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Observer-based self sensing for digital (on–off) single-coil solenoid valves is investigated. Self sensing refers to the case where merely the driving signals used to energize the actuator (voltage and coil current) are available to obtain estimates of both the position and velocity. A novel observer approach for estimating the position and velocity from the driving signals is presented, where the dynamics of the mechanical subsystem can be neglected in the model. Both the effect of eddy currents and saturation effects are taken into account in the observer model. Practical experimental results are shown and the new method is compared with a full-order sliding mode observer.
We present an approach to reduce the complexity of adjusting privacy preferences for multiple online social networks. To achieve this, we quantify the effect on privacy for choices that users make, and simplify configuration by introducing privacy configuration as a service. We present an algorithm that effectively measures privacy and adjusts privacy settings across social networks. The aim is to configure privacy with one click.
The electrochemical behavior for different surface conditions and different degrees of deformation of metastable austenitic stainless steel AISI 304 UNS S30400 were studied using critical pitting potential and electrochemical noise measurements. The influence on corrosion resistance by using different abrasives (silicon carbide and corundum) for surface finish by grinding is illustrated. For the characterization of local defects and surface topography, scanning electron microscopy (SEM) and tactile measurements were used. An inverse correlation between occurrence of local defects on the surface and critical pitting potential was found by using image processing. Therefore, gray scale values of different surfaces were compared. The influence of mass content of α'-martensite on the corrosion resistance is shown by comparing different qualities of surface finish. For smooth machined surfaces it can be shown that an increasing numbers of strain induced martensite is decreasing the corrosion resistance lightly. For low abrasive machining an inverse correlation between the critical pitting potential and surface roughness is given. However, for higher abrasive machining parameters, this correlation could not be found.
Organizations deploy a plethora of information technology (IT) systems. Various types of enterprise systems (ES) may coexist with the shadow IT systems (SITS) implemented by individual business units without the involvement of the IT department. The associated redundancy of SITS and ES suggests their integration. After integration, however, organization may find it challenging to retain the flexibility and innovation that the development of SITS offers the business. In this study, we conduct a literature review on IT systems integration. This review and the specific characteristics of SITS then serve to define SITS integration, derive guidelines for the integration decision, the phases preceding and following integration, and the integration process itself. SITS and ES integration can profit from existing knowledge of integration benefits, costs, and of the available technologies. Our study offers IT decision makers an insight into the specifics of SITS integration, and provides a basis for future SITS research.
Shadow information technology systems (SITS) coexist with formal enterprise systems in organisations. SITS pose risks but also increase flexibility of business units. Practice shows that SITS emerge, despite that Enterprise Architecture Management (EAM) aims at controling all IT systems in an organization. Studies acknowledge this problem in general. However, they neither show the specific influencing areas of SITS nor provide approaches to address them. To close this gap, we use a literature review to analyse examples of practical SITS and their interference with EAM concerns. Thus, we find that they hinder especially transparency, reduction of EA complexity and governance. Research has focused on achieving transparency, governing the evolution of the EA but lacks strategies for reducing complexity. This study contributes to research and practice by uncovering the main influencing areas of SITS on EAM, as well as by laying a foundation for future research on this topic.
LEGIC Identsystems Ltd
(2017)
One major realm of Condition Based Maintenance is finding features that reflect the current health state of the asset or component under observation. Most of the existing approaches are accompanied with high computational costs during the different feature processing phases making them infeasible in a real-world scenario. In this paper a feature generation method is evaluated compensating for two problems: (1) storing and handling large amounts of data and (2) computational complexity. Both aforementioned problems are existent e.g. when electromagnetic solenoids are artificially aged and health indicators have to be extracted or when multiple identical solenoids have to be monitored. To overcome those problems, Compressed Sensing (CS), a new research field that keeps constantly emerging into new applications, is employed. CS is a data compression technique allowing original signal reconstruction with far fewer samples than Shannon-Nyquist dictates, when some criteria are met. By applying this method to measured solenoid coil current, raw data vectors can be reduced to a way smaller set of samples that yet contain enough information for proper reconstruction. The obtained CS vector is also assumed to contain enough relevant information about solenoid degradation and faults, allowing CS samples to be used as input to fault detection or remaining useful life estimation routines. The paper gives some results demonstrating compression and reconstruction of coil current measurements and outlines the application of CS samples as condition monitoring data by determining deterioration and fault related features. Nevertheless, some unresolved issues regarding information loss during the compression stage, the design of the compression method itself and its influence on diagnostic/prognostic methods exist.
Successful project management (PM), as one of the most important key competences in the western-oriented working world, is mainly influenced by experience and social skills. As a direct impact on PM training, the degree of practice and reality is crucial for the application of lessons learned in a challenging everyday work life. This work presents a recursive approach that adapts well-known principles of PM itself for PM training. Over three years, we have developed a concept and an integrated software system that support our PM university courses. Stepwise, it transfers theoretical PM knowledge into realistic project phases by automatically adjusting to the individual learning progress. Our study reveals predictors such as degrees of collaboration or weekend work as vital aspects in the PM training progress. The chosen granularity of project phases with variances in different dimensions makes our model a canonical incarnation of seamless learning.
As part of large-scale project in the Lake Constance region that borders Germany, Austria and Switzerland, seamless learning prototypes are designed, implemented, and evaluated. A design-based research (DBR) approach is used for the development, implementation and evaluation. The project consists of one base project that brings together instructional design and instructional technology specialists as well as (educational) software architects, supporting seven subprojects in developing seamless-learning lighthouse implementations mostly within higher and further education.
Industrial partners are involved in all subprojects. The authors are unaware of similar seamless learning projects using a DBR approach that include evaluation and redesign and allow for comparison of experiences by applying DBR across subprojects. The project aims to generate novel seamless learning implementations, respective novel research and novel software supporting different aspects of seamless learning. The poster will present the project design, delineate areas of research and development, and include initial empirical results.
Corporate entrepreneurship (CE) supports the strategic renewal of established companies. Corporate venturing represents one key concept of CE that supports companies to strengthen their innovation capabilities. For the successful implementation of corporate ventures dual structures are recommended. The question, how the interface should be designed, plays a crucial role. Although it seems to be an important factor, this aspect requires further attention. One relevant element of the interface design are the different roles of the individuals that are interacting within the interface. This study is based on nine interviews that are representing six internal corporate ventures within one large German corporate from the ICT sector. The results that were mirrored with short case studies of 25 additional companies of the data sample, contribute to a better understanding of the interface design by adding insights about roles in corporate entrepreneurship. This deeper understanding about roles allows to draw conclusions on the interface design from a structural point of view.
This work proposes a decoder implementation for high-rate generalized concatenated (GC) codes. The proposed codes are well suited for error correction in flash memories for high reliability data storage. The GC codes are constructed from inner extended binary Bose-Chaudhuri-Hocquenghem (BCH) codes and outer Reed-Solomon (RS) codes. The extended BCH codes enable high-rate GC codes. Moreover, the decoder can take advantage of soft information. For the first three levels of inner codes we propose an optional Chase soft decoder. In this work, the code construction is explained and a decoder architecture is presented. Furthermore, area and throughput results are discussed.
In the automotive industry a strong effort has been undertaken to reduce the weight of modern vehicles. In order to reduce the energy consumption and to improve the environmental sustainability, the importance of weight reduction activities is even growing faster. As lightweight designing is becoming more and more expensive and show less potential savings, new approaches are needed. One promising technology could be the use of shape memory elements. In the last years a lot of potential application possibilities were presented, demonstrating the benefit of these functional elements in automotive design solutions: they often reduce complexity, weight and design space of an actuation device and enable new functions. In addition they work silently and are therefore ideally suitable for comfort applications in the passenger cabin. Because of the current trend to electric vehicle the hitherto existing drawback of a high electrical energy consumption of shape memory actuators in some design proposals is not given any more.
Leadership in a global world
(2017)
We present an analysis of how to determine security requirements for software that controls routing decisions in the distribution of discrete physical goods. Requirements are derived from stakeholder interests and threat scenarios. Three deployment scenarios are discussed: cloud and hybrid deployment as well as on-premise installation for legacy sites.
Business models (BM) are the logic of a firm on how to create, deliver and capture value. Business model innovation (BMI) is essential to organisations for keeping competitive advantage. However, the existence of barriers to BMI can impact the success of a corporate strategic alignment. Previous research has examined the internal barriers to business model innovation, however there is a lack of research on the potential external barriers that could potentially inhibit business model innovation. Drawn from an in-depth case study in a German medium size engineering company in the equestrian sports industry, we explore both internal and external barriers to business model innovation. BMI is defined as any change in one or more of the nine building blocks of the Business Model Canvas; customer segment, value propositions, channels, customer relation, revenue streams, key resources, key activities, key partners, cost structure [1]. Our results show that barriers to business model innovation can be overcome by the deployment of organisational learning mechanisms and the development of an open network capability.
Stress and physical activities are important aspects of life of people. Body reactions on stress and on physical activities can be very similar but long-term stress leads to diseases and damages the body. Currently there is no method to differentiate easily and clearly between these two aspects in a time slot. We have confronted this problem while developing a mobile system for detection and analysis of stress. This paper presents an approach, which uses a long-term monitor with ECG/EKG capabilities and analysis of the heart rate data that is extracted from the device. The focus of the work is to find characteristics that are useful for differentiation between physical activity and stress.
One way of reducing carbon emissions is to reduce carbon emissions from consumption. Quantitative information about these emissions helps to better understand the reduction potential. This article aims to provide carbon footprint data for students of the University of Applied Science in Konstanz, Germany. The study includes almost 10% of the University’s students. Data on emission patterns was collected via questionnaires and calculated by a web-based carbon calculator. The study analyses personal carbon footprints and, more detailed, carbon emissions from consumption categories heating, electricity, mobility (land travel and aviation) and food. The findings show average students’ annual carbon footprint to be10.9t CO2eq and in the same order of magnitude as the German average. While students cause less emissions through heating because of smaller living space per person, they cause significantly more emissions by aviation. Female students tend to have higher emissions from aviation, instead male students have higher emissions from food (due to more meat in their diet). Business students have higher emissions than others, mainly because they are tending to fly more. The student carbon footprint is far above climate protection goals formulated for 2050.
The estimation of the holding periods of financial products has to be done in a dynamic process in which the size of the observation time interval influences the result. Small intervals will produce smaller average holding periods than bigger ones. The approach developed in this paper offers the possibility of estimating this average independently of the size of this time interval. This method is demonstrated on the example of two distributions, based on the exponential and the geometric probability functions. The estimation will be found by maximizing the likelihood function.
Many secure software development methods and tools are well-known and understood. Still, the same software security vulnerabilities keep occurring. To find out if new source code patterns evolved or the same patterns are reoccurring, we investigate SQL injections in PHP open source projects. SQL injections are well-known and a core part of software security education. For each common part of SQL injections, the source code patterns are analysed. Examples are pointed out showing that developers had software security in mind, but nevertheless created vulnerabilities. A comparison to earlier work shows that some categories are not found as often as expected. Our main contribution is the categorization of source code patterns.
In extended object tracking, a target is capable to generate more than one measurement per scan. Assuming the target being of elliptical shape and given a point cloud of measurements, the Random Matrix Framework can be applied to concurrently estimate the target’s dynamic state and extension. If the point cloud contains also clutter measurements or origins from more than one target, the data association problem has to be solved as well. However, the well-known joint probabilistic data association method assumes that a target can generate at most one detection. In this article, this constraint is relaxed, and a multi-detection version of the joint integrated probabilistic data association is proposed. The data association method is then combined with the Random Matrix framework to track targets with elliptical shape. The final filter is evaluated in the context of tracking smaller vessels using a high resolution radar sensor. The performance of the filter is shown in simulation and in several experiments.
We examine to what extent a transaction relation-based value network maturity status of New Technology-Based Firms (NTBFs) is related to their survival. A specific challenge of NTBFs is their lack of market-orientation, which is why the maturity of the ties they form towards the market in terms of customers, financiers, personnel and partners is supposed to be a strong indicator for survival. We analyze a sample of 170 NTBFs by capturing their value network status from business plans and defining their survival status using secondary research. Simple statistical tests and regressions suggest that the official registration of the business is a pre-step for survival that requires industry-specific value network dimension strengths. A sub-sample survival analysis shows that for all NTBFs that have reached registration, regardless of their industry, a stronger customer value network maturity dimension prevents from failure and is thus a significant predictor for survival. Moreover, the analyses partly support the idea that NTBFs from the IT sector are less dependent on a strong value network in the financier dimension to survive. The results are of relevance for both practitioners and researchers in the innovation system: a better understanding of the factors impacting on NTBF survival can help to provide more tailored support services for young firms, increase the effectiveness of resource allocations, and provide a basis for further research.
The evolution of strain induced martensite in austenitic stainless steel AISI 304 was investigated in a rolling contact on a two-discs-tribometer. The effects of surface roughness, slip and normal force as well as the number of load cycles were examined. In comparison to the investigations of martensitic phase transformation during cold rolling, the applied stresses are considerably lower. The formation of strain induced martensite was detected in-situ by means of a FERITSCOPE MP30 and ex-situ by optical microscopy after etching with Kane etchant. Both number of load cycles and magnitude of normal force appeared to be the main influencing factors regarding strain induced martensitic evolution in low stress rolling contacts.
This work proposes a lossless data compression algorithm for short data blocks. The proposed compression scheme combines a modified move-to-front algorithm with Huffman coding. This algorithm is applicable in storage systems where the data compression is performed on block level with short block sizes, in particular, in non-volatile memories. For block sizes in the range of 1(Formula presented.)kB, it provides a compression gain comparable to the Lempel–Ziv–Welch algorithm. Moreover, encoder and decoder architectures are proposed that have low memory requirements and provide fast data encoding and decoding.
Sleep quality and in general, behavior in bed can be detected using a sleep state analysis. These results can help a subject to regulate sleep and recognize different sleeping disorders. In this work, a sensor grid for pressure and movement detection supporting sleep phase analysis is proposed. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this project is a non-invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable Actigraphy devices tends to be uncomfortable. Besides this fact, they are also very expensive. The system represented in this work classifies respiration and body movement with only one type of sensor and also in a non-invasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed the potential for classification of breathing rate and body movements. Although previous researches show the use of pressure sensors in recognizing posture and breathing, they have been mostly used by positioning the sensors between the mattress and bedsheet. This project however, shows an innovative way to position the sensors under the mattress.
Rethinking Compliance
(2017)
In the past Compliance Management has often failed, the Volkswagen emissions scandal just being one prominent example. Not everything has to be reinvented, and not everything that companies have done in the past regarding Compliance is wrong. But it is about time to think Compliance in new ways. What does “Compliance Management 2.0” really depend on? The following article aims at laying out the cornerstones for enduring effective Compliance which amongst others comprises sincerity and credibility and a moral foundation. Furthermore, the commitment and role model behavior of top managers and the training of line managers are crucial for the effectiveness of any Compliance Management System (CMS). Ultimately, for Compliance to function efficiently the efforts must be adequate for the respective company and realistic regarding the achievable goals.
To evaluate the quality of sleep, it is important to determine how much time was spent in each sleep stage during the night. The gold standard in this domain is an overnight polysomnography (PSG). But the recording of the necessary electrophysiological signals is extensive and complex and the environment of the sleep laboratory, which is unfamiliar to the patient, might lead to distorted results. In this paper, a sleep stage detection algorithm is proposed that uses only the heart rate signal, derived from electrocardiogram (ECG), as a discriminator. This would make it possible for sleep analysis to be performed at home, saving a lot of effort and money. From the heart rate, using the fast Fourier transformation (FFT), three parameters were calculated in order to distinguish between the different sleep stages. ECG data along with a hypnogram scored by professionals was used from Physionet database, making it easy to compare the results. With an agreement rate of 41.3%, this approach is a good foundation for future research.
Industry 4.0
(2017)
Deep 3D
(2017)
Vortrag
In the reverse engineering process one has to classify parts of point clouds with the correct type of geometric primitive. Features based on different geometric properties like point relations, normals, and curvature information can be used, to train classifiers like Support Vector Machines (SVM). These geometric features are estimated in the local neighborhood of a point of the point cloud. The multitude of different features makes an in-depth comparison necessary. In this work we evaluate 23 features for the classification of geometric primitives in point clouds. Their performance is evaluated on SVMs when used to classify geometric primitives in simulated and real laser scanned point clouds. We also introduce a normalization of point cloud density to improve classification generalization.
Vortrag
As a result of increasing needs and shrinking resources, aquaculture is gaining progressively significance in the recent years. Ecological issues such as negative effects on the ecological system due to the high fish density in the farms, the use of copper as antifouling strategy etc. are very present, particularly regarding the increasing number of fish going to be produced in farms in the future. Current trends focus on larger farms operated offshore. To make these farms working safe and economical, reliability has to be improved and maintenance costs need to be reduced. Also, alternatives with higher mechanical strength compared to current textile net materials as well as common metal wires might be necessary. In the last years, a new net system made of high strength duplex stainless steel wires with environmentally friendly antifouling properties suitable for offshore applications was developed. The first nets are operating for one year now as predator protection (i.e. seals) for fish farms and show a good performance in cleaning capability and predator protection. But in the real usage, some corrosion effects in the contact points of the net made of duplex stainless steel 1.4362 occur which were not observed in preliminary tests in laboratory and at different test sites around the world. These corrosion effects endanger the sustainable success of the net system. In this work, the observed corrosion effects are investigated. A laboratory test, which simulates the movement in the contact points of the net, was developed. Two pieces of wire are bent in the middle and get stucked into each other. One wire is fixed at both ends and the second wire is fixed on one end. On the other end, a circular movement with 1-2 rps and a 1 cm displacement is applied. The movement generates friction between the wires and the passive layer will be locally damaged. When the movement stops, a repassivation starts. The passivity breakdown and the repassivation were measured with electrochemical techniques. During the friction phase, when the surface will be activated, the open circuit potential breaks down. When the friction stops, the OCP increases. Between the movement phases, measurements of critical pitting potential were done. Thereby the quality of repassivation was investigated. The tests were done in a 3% sodium chloride solution. Different temperatures were tested as well as the influence of air saturation and low oxygen content.
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