviews focused on applied technologies, Microservices characteristics, and the perceived influence on software quality. We found that companies generally rely on well established technologies for service implementation, communication, and deployment. Most systems, however, did not exhibit a high degree of technological diversity as commonly expected with Microservices. Decentralization and product character were different for systems built for external customers. Applied DevOps practices and automation were still on a mediocre level and only very few companies strictly followed the you build it, you run it principle. The impact of Microservices on software quality was mainly rated as positive. While maintainability received the most positive mentions, some major issues were associated with security. We present a description of each case and summarize the most important findings of companies across different domains and sizes. Researchers may build upon our findings and take them into account when designing industry-focused methods.
While the concepts of object-oriented antipatterns and code smells are prevalent in scientific literature and have been popularized by tools like SonarQube, the research field for service-based antipatterns and bad smells is not as cohesive and organized. The description of these antipatterns is distributed across several publications with no holistic schema or taxonomy. Furthermore, there is currently little synergy between documented antipatterns for the architectural styles SOA and Microservices, even though several antipatterns may hold value for both. We therefore conducted a Systematic Literature Review (SLR) that identified 14 primary studies. 36 service-based antipatterns were extracted from these studies and documented with a holistic data model. We also categorized the antipatterns with a taxonomy and implemented relationships between them. Lastly, we developed a web application for convenient browsing and implemented a GitHub-based repository and workflow for the collaborative evolution of the collection. Researchers and practitioners can use the repository as a reference, for training and education, or for quality assurance.
Background: Design patterns are supposed to improve various quality attributes of software systems. However, there is controversial quantitative evidence of this impact. Especially for younger paradigms such as service- and microservice-based systems, there is a lack of empirical studies.
Objective: In this study, we focused on the effect of four service-based patterns — namely process abstraction, service façade, decomposed capability, and event-driven messaging — on the evolvability of a system from the viewpoint of inexperienced developers.
Method: We conducted a controlled experiment with Bachelor students (N = 69). Two functionally equivalent versions of a service-based web shop — one with patterns (treatment group), one without (control group) — had to be changed and extended in three tasks. We measured evolvability by the effectiveness and efficiency of the participants in these tasks. Additionally, we compared both system versions with nine structural maintainability metrics for size, granularity, complexity, cohesion, and coupling.
Results: Both experiment groups were able to complete a similar number of tasks within the allowed 90 min. Median effectiveness was 1/3. Mean efficiency was 12% higher in the treatment group, but this difference was not statistically significant. Only for the third task, we found statistical support for accepting the alternative hypothesis that the pattern version led to higher efficiency. In the metric analysis, the pattern version had worse measurements for size and granularity while simultaneously having slightly better values for coupling metrics. Complexity and cohesion were not impacted.
Interpretation: For the experiment, our analysis suggests that the difference in efficiency is stronger with more experienced participants and increased from task to task. With respect to the metrics, the patterns introduce additional volume in the system, but also seem to decrease coupling in some areas.
Conclusions: Overall, there was no clear evidence for a decisive positive effect of using service-based patterns, neither for the student experiment nor for the metric analysis. This effect might only be visible in an experiment setting with higher initial effort to understand the system or with more experienced developers.
Software evolvability is an important quality attribute, yet one difficult to grasp. A certain base level of it is allegedly provided by service- and microservice-based systems, but many software professionals lack systematic understanding of the reasons and preconditions for this. We address this issue via the proxy of architectural modifiability tactics. By qualitatively mapping principles and patterns of Service Oriented Architecture (SOA) and microservices onto tactics and analyzing the results, we cannot only generate insights into service-oriented evolution qualities, but can also provide a modifiability comparison of the two popular service-based architectural styles. The results suggest that both SOA and microservices possess several inherent qualities beneficial for software evolution. While both focus strongly on loose coupling and encapsulation, there are also differences in the way they strive for modifiability (e.g. governance vs. evolutionary design). To leverage the insights of this research, however, it is necessary to find practical ways to incorporate the results as guidance into the software development process.
Purpose – Many start-ups are in search of cooperation partners to develop their innovative business models. In response, incumbent firms are introducing increasingly more cooperation systems to engage with startups. However, many of these cooperations end in failure. Although qualitative studies on cooperation models have tried to improve the effectiveness of incumbent start-up strategies, only a few have empirically examined start-up cooperation behavior. The paper aims to discuss these issues.
Design/methodology/approach – Drawing from a series of qualitative and quantitative studies. The scale dimensions are identified on an interview based qualitative study. Following workshops and questionnaire-based studies identify factors and rank them. These ranked factors are then used to build a measurement scale that is integrated in a standardized online questionnaire addressing start-ups. The gathered data are then analyzed using PLS-SEM.
Findings – The research was able to build a multi-item scale for start-ups cooperation behavior. This scale can be used in future research. The paper also provides a causal analysis on the impact of cooperation behavior on start-up performance. The research finds, that the found dimensions are suitable for measuring cooperation behavior. It also shows a minor positive effect on start-up’s performance.
Originality/value – The research fills the gap of lacking empirical research on the cooperation between start-ups and established firms. Also, most past studies focus on organizational structures and their performance when addressing these cooperations. Although past studies identified the start-ups behavior as a relevant factor, no empirical research has been conducted on the topic yet.
A large body of literature is concerned with models of presence— the sensory illusion of being part of a virtual scene— but there is still no general agreement on how to measure it objectively and reliably. For the presented study, we applied contemporary theory to measure presence in virtual reality. Thirty-seven participants explored an existing commercial game in order to complete a collection task. Two startle events were naturally embedded in the game progression to evoke physical reactions and head tracking data was collected in response to these events. Subjective presence was recorded using a post-study questionnaire and real-time assessments. Our novel implementation of behavioral measures lead to insights which could inform future presence research: We propose a measure in which startle reflexes are evoked through specific events in the virtual environment, and head tracking data is compared to the range and speed of baseline interactions.
In recent years, the parallel computing community has shown increasing interest in leveraging cloud resources for executing parallel applications. Clouds exhibit several fundamental features of economic value, like on-demand resource provisioning and a pay-per-use model. Additionally, several cloud providers offer their resources with significant discounts; however, possessing limited availability. Such volatile resources are an auspicious opportunity to reduce the costs arising from computations, thus achieving higher cost efficiency. In this paper, we propose a cost model for quantifying the monetary costs of executing parallel applications in cloud environments, leveraging volatile resources. Using this cost model, one is able to determine a configuration of a cloud-based parallel system that minimizes the total costs of executing an application.
In this paper we describe an interactive web-based visual analysis tool for Formula one races. It first provides an overview about all races on a yearly basis in a calendar-like representation. From this starting point, races can be selected and visually inspected in detail. We support a dynamic race position diagram as well as a more detailed lap times line plot for showing the drivers’ lap times in comparison. Many interaction techniques are supported like selections, filtering, highlighting, color coding, or details-on demand. We illustrate the usefulness of our visualization tool by applying it to a Formula one dataset while we describe the different dynamic visual racing patterns for a number of selected races and drivers.
Data analytics tasks on large datasets are computationally intensive and often demand the compute power of cluster environments. Yet, data cleansing, preparation, dataset characterization and statistics or metrics computation steps are frequent. These are mostly performed ad hoc, in an explorative manner and mandate low response times. But, such steps are I/O intensive and typically very slow due to low data locality, inadequate interfaces and abstractions along the stack. These typically result in prohibitively expensive scans of the full dataset and transformations on interface boundaries.
In this paper, we examine R as analytical tool, managing large persistent datasets in Ceph, a wide-spread cluster file-system. We propose nativeNDP – a framework for Near Data Processing that pushes down primitive R tasks and executes them in-situ, directly within the storage device of a cluster-node. Across a range of data sizes, we show that nativeNDP is more than an order of magnitude faster than other pushdown alternatives.
Ganz gleich, ob im privaten oder beruflichen Alltag, begleiten uns digitale Medien heute nahezu überall. Dabei dienen sie nicht nur zur Unterhaltung, sondern helfen uns, Arbeitsabläufe effizienter und produktiver durchzuführen. Doch die Arbeit des Menschen ist bei Weitem nicht überflüssig geworden. Durch die steigenden Anforderungen ist die Nachfrage nach qualifiziertem Fachpersonal heute höher denn je. Währenddessen müssen Mitarbeiter in der Lage sein, mit der rasanten Entwicklung neuer Produkte und Technologien Schritt zu halten. Dabei ist eine qualitative Aus- und Weiterbildung unumgänglich. Beginnend mit der Bildung von Medienkompetenz in Schulen bis hin zur Fach- und Berufsbildung sowie beruflichen Weiterbildung, muss der Umgang mit digitalen Technologien gelehrt sein. Darüber hinaus bieten diese Technologien neue Potenziale zur Verbesserung von Bildungskonzepten und können zudem dabei helfen, den Lernerfolg zu steigern.
Diese Arbeit beschäftigt sich mit der Evaluation einer VR-basierten Lernumgebung und untersucht mögliche Auswirkungen auf den Lernerfolg durch die verkörperte Darstellung eines virtuellen Instruktors. Dazu wurde die technische Implementierung einer kollaborativen Lernumgebung vorgenommen, mit welcher anschließend eine Versuchsreihe mit 16 Probanden durchgeführt wurde. Im Hinblick auf eine mögliche Steigerung der Effizienz in der eigenständigen Bewältigung von Montageaufgaben nach unterschiedlichen Instruktionsarten, wurden keine signifikanten Leistungsverbesserungen festgestellt.
Type 1 diabetes is a chronic and a life threatening disease: an adjusted treatment and a proper management of the disease are crucial to prevent or delay the complications of diabetes. Although during the last decade the development of the artificial pancreas has presented great advances in diabetes care, the multiple daily injections therapy still represents the most widely used treatment option for type 1 diabetes. This work presents the proposal and first development stages of an application focused on guiding patients using the continuous glucose monitors and smart pens together with insulin and carbohydrates recommendations. Our proposal aims to develop a platform to integrate a series of innovative machine learning models and tools rigorously tested together with the use of the latest IoT devices to manage type 1 diabetes. The resulting system actually closes the loop, like the artificial pancreas, but in an intermittent way.
Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
