Towards understanding of value co-creation on web 2.0 platforms: an assessment methodology

Web 2.0 technologies and social media can be used as a platform for value creation. While some firms are successful in engaging with external audiences on social media, others are less so. Many of these firms have equal access to web 2.0 platforms and operate in similar or same conditions, the resource based view (RBV) offers an explanation for disparities in performance of these organisations: the differences are due to firm internal, valuable, immutable and rare resources. Comparing high- and low-performers in a comparative case study helps to identify and highlight firm internal idiosyncratic resources that result in better sustained performances. In-depth studies inside the organisations answer the questions how and why some firms on the same platform can attract higher engagement levels than others. The problem is how to recognise best and worst performance to conduct in-depth case studies? This paper introduces ALIAS – a methodology for identification of the relative firm performance within a population, and selection of theoretically relevant cases to conduct comparative case studies through the lens of RBV. The proposed methodology is a five step process and utilises the DART framework of value co-creation for identification and assessment of performance criteria

It’s not about what, it’s about who you know: social media-use in organisations

This paper investigates the impact of social media-use on communication processes within organisations. Findings from three qualitative comparative case studies are analysed through the lens of the resource based view of organisations. The analysis follows comparative logic focusing on similarities and differences in case-settings and outcomes. Each of the cases represents an organisation with similar workforces of similar size, composition and distribution but with qualitatively different approaches to social media-use and, as expected, different effects of social media on processes and capabilities. The findings suggest, that the value of social media in contrast to other IT technologies is derived from its use for relationship-building (who actors are connected to and how) rather than information storage and dissemination (what do actors know and where they find it)

Look who's co-creating: employer branding on social media

Web2.0 changes the way information, services and products are created. Companies engage with consumers in a process of co-creation to invent, shape and generate added value. This trend has been labelled Enterprise 2.0. This interdisciplinary study joins the fields of Infor-mation Systems, Marketing and Human Resource Management and provides an insight into how the models of value-, product- and service co-creation can be applied to the domain of employer branding. Based on the DART-model of value co-creation a qualitative multi-case study investi-gates how social media usage contributes to co-creation of employer brand. The study reveals unexpected trends, paradoxes and potential conflicts, and provides suggestions for further re-search. The paper highlights the lack of Dialogue between employer and employee; new ways of Accessing information by employees outside the control of the employer; the uncertainty of ben-efits and Risks of employee involvement in brand creation; and increased Transparency through inclusion of new participants in the employer brand creation process: alumni and customers. The study identifies an emergent shift of power to control and create information from the or-ganization towards employees and consumers and links this power shift to social media use by organisations and their employees

Pléiades project: Assessment of georeferencing accuracy, image quality, pansharpening performence and DSM/DTM quality

Pléiades 1A and 1B are twin optical satellites of Optical and Radar Federated Earth Observation (ORFEO) program jointly running by France and Italy. They are the first satellites of Europe with sub-meter resolution. Airbus DS (formerly Astrium Geo) runs a MyGIC (formerly Pléiades Users Group) program to validate Pléiades images worldwide for various application purposes. The authors conduct three projects, one is within this program, the second is supported by BEU Scientific Research Project Program, and the third is supported by TÜBİTAK. Assessment of georeferencing accuracy, image quality, pansharpening performance and Digital Surface Model/Digital Terrain Model (DSM/DTM) quality subjects are investigated in these projects. For these purposes, triplet panchromatic (50 cm Ground Sampling Distance (GSD)) and VNIR (2 m GSD) Pléiades 1A images were investigated over Zonguldak test site (Turkey) which is urbanised, mountainous and covered by dense forest. The georeferencing accuracy was estimated with a standard deviation in X and Y (SX, SY) in the range of 0.45m by bias corrected Rational Polynomial Coefficient (RPC) orientation, using ~170 Ground Control Points (GCPs). 3D standard deviation of ±0.44m in X, ±0.51m in Y, and ±1.82m in Z directions have been reached in spite of the very narrow angle of convergence by bias corrected RPC orientation. The image quality was also investigated with respect to effective resolution, Signal to Noise Ratio (SNR) and blur coefficient. The effective resolution was estimated with factor slightly below 1.0, meaning that the image quality corresponds to the nominal resolution of 50cm. The blur coefficients were achieved between 0.39-0.46 for triplet panchromatic images, indicating a satisfying image quality. SNR is in the range of other comparable space borne images which may be caused by de-noising of Pléiades images. The pansharpened images were generated by various methods, and are validated by most common statistical metrics and also visual interpretation. The generated DSM and DTM were achieved with ±1.6m standard deviation in Z (SZ) in relation to a reference DTM.Airbus Defence and SpaceBEU/2014-47912266-01TÜBİTAK/114Y38

Vehicle localization by lidar point correlation improved by change detection

LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany

Orientation of oblique airborne image sets - Experiences from the ISPRS/Eurosdr benchmark on multi-platform photogrammetry

During the last decade the use of airborne multi camera systems increased significantly. The development in digital camera technology allows mounting several mid- or small-format cameras efficiently onto one platform and thus enables image capture under different angles. Those oblique images turn out to be interesting for a number of applications since lateral parts of elevated objects, like buildings or trees, are visible. However, occlusion or illumination differences might challenge image processing. From an image orientation point of view those multi-camera systems bring the advantage of a better ray intersection geometry compared to nadir-only image blocks. On the other hand, varying scale, occlusion and atmospheric influences which are difficult to model impose problems to the image matching and bundle adjustment tasks. In order to understand current limitations of image orientation approaches and the influence of different parameters such as image overlap or GCP distribution, a commonly available dataset was released. The originally captured data comprises of a state-of-the-art image block with very high overlap, but in the first stage of the so-called ISPRS/EUROSDR benchmark on multi-platform photogrammetry only a reduced set of images was released. In this paper some first results obtained with this dataset are presented. They refer to different aspects like tie point matching across the viewing directions, influence of the oblique images onto the bundle adjustment, the role of image overlap and GCP distribution. As far as the tie point matching is concerned we observed that matching of overlapping images pointing to the same cardinal direction, or between nadir and oblique views in general is quite successful. Due to the quite different perspective between images of different viewing directions the standard tie point matching, for instance based on interest points does not work well. How to address occlusion and ambiguities due to different views onto objects is clearly a non-solved research problem so far. In our experiments we also confirm that the obtainable height accuracy is better when all images are used in bundle block adjustment. This was also shown in other research before and is confirmed here. Not surprisingly, the large overlap of 80/80% provides much better object space accuracy – random errors seem to be about 2-3fold smaller compared to the 60/60% overlap. A comparison of different software approaches shows that newly emerged commercial packages, initially intended to work with small frame image blocks, do perform very well

Serum glucose, lactate dehydrogenase and hypertension are mediators of the 1 effect of body mass index on severity of COVID-19

Background: COVID-19 has a broad clinical specturm. We investigated the role of serum markers measured on admission on severity as assessed at discharge and investigated those which relate to the effect of BMI on severity. Methods: Clinical and laboratory data form 610 COVID-19 cases hospitalised in the province of Zheijang, China was investigated as risk factors for severe COVID-19 (assessed by respiratory distress) compared to mild or common forms using logistic regression methods. Biochemical markers were correlated with severity using spearman correlations and a ROC analysis was used to determine the individual contribution of each of the biochemical markers on severity. We carried out formal mediation analyses to investigate the extent of the effect of body mass index (BMI) on COVID-19 severity mediated by hypertension, glycemia, Lactose Dehydrogenase (LDH) at the time of hospitalisation and C-Reactive Protein levels (CRP), in units of standard deviations. Results: The individual markers measured on admission contributing most strongly to prediction of COVID-19 severity as assessed at discharge were LDH, CRP and glucose. The proportion of the effect of BMI on severity of COVID-19 mediated by CRP, glycemia or hypertension we find that glucose mediated 79% (

Long-term Correction of Very Long-chain Acyl-CoA Dehydrogenase Deficiency in Mice Using AAV9 Gene Therapy

Very long-chain acyl-coA dehydrogenase (VLCAD) is the rate-limiting step in mitochondrial fatty acid oxidation. VLCAD-deficient mice and patients clinical symptoms stem from not only an energy deficiency but also long-chain metabolite accumulations. VLCAD-deficient mice were treated systemically with 1 × 1012 vector genomes of recombinant adeno-associated virus 9 (rAAV9)-VLCAD. Biochemical correction was observed in vector-treated mice beginning 2 weeks postinjection, as characterized by a significant drop in long-chain fatty acyl accumulates in whole blood after an overnight fast. Changes persisted through the termination point around 20 weeks postinjection. Magnetic resonance spectroscopy (MRS) and tandem mass spectrometry (MS/MS) revealed normalization of intramuscular lipids in treated animals. Correction was not observed in liver tissue extracts, but cardiac muscle extracts showed significant reduction of long-chain metabolites. Disease-specific phenotypes were characterized, including thermoregulation and maintenance of euglycemia after a fasting cold challenge. Internal body temperatures of untreated VLCAD−/− mice dropped below 20 °C and the mice became lethargic, requiring euthanasia. In contrast, all rAAV9-treated VLCAD−/− mice and the wild-type controls maintained body temperatures. rAAV9-treated VLCAD−/− mice maintained euglycemia, whereas untreated VLCAD−/− mice suffered hypoglycemia following a fasting cold challenge. These promising results suggest rAAV9 gene therapy as a potential treatment for VLCAD deficiency in humans