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Binary relations with certain properties such as biorders, equivalences or difunctional relations can be represented as particular matrices. In order for these properties to be identified usually a rearrangement of rows and columns is required in order to reshape it into a recognisable normal form. Most algorithms performing these transformations are working on binary matrix representations of the underlying relations. This paper presents an approach to use the RLE-compressed matrix representation as a data structure for storing relations to test whether they are biorders in a hopefully more efficient way.
Hox genes are an evolutionary highly conserved gene family. They determine the anterior-posterior body axis in bilateral organisms and influence the developmental fate of cells. Embryonic stem cells are usually devoid of any Hox gene expression, but these transcription factors are activated in varying spatial and temporal patterns defining the development of various body regions. In the adult body, Hox genes are among others responsible for driving the differentiation of tissue stem cells towards their respective lineages in order to repair and maintain the correct function of tissues and organs. Due to their involvement in the embryonic and adult body, they have been suggested to be useable for improving stem cell differentiations in vitro and in vivo. In many studies Hox genes have been found as driving factors in stem cell differentiation towards adipogenesis, in lineages involved in bone and joint formation, mainly chondrogenesis and osteogenesis, in cardiovascular lineages including endothelial and smooth muscle cell differentiations, and in neurogenesis. As life expectancy is rising, the demand for tissue reconstruction continues to increase. Stem cells have become an increasingly popular choice for creating therapies in regenerative medicine due to their self-renewal and differentiation potential. Especially mesenchymal stem cells are used more and more frequently due to their easy handling and accessibility, combined with a low tumorgenicity and little ethical concerns. This review therefore intends to summarize to date known correlations between natural Hox gene expression patterns in body tissues and during the differentiation of various stem cells towards their respective lineages with a major focus on mesenchymal stem cell differentiations. This overview shall help to understand the complex interactions of Hox genes and differentiation processes all over the body as well as in vitro for further improvement of stem cell treatments in future regenerative medicine approaches.
So far, sustainable HCI has mainly focused on the domestic context, but there is a growing body of work looking at the organizational context. As in the domestic context, these works still rest on psychological theories for behaviour change used for the domestic context. We supplement this view with an organizational theory-informed approach that adopts organizational roles as a key element. We will show how a role-based analysis could be applied to uncover information needs and to give em-ployee’s eco-feedback, which is linked to their tasks at hand. We illustrate the approach on a qualitative case study that was part of a broader, ongoing action research conducted in a German production company.
Schlussbericht HIGEDIS
(2015)
TinyECC 2.0 is an open source library for Elliptic Curve Cryptography (ECC) in wireless sensor networks. This paper analyzes the side channel susceptibility of TinyECC 2.0 on a LOTUS sensor node platform. In our work we measured the electromagnetic (EM) emanation during computation of the scalar multiplication using 56 different configurations of TinyECC 2.0. All of them were found to be vulnerable, but to a different degree. The different degrees of leakage include adversary success using (i) Simple EM Analysis (SEMA) with a single measurement, (ii) SEMA using averaging, and (iii) Multiple-Exponent Single-Data (MESD) with a single measurement of the secret scalar. It is extremely critical that in 30 TinyECC 2.0 configurations a single EM measurement of an ECC private key operation is sufficient to simply read out the secret scalar. MESD requires additional adversary capabilities and it affects all TinyECC 2.0 configurations, again with only a single measurement of the ECC private key operation. These findings give evidence that in security applications a configuration of TinyECC 2.0 should be chosen that withstands SEMA with a single measurement and, beyond that, an addition of appropriate randomizing countermeasures is necessary.
Semantic Image Segmentation Combining Visible and Near-Infrared Channels with Depth Information
(2015)
Image understanding is a vital task in computer vision that has many applications in areas such as robotics, surveillance and the automobile industry. An important precondition for image understanding is semantic image segmentation, i.e. the correct labeling of every image pixel with its corresponding object name or class. This thesis proposes a machine learning approach for semantic image segmentation that uses images from a multi-modal camera rig. It demonstrates that semantic segmentation can be improved by combining different image types as inputs to a convolutional neural network (CNN), when compared to a single-image approach. In this work a multi-channel near-infrared (NIR) image, an RGB image and a depth map are used. The detection of people is further improved by using a skin image that indicates the presence of human skin in the scene and is computed based on NIR information. It is also shown that segmentation accuracy can be enhanced by using a class voting method based on a superpixel pre-segmentation. Models are trained for 10-class, 3-class and binary classification tasks using an original dataset. Compared to the NIR-only approach, average class accuracy is increased by 7% for 10-class, and by 22% for 3-class classification, reaching a total of 48% and 70% accuracy, respectively. The binary classification task, which focuses on the detection of people, achieves a classification accuracy of 95% and true positive rate of 66%. The report at hand describes the proposed approach and the encountered challenges and shows that a CNN can successfully learn and combine features from multi-modal image sets and use them to predict scene labeling.
Simultaneous multifrequency radio observations of the Galactic Centre magnetar SGR J1745-2900
(2015)
Das Thema Prozessorganisation hat die gfo in den letzten Jahren intensiv begleitet und auf mehreren Tagungen eingehend diskutiert. Um den aktuellen Umsetzungsstand der Prozessorganisation in Deutschland zu untersuchen wurde im Jahr 2014 eine empirische Studie durchgeführt. Neben der Ist-Situation liefert die Studie Einsichten in Erwartungen über zukünftige Entwicklungen, Hindernisse und Erfolgsfaktoren der Einführung einer Prozessorganisation sowie zur Zielerreichung durch prozessorientierte Organisationen.
Sustainable development needs sustainable production and sustainable consumption. During the last decades the encouragement of sustainable production has been the focus of research and policy makers under the implicit assumption that the observable increasing ‘green’ values of consumers would also entail a growing sustainable consumption. However, it has been found that the actual purchasing behaviour often deviates from ‘green’ attitudes. This phenomenon is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications.