Refine
Year of publication
- 2016 (91) (remove)
Document Type
- Conference Proceeding (54)
- Article (21)
- Part of a Book (8)
- Other Publications (5)
- Book (1)
- Doctoral Thesis (1)
- Report (1)
Language
- English (91) (remove)
Keywords
- Abstract interpretation (1)
- Bernstein polynomial (1)
- Block codes (1)
- Body sensor networks (1)
- Business life-cycle (1)
- Business plan (3)
- Bytecode (1)
- Cauchon algorithm (1)
- Chassis dynamometer (1)
- Code Generation (1)
Institute
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.
In this paper, utilisation of an Unscented Kalman Filter for concurrently performing disturbance estimation and wave filtering is investigated. Experimental results are provided that demonstrate very good performance subject to both tasks. For the filter, a dynamic model has been used which was optimised via correlation analysis in order to obtain a minimum set of relevant parameters. This model has also been validated by experiments deploying a small vessel. A simulation study is presented to evaluate the performance using known quantities. Experimental trials have been performed on the Rhine river. The results show that for instance flow direction and varying current velocities can continuously be estimated with decent precision, even while the boat is performing turning manoeuvres. Moreover, the filtering properties are very satisfactory. This makes the filter suitable for being used, for instance, in autonomous vessel applications or assistance systems.
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.
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.