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An approach for an adaptive position-dependent friction estimation for linear electromagnetic actuators with altered characteristics is proposed in this paper. The objective is to obtain a friction model that can be used to describe different stages of aging of magnetic actuators. It is compared to a classical Stribeck friction model by means of model fit, sensitivity, and parameter correlation. The identifiability of the parameters in the friction model is of special interest since the model is supposed to be used for diagnostic and prognostic purposes. A method based on the Fisher information matrix is employed to analyze the quality of the model structure and the parameter estimates.
Das Software-Engineering sollte nicht nur über das Aufzählen von Aktivitäten charakterisiert, sondern zusätzlich auch über grundsätzliche Probleme motiviert werden. Die Beschäftigung mit dem Warum des Software-Engineerings erhält so mehr Gewicht gegenüber dem Wie. Mit der Betonung des Problembewusstseins nährt man auch weniger das Missverständnis, das Software-Engineering diene hauptsächlich der Disziplinierung von Software- Entwicklern. Es geht eben nicht in erster Linie darum, sich in ein Vorgehensmodell einzufügen und eine Aktivität nach der anderen regelkonform mit den vorgesehenen Werkzeugen abzuarbeiten. Vielmehr sind Spürsinn, Kreativität und Urteilsvermögen gefragt. Denn die genannten grundsätzlichen Probleme sind zwar in jedem Projekt allgegenwärtig, aber trotzdem nicht unbedingt auf den ersten Blick erkennbar, und sie müssen mangels echter Lösungen immer neu mit angemessenen Kompromissen bewältigt werden. Dabei ist Nützlichkeit der Maßstab, nicht Wahrheit. Das alles ist herausfordernd und Herausforderungen machen Spaß.
Nowadays there is a rich diversity of sleep monitoring systems available on the market. They promise to offer information about sleep quality of the user by recording a limited number of vital signals, mainly heart rate and body movement. Typically, fitness trackers, smart watches, smart shirts, smartphone applications or patches do not provide access to the raw sensor data. Moreover, the sleep classification algorithm and the agreement ratio with the gold standard, polysomnography (PSG) are not disclosed. Some commercial systems record and store the data on the wearable device, but the user needs to transfer and import it into specialised software applications or return it to the doctor, for clinical evaluation of the data set. Thus an immediate feedback mechanism or the possibility of remote control and supervision are lacking. Furthermore, many such systems only distinguish between sleep and wake states, or between wake, light sleep and deep sleep. It is not always clear how these stages are mapped to the four known sleep stages: REM, NREM1, NREM2, NREM3-4. [1] The goal of this research is to find a reduced complexity method to process a minimum number of bio vital signals, while providing accurate sleep classification results. The model we propose offers remote control and real time supervision capabilities, by using Internet of Things (IoT) technology. This paper focuses on the data processing method and the sleep classification logic. The body sensor network representing our data acquisition system will be described in a separate publication. Our solution showed promising results and a good potential to overcome the limitations of existing products. Further improvements will be made and subjects with different age and health conditions will be tested.
Software startups
(2016)
Software startup companies develop innovative, software-intensive products within limited time frames and with few resources, searching for sustainable and scalable business models. Software startups are quite distinct from traditional mature software companies, but also from micro-, small-, and medium-sized enterprises, introducing new challenges relevant for software engineering research. This paper’s research agenda focuses on software engineering in startups, identifying, in particular, 70+ research questions in the areas of supporting startup engineering activities, startup evolution models and patterns, ecosystems and innovation hubs, human aspects in software startups, applying startup concepts in non-startup environments, and methodologies and theories for startup research. We connect and motivate this research agenda with past studies in software startup research, while pointing out possible future directions. While all authors of this research agenda have their main background in Software Engineering or Computer Science, their interest in software startups broadens the perspective to the challenges, but also to the opportunities that emerge from multi-disciplinary research. Our audience is therefore primarily software engineering researchers, even though we aim at stimulating collaborations and research that crosses disciplinary boundaries. We believe that with this research agenda we cover a wide spectrum of the software startup industry current needs.
This paper broadens the resource-based approach to explaining survival of new technology-based firms (NTBFs) by focusing on the entrepreneur's ability to transform resources in response to triggers resulting from market interactions. Network theory is used to define a construct that allows determining the status of venture emergence (VE).The operationalization of the VE construct is built on the firm's value network maturity in the four market dimensions customer, investor, partner, and human resource. Business plans of NTBFs represent the artifact that contains this data in the form of transaction relation descriptions. Using content analysis, a multi-step combined human and computer coding process has been developed to empirically determine NTBFs' status of VE.Results of the business plan analysis suggests that the level of transaction relations allows to draw conclusions on the status of VE. Moreover, applying the developed process, a business plan coding test shows that the transaction relation based VE status significantly relates to NTBFs' survival capabilities.
This paper builds upon the widely-used resource-based approach to explaining survival of new technology-based firms (NTBFs). However, instead of looking at the NTBF's initial resource configuration, a process-oriented perspective is taken by focusing on the entrepreneur's ability to transform resources in response to triggers resulting from market interactions. Transaction relations reflect these interactions and are thus operationalized with a suggested method for measuring the status of venture emergence (VE) applicable to early-stage NTBFs. NTBFs' value network maturity is reflected in the number and strength of their transaction relations in the four market dimensions customer, investor, partner, and human resource. Business plans of NTBFs represent the artifact that contains this data in the form of transaction relation descriptions. Using content analysis, a multi-step combined human and computer coding process has been developed to annotate and classify transaction relations from business plans in order to empirically determine NTBFs' status of VE. Results of the business plan analysis suggest that the level of transaction relations allows to draw conclusions on the VE status. Moreover, applying the developed process, first analysis of a business plan coding test shows that the transaction relation based VE status significantly relates to NTBF survival capability.
Tango Argentino
(2016)
Geographieunterricht ist in besonderem Maße prädestiniert, Mensch-Umwelt- und Mensch-Mitwelt-Beziehungen bewusst zu machen. Hierzu soll dieser Band beitragen, denn Musik wirkt ganzheitlich und lässt uns geographische Sachverhalte nicht nur visuell wahrnehmen, sondern macht sie akustisch "fühlbar" und bringt somit eine neue Erfahrungsdimension in den Unterricht. Da Musik aber auch eng mit Kultur verbunden ist, ermöglichen die 12 Unterrichtsbeispiele zudem Zugänge zu kulturellen Vorstellungen anhand diverser Raumbeispiele.
Purpose The purpose of this paper is to find out tourism movement patterns via the tracking of tourists with the help of positioning systems like GPS in the rural area of the Lake Constance destination in Germany. In doing so past, present and future of tourist tracking is illustrated. Design/methodology/approach The tracking is realized via common smartphones extended by an app, with dedicated sensors like position loggers and a survey. The three different approaches are applied in order to compare and cross-check results (triangulation of data and methods). Findings Movement patterns turned out to be diverse and individualistic within the rural destination of Lake Constance and following an ants trail in sub-destinations like the city of Constance. Repeat visitors and first-time visitors alike always visit the bigger cities and main day-trip destinations of the Lake. A possible prediction tool enables new avenues of governing tourism movement patterns. Research limitations/implications The tracking techniques can be developed further into the direction of “quantified self” using gamification in order to make the tracking app even more attractive. Practical implications An algorithm-based prediction tool would offer new perspectives to the management of tourism movements. Social implications Further research is needed to overcome the feeling of invasiveness of the app to allow tracking with that approach. Originality/value This study is original and innovative because of the first-time use of a smartphone app in tourist tracking, the application on a rural destination and the conceptual description of a prediction tool.
Loch im Putz = alles neu?
(2016)