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User innovators follow multiple diffusion and adoption pathways for their self-developed innovations. Users may choose to commercialize their self-developed products on the marketplace by becoming entrepreneurs. Few studies exist that focus on understanding personal and interpersonal factors that affect some user innovators’ entrepreneurial decision-making. Hence, this paper focuses on how user innovators make key decisions relating to opportunity recognition and evaluation and when opportunity evaluation leads to subsequent entrepreneurial action in the entrepreneurial process. We conducted an exploratory study using a multi-grounded theory methodology as the user entrepreneurship phenomenon embodies complex social processes. We collected data through the netnography approach that targeted 18 entrepreneurs with potentially relevant differences through crowdfunding platforms. We integrated self-determination, human capital, and social capital theory to address the phenomena under study. This study’s significant findings posit that users’ motives are dissatisfaction with existing goods, interest in innovation, altruism, social recognition, desire for independence, and economic benefits. Besides, use-related experience, product-related knowledge, product diffusion, and iterative feedback positively impact innovative users’ entrepreneurial decision-making.
Theoretical foundation, effectiveness, and design artefact for machine learning service repositories
(2022)
Machine learning (ML) has played an important role in research in recent years. For companies that want to use ML, finding the algorithms and models that fit for their business is tedious. A review of the available literature on this problem indicates only a few research papers. Given this gap, the aim of this paper is to design an effective and easy-to-use ML service repository. The corresponding research is based on a multi-vocal literature analysis combined with design science research, addressing three research questions: (1) How is current white and gray literature on ML services structured with respect to repositories? (2) Which features are relevant for an effective ML service repository? (3) How is a prototype for an effective ML service repository conceptualized? Findings are relevant for the explanation of user acceptance of ML repositories. This is essential for corporate practice in order to create and use ML repositories effectively.
Gamification is one of the recognized methods of motivating people in various life processes, and it has spread to many spheres of life, including healthcare. This article proposes a system design for long-term care patients using the method mentioned. The proposed system aims to increase patient engagement in the treatment and rehabilitation process via gamification. Literature research on available and earlier proposed systems was conducted to develop a suited system design. The primary target group includes bedridden patients and a sedentary lifestyle (predominantly lying in bed). One of the main criteria for selecting a suitable option was its contactless realization for the mentioned target groups in long-term care cases. As a result, we developed the system design for hardware and software that could prevent bedsores and other health problems from occurring because of low activity. The proposed design can be tested in hospitals, nursing homes, and rehabilitation centers.
The rapid development and growth of knowledge has resulted in a rich stream of literature on various topics. Information systems (IS) research is becoming increasingly extensive, complex, and heterogeneous. Therefore, a proper understanding and timely analysis of the existing body of knowledge are important to identify emerging topics and research gaps. Despite the advances of information technology in the context of big data, machine learning, and text mining, the implementation of systematic literature reviews (SLRs) is in most cases still a purely manual task. This might lead to serious shortcomings of SLRs in terms of quality and time. The outlined approach in this paper supports the process of SLRs with machine learning techniques. For this purpose, we develop a framework with embedded steps of text mining, cluster analysis, and network analysis to analyze and structure a large amount of research literature. Although the framework is presented using IS research as an example, it is not limited to the IS field but can also be applied to other research areas.
In order to evaluate the performance of different stapes prosthesis types, a coupled finite element (FE) model of human ear was developed. First, the middle-ear FE model was developed and validated using the middle-ear transfer function measurements available in literature including pathological cases. Then, the inner-ear FE model was developed and validated using tonotopy, impedance, and level of cochlea amplification curves from literature. Both models are based on pre-existing research with some improvements and were combined into one coupled FE model. The stapes in the coupled FE ear model was replaced with a model of a stapes prosthesis to create a reconstructed ear model that can be used to estimate how different types of protheses perform relative to each other as well as to the natural ear. This will help in designing of new innovative types of stapes prostheses or any other type of middle-ear prostheses as well as to improve the ones that are already available on the market.
An autonomous vehicle is a robotic vehicle with decision and action capability capable of performing assigned tasks without or with minimal human intervention. Autonomous cars have been in development for many years. The Society of Automotive Engineers (SAE International) published in 2014 a classification in five levels of driving automation, with level 0 corresponding to completely manual driving, and level 5 to an ideal dream where the vehicle would be able to navigate entirely autonomously for all missions and in all environments. This work addressed the navigation of an autonomous vehicle in general. We focus on one of the most complex scenarios of the road network and crossing of road intersections. In this paper, the critical features of autonomous intelligent vehicles are reviewed. Furthermore, the associated problems are presented, and the most advanced solutions are derived. This article aims to allow a novice in this field to understand the different facets of localization and perception problems for autonomous vehicles.
Personalized remote healthcare monitoring is in continuous development due to the technology improvements of sensors and wearable electronic systems. A state of the art of research works on wearable sensors for healthcare applications is presented in this work. Furthermore, a state of the art of wearable devices, chest and wrist band and smartwatches available on the market for health and sport monitoring is presented in this paper. Many activity trackers are commercially available. The prices are continuously reducing and the performances are improving, but commercial devices do not provide raw data and are therefore not useful for research purposes.
The transmembrane Ca2+ − activated Cl− channel - human bestrophin-1 (hBest1) is expressed in retinal pigment epithelium and mutations of BEST1 gene cause ocular degenerative diseases colectivelly referred to as “bestrophinopathies”. A large number of genetical, biochemical, biophysical and molecular biological studies have been performed to understand the relationship between structure and function of the hBest1 protein and its pathophysiological significance. Here, we review the current understanding of hBest1 surface organization, interactions with membrane lipids in model membranes, and its association with microdomains of cellular membranes. These highlights are significant for modulation of channel activity in cells.
Public transport causes in rural areas high costs per passenger and kilometer as the frequency of scheduled busses is low and therefore, many people avoid using public transport. With the trend of moving from urban regions to countryside individual traffic will further increase. To tackle issues of emissions, mobility for young and elderly people and provide economically meaningful public transport a new concept was elaborated in Germany. This consists of (partly) autonomous shuttle busses which are remote controlled. For implementation rural districts of Germany have worked together and set up a three-phase plan consisting of a project with public funding, a highly frequent used pilot region and industrial partners with the commitment and possibilities for necessary investments. The concept promises economical value with respect to installation, service and maintaining costs, it leads to lower barriers for public transport of young and elderly people and ultimately reduces emissions and congestions.
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.
In recent decades, it can be observed that a steady increase in the volume of tourism is a stable trend. To offer travel opportunities to all groups, it is also necessary to prepare offers for people in need of long-term care or people with disabilities. One of the ways to improve accessibility could be digital technologies, which could help in planning as well as in carrying out trips. In the work presented, a study of barriers was first conducted, which led to selecting technologies for a test setup after analysis. The main focus was on a mobile app with travel information and 360° tours. The evaluation results showed that both technologies could increase accessibility, but some essential aspects (such as usability, completeness, relevance, etc.) need to be considered when implementing them.
Protective welding clothing must meet various requirements. Among other things, it must be flame-resistant, protect against splashes of metal or sparks and also ensure protection against radiant heat and UV light caused by exposure to the welding arc. The protection against molten metal splashes is directly related to the fabric weight per unit area of the protective welding clothing and the level of protection is normally determined by the number of molten metal droplets that fall on the fabric. The higher the weight per unit area, the greater the protection against welding spatter. However, increasing the fabric weight per unit area also leads to psychologically uncomfortable wearing and thus increasing the physical strain on the wearer. The required basis weight per unit area of protective welding clothing can be reduced by applying nanoparticles as a protective layer while preserving other indispensable properties.
The hearing contact lens® (HCL) is a new type of hearing aid devices. One of its main components is a piezo-electric actuator. In order to evaluate and maximize the HCL’s performance, a model of the HCL coupled to the middle ear was developed using finite element approach. The model was validated step by step starting with the HCL only. To validate the HCL model, vibrational measurements on the HCL were performed using a Laser-Doppler-Vibrometer (LDV). Then, a silicone cap was placed onto the HCL to provide an interface between the HCL and the tympanic membrane of the middle-ear model and additional LDV measurements on temporal bones were performed to validate the coupled model. The coupled model was used to evaluate the equivalent sound pressure of the HCL. Moreover, a deeper insight was gained into the contact between the HCL and tympanic membrane and its effects on the HCL performance. The model can be used to investigate the sensitivity of geometrical and material parameters with respect to performance measures of the HCL and evaluate the feedback behavior.
Enterprises and societies currently face crucial challenges, while Society 5.0 can contribute to a supersmart society, especially for manufacturing and healthcare, and Industry 4.0 becomes important in the global manufacturing industry. Smart energy digital platforms are architected to manage energy supply efficiently. Furthermore, the above digital platforms are expected to collect various kinds of data and analyze Big Data for the trends in the sharing economy in ecosystems. The adaptive integrated digital architecture framework (AIDAF) for Design Thinking Approach with Risk Management is expected to make an alignment with digital IT strategy. In this paper, we propose that various energy management systems and related digital platforms are designed and implemented in an alignment to digital IT strategy for sharing economy toward Society 5.0, with the AIDAF framework for Design Thinking Approach with Risk Management. The vision of AIDAF applications to enable sharing economy and digital platforms is explained and extended in the context of Society 5.0. In addition, challenges and future activities for this area are discussed that cover the directions of smart energy for Society 5.0.
What might the attendee be able to do after being in your session?
Our work shows how to connect intra-operative devices via IEEE 11073 Service-oriented Device Connectivity (SDC).
Description of the Problem or Gap
Standardized device communication is essential for interoperability, availability of device data, and therefore for the intelligent operating room (OR) and arising solutions. The SDC standard was developed to make information from medical devices available in a uniform manner and enable interoperability. Existing devices are rarely SDC-capable and need interfaces to be interoperable via SDC.
Methods: What did you do to address the problem or gap?
We conceived an SDC-based architecture consisting of a service provider and service consumer. In our concept, the service provider is connected to the medical device and capable to translate the proprietary protocol of the device into SDC and vice versa. The service consumer is used to request or send information via the SDC protocol to the service provider and can function as a uniform bidirectional interface (e.g. for displaying or controlling). This concept was exemplarily demonstrated with the patient monitor MX800 of Philips to retrieve the device data (e.g. vital parameters) via SDC and partly for the operating light marLED X of KLS Martin Group.
Results: What was the outcome(s) of what you did to address the problem or gap?
The patient monitor MX800 was connected to a Raspberry Pi (RPi) via LAN, on which the service provider is running. The python script on the RPi establishes a connection to the monitor and translates incoming and outgoing messages from the proprietary protocol to SDC and vice versa to/from the service consumer. The service consumer is running on a laptop and acts as a simulation for different kinds of systems that want to get vital parameters or other information from the patient monitor. The operating light marLED X was connected to an RPi via USB-to-RS232. A python script on the RPi establishes a connection to the light and makes it possible via proprietary commands to get information of the light (e.g. status) and to control it (e.g. toggle the light, increment the intensity). A translation to SDC is not integrated yet.
Discussion of Results
Our practical implementation shows that medical devices can be accessed via external connections to get device data and control the device via commands. The example SDC implementation of the patient monitor MX800 makes it possible to request its data via the standardized communication protocol SDC. This is also possible for the operating light marLED X if its proprietary protocol is analyzed to be translatable to/from SDC. This would allow to control the device from an external system, or automatically depending on the status of the ongoing procedure. The advantage is, that existing intra-operative devices can be extended by a service provider which is capable of translating the proprietary protocol of the device in SDC and vice versa. This enables interoperability and an intelligent OR that, for example, is aware of all devices, their status, and data and can use this information to optimally support the surgeons and their team (e.g. provision of information, automated documentation). This interoperability allows that future innovations merely need to understand the SDC protocol instead of all vendor-dependent communication protocols.
Conclusion
Standardized device communication is essential to reach interoperability, and therefore intelligent ORs. Our contribution addresses the possibility of subsequently making medical devices SDC-capable. This may eliminate the need of understanding all the different proprietary protocols when developing new innovative solutions for the OR.
Current clinical practice is often unable to identify the causes of conductive hearing loss in the middle ear with sufficient certainty without exploratory surgery. Besides the large uncertainties due to interindividual variances, only partially understood cause–effect principles are a major reason for the hesitant use of objective methods such as wideband tympanometry in diagnosis, despite their high sensitivity to pathological changes. For a better understanding of objective metrics of the middle ear, this study presents a model that can be used to reproduce characteristic changes in metrics of the middle ear by altering local physical model parameters linked to the anatomical causes of a pathology. A finite-element model is, therefore, fitted with an adaptive parameter identification algorithm to results of a temporal bone study with stepwise and systematically prepared pathologies. The fitted model is able to reproduce well the measured quantities reflectance, impedance, umbo and stapes transfer function for normal ears and ears with otosclerosis, malleus fixation, and disarticulation. In addition to a good representation of the characteristic influences of the pathologies in the measured quantities, a clear assignment of identified model parameters and pathologies consistent with previous studies is achieved. The identification results highlight the importance of the local stiffness and damping values in the middle ear for correct mapping of pathological characteristics and address the challenges of limited measurement data and wide parameter ranges from the literature. The great sensitivity of the model with respect to pathologies indicates a high potential for application in model-based diagnosis.
Simulation models of the middle ear have rarely been used for diagnostic purposes due to their limited predictive ability with respect to pathologies. One big challenge is the large uncertainty and ambiguity in the choice of material parameters of the model.
Typically, the model parameters are determined by fitting simulation results to validation measurements. In a previous study, it was shown that fitting the model parameters of a finite-element model using the middle-ear transfer function and various other measurable output variables from normal ears alone is not sufficient to obtain a good predictive ability of the model on pathological middle-ear conditions. However, the inclusion of validation measurements on one pathological case resulted in a very good predictive ability also for other pathological cases. Although the found parameter set was plausible in all aspects, it was not yet possible to draw conclusions about the uniqueness and the accuracy or the uncertainty of the parameter set.
To answer these questions, statistical solution approaches are used in this study. Using the Monte Carlo method, a large number of plausible model data sets are generated that correctly represent the normal and pathological middle-ear characteristics in terms of various output variables like e.g., impedance, reflectance, umbo, and stapes transfer function. Subsequent principal component analyses (PCA) allow to draw conclusions about correlations, quantitative limits and statistical density of parameter values.
Furthermore, applying inverse PCA yields numerous plausible parameterizations of the middle-ear model, which can be used for data augmentation and training of a neural network which is capable of distinguishing between a normal middle ear and pathologies like otosclerosis, malleus fixation, and disarticulation based on objectively measured quantities like impedance, reflectance, and umbo velocity.
The digital twin concept has been widely known for asset monitoring in the industry for a long time. A clear example is the automotive industry. Recently, there has also been significant interest in the application of digital twins in healthcare, especially in genomics in what is known as precision medicine. This work focuses on another medical speciality where digital twins can be applied, sleep medicine. However, there is still great controversy about the fundamentals that constitute digital twins, such as what this concept is based on and how it can be included in healthcare effectively and sustainably. This article reviews digital twins and their role so far in what is known as personalized medicine. In addition, a series of steps will be exposed for a possible implementation of a digital twin for a patient suffering from sleep disorders. For this, artificial intelligence techniques, clinical data management, and possible solutions for explaining the results derived from artificial intelligence models will be addressed.
Early exposure makes the entrepreneur: how economics education in school influences entrepreneurship
(2022)
Many countries that seek to boost their economy share the goal of promoting entrepreneurship. Whereas there is ample research on the predictors of entrepreneurship during adulthood, we know little about how pre-adulthood experience influences entrepreneurship later in life. Using a natural experiment, this paper examines whether introducing economics classes in school enhances entrepreneurial behavior in adulthood. Our difference-in-differences approach exploits curricula reforms across German states that introduced compulsory economics education classes in secondary schools. Using information on school and labor market careers for more than 10,000 individuals from 1984 to 2019, we find that the reform increases students’ entrepreneurial activities by three percentage points. Examining gender differences, we find that economics classes equally benefit female and male students. Our results advance our understanding of how pre-adulthood experiences shape individuals’ entrepreneurial behavior.
With significant advancements in digital technologies, firms find themselves competing in an increasingly dynamic business environment. Therefore, the logic of business decisions is based on the agility to respond to emerging trends in a proactive way. By contrast, traditional IT governance (ITG) frameworks rely on hierarchy and standardized mechanisms to ensure better business/IT alignment. This conflict leads to a call for an ambidextrous governance, in which firms alternate between stability and agility in their ITG mechanisms. Accordingly, this research aims to explore how agility might be integrated in ITG. A quantitative research strategy is implemented to explore the impact of agility on the causal relationship among ITG, business/IT alignment, and firm performance. The results show that the integration of agile ITG mechanisms contributes significantly to the explanation of business/IT alignment. As such, firms need to develop a dual governance model powered by traditional and agile ITG mechanisms.