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Hot isostatic pressing (HIP) allows the production of complex components geometry. Generally, a high quality of the components is achieved due to the well managed composition of the metal powder and the non-isotropic properties. If a duplex stainless steel is produced, a heat treatment after the HIP-process is necessary to remove precipitations like carbides, nitrides and intermetallic phases. In a new process, the sintering step should be combined with the heat treatment. In this case a high cooling rate is necessary to avoid precipitations in duplex stainless steels. In this work, the influence of the HIP-temperature and the wall thickness on corrosion resistance, microstructure and impact strength were investigated. The results should help to optimize the process parameters like temperature and cooling rate. For the investigation, two HIP-temperatures were tested in a classical HIP-process step with a defined cooling rate. An additional heat treatment was not conducted. The specimens were cut from different sectors of the HIP-block. For investigation of the corrosion resistance, the critical pitting temperature was determined with electrochemical method according to EN ISO 17864. An impact test was used to determine the impact transition temperature. Metallographic investigations show the microstructure in the different sectors of the HIP-block.
These days computer analysis of ECG (Electrocardiograms) signals is common. There are many real-time QRS recognition algorithms; one of these algorithms is Pan-Tompkins Algorithm. Which the Pan-Tompkins Algorithm can detect QRS complexes of ECG signals. The proposed algorithm is analysed the data stream of the heartbeat based on the digital analysis of the amplitude, the bandwidth, and the slope. In addition to that, the stress algorithm compares whether the current heartbeat is similar or different to the last heartbeat after detecting the ECG signals. This algorithm determines the stress detection for the patient on the real-time. In order to implement the new algorithm with higher performance, the parallel programming language CUDA is used. The algorithm determines stress at the same time by determining the RR interval. The algorithm uses a different function as beat detector and a beat classifier of stress.
Stress is recognized as a factor of predominant disease and in the future the costs for treatment will increase. The presented approach tries to detect stress in a very basic and easy to implement way, so that the cost for the device and effort to wear it remain low. The user should benefit from the fact that the system offers an easy interface reporting the status of his body in real time. In parallel, the system provides interfaces to pass the obtained data forward for further processing and (professional) analyses, in case the user agrees. The system is designed to be used in every day’s activities and it is not restricted to laboratory use or environments. The implementation of the enhanced prototype shows that the detection of stress and the reporting can be managed using correlation plots and automatic pattern recognition even on a very light-weighted microcontroller platform.
The ballistocardiography is a technique that measures the heart rate from the mechanical vibrations of the body due to the heart movement. In this work a novel noninvasive device placed under the mattress of a bed estimates the heart rate using the ballistocardiography. Different algorithms for heart rate estimation have been developed.
Sleep is an important part of our life that significantly influences our health and well-being. The monitoring of sleep can provide data based on which sleep quality could be improved. This paper presents a system for heart rate detection during sleep. The data is collected from sensors underneath the test subjects. Though the data contains noise, it needs to be filtered to remove it. Due to the low strength of the signals, they need to be amplified after filtering. At some points of the signal, particular heartbeats may not be tracked by sensors due to the failure of a sensor or other reasons, which should be considered. The heart rate is detected in intervals of 15 s. A tool is implemented that detects the heart rate and visualizes it. The preprocessing of the data is performed with several filters: a highpass filter, a band-reject filter, a lowpass filter, and a motion detector. After the preprocessing of the data, the quality of the signal is significantly increased, and detection is possible.
In many cases continuous monitoring of vital signals is required and low intrusiveness is an important requirement. Incorporating monitoring systems in the hospital or home bed could have benefits for patients and caregivers. The objective of this work is the definition of a measurement protocol and the creation of a data set of measurements using commercial and low-cost prototypes devices to estimate heart rate and breathing rate. The experimental data will be used to compare results achieved by the devices and to develop algorithms for feature extraction of vital signals.
Extracting suitable features from acquired data to accurately depict the current health state of a system is crucial in data driven condition monitoring and prediction. Usually, analogue sensor data is sampled at rates far exceeding the Nyquist-rate containing substantial amounts of redundancies and noise, imposing high computational loads due to the subsequent and necessary feature processing chain (generation, dimensionality reduction, rating and selection). To overcome these problems, Compressed Sensing can be used to sample directly to a compressed space, provided the signal at hand and the employed compression/measurement system meet certain criteria. Theory states, that during this compression step enough information is conserved, such that a reconstruction of the original signal is possible with high probability. The proposed approach however does not rely on reconstructed data for condition monitoring purposes, but uses directly the compressed signal representation as feature vector. It is hence assumed that enough information is conveyed by the compression for condition monitoring purposes. To fuse the compressed coefficients into one health index that can be used as input for remaining useful life prediction algorithms and is limited to a reasonable range between 1 and 0, a logistic regression approach is used. Run-to-failure data of three translational electromagnetic actuators is used to demonstrate the health index generation procedure. A comparison to the time domain ground truth signals obtained from Nyquist sampled coil current measurements shows reasonable agreement. I.e. underlying wear-out phenomena can be reproduced by the proposed approach enabling further investigation of the application of prognostic methods.
With the high resolution of modern sensors such as multilayer LiDARs, estimating the 3D shape in an extended object tracking procedure is possible. In recent years, 3D shapes have been estimated in spherical coordinates using Gaussian processes, spherical double Fourier series or spherical harmonics. However, observations have shown that in many scenarios only a few measurements are obtained from top or bottom surfaces, leading to error-prone estimates in spherical coordinates. Therefore, in this paper we propose to estimate the shape in cylindrical coordinates instead, applying harmonic functions. Specifically, we derive an expansion for 3D shapes in cylindrical coordinates by solving a boundary value problem for the Laplace equation. This shape representation is then integrated in a plain greedy association model and compared to shape estimation procedures in spherical coordinates. Since the shape representation is only integrated in a basic estimator, the results are preliminary and a detailed discussion for future work is presented at the end of the paper.
Guiding through the Fog
(2021)
Corporate Entrepreneurship (CE) programs are formalized efforts to realize entrepreneurial activities in established companies. Despite the growing and evolving landscape of CE programs, effectively managing them remains a challenging endeavor which results in disappointing outcomes and oftentimes leads to the early termination of such programs. We unmask the differences in goal setting of CE programs and highlight that setting appropriate goals is imperative for their desired outcomes. In practice, companies seem to struggle with the goal setting, and scholars have not yet fully solved the puzzle of goals setting in the context of CE programs either. Therefore, we set out to explore the current state of goal setting in the context of CE programs building upon 61 semi-structured interviews with CE program executives from cross-industry companies with different sizes. Our study contributes to a better understanding of goal setting in the context of CE programs by (1) characterizing the goal setting of CE programs based on goal attributes and goal types and (2) identifying differences among the goal setting of CE programs. We provide implications to practice for a more effective management of CE programs and conclude with a discussion for future research on the impact of the different goal settings.
Growth is a key indicator of the prosperity of an economy. In today's Germany the " Gründerzeit " still describes a period of enormous economic growth. Factors that lead to growth haven't been investigated in the context of the different life cycle stages of early-stage technology ventures so far. This paper proposes a model of early-stage ventures' growth based on factors. From a theoretical angle, we look at the business from the market-based view (MBV) and the resource-based view (RBV) on strategy in the longitudinal perspective of the business life cycle. With this view we get to know what are the stage specific needs and processes of new technology based ventures in order to provide appropriate support. We tested different potential growth indicators for the model with a questionnaire-based survey which was answered by 68 high-tech entrepreneurs. The results suggest that growth factors are stage specific in their relevance. While leading to growth in one stage, certain factors evince no or even negative influence on growth in other stages. Moreover, RBV factors as seen more relevant for the growth than the MBV factors. Further research requires a large and representative population to validate the results. Keywords:-growth factors, early-stage ventures, market-based view, resources based view.
The IT unit is not the only provider of information technology (IT) used in business processes. Aiming for increased performance, many business workgroups autonomously implement IT resources not covered by their organizational IT service management. This is called shadow IT. Risks and inefficiencies associated with this phenomenon challenge organizations. Organizations need to decide how to deal with identified shadow IT and if the business or the IT unit should be responsible for corresponding tasks and components. This study proposes design principles for a method to control identified shadow IT following action design research in four organizational settings. The procedure results in an allocation of IT task responsibilities between the business workgroups and the IT unit following risk considerations and transaction cost economics, leading to an IT service governance. This contributes to governance research regarding adaptive and efficient arrangements with reduced risks for business-located IT activities.
Female Entrepreneurship has gained interest over the last 20 years. Therefore, this paper analyses 7,320 articles of the research field ‘women in entrepreneurial context’ published in 885 journals. The sample is analyzed by using a machine learning and text mining based methodological approach. Aiming to provide a broad overview over the research literature, 41 clusters and 11 superordinate topics were identified. Major developments of research attention are outlined by analyzing bibliometric data of the period from 2000 to 2020. Overall growth in terms of research attention measured by the development of yearly citations per article is best noticeable in clusters ‘corporate social responsibility’, ‘brand’, and ‘corporate (-governance)’, and in superordinate topics ‘performance’, ‘education’, and ‘corporate (board/ management)’. There are also indicators for an overall increase of research attention and cluster variety. The synthesis provides an insight into most trending superordinate topics. Therefore, this literature review gives a comprehensive and descriptive overview as well as an insight into thematic trend developments of the research field.
Generative Design Software - How does digitalization change the professional profile of architects
(2019)
Abstract, Poster und Vortrag