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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.
The phenomenon of the deviation between purchase attitudes and actual buying behaviour of responsible consumers 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. The last three barriers are mainly of a psychological nature. Especially the low-involvement feature of food products due to daily purchase routines and relatively low prices tends to result in fast, automatic and subconscious decisions based on a so-called human mental system 1, derived from Daniel Kahneman’s (Nobel-Prize laureate in Behavioural Economics) model in behavioural psychology. In contrast, the human mental system 2 is especially important for the transformations of individual behaviour towards a more sustainable consumption. Decisions based on the human mental system 2 are slow, logical, rational, conscious and arduous. This so-called dual action model also influences the reliability of responses in consumer surveys. It seems that the consumer behaviour is the most unstable and unpredictable part of the entire supply chain and requires special attention. Concrete measures to influence consumer behaviour towards sustainable consumption are highly complex. Reviews of interdisciplinary research literature on behavioural psychology, behavioural economics and consumer behaviour and an empirical analysis of selected countries worldwide with a view to sustainable food are presented. The example of Denmark serves as a ‘best practice’ case study to illustrate how sustainable food consumption can be encouraged. It demonstrates that common efforts and a shared responsibility of consumers, business, interdisciplinary researchers, mass media and policy are needed. It takes pioneers of change who succeed in assembling a ‘critical mass’ willing to increase its ‘sustainable’ behaviour. Considering the strong psychological barriers of consumers and the continuing low market share of organic food, proactive policy measures would be conducive to foster the personal responsibility of the consumers and offer incentives towards a sustainable production. Also, further self-obligations of companies (Corporate Social Responsibility – CSR) as well as more transparency and simplification of reliable labels and certifications are needed to encourage the process towards a sustainable development.
Introduction: After cellulose, lignin represents the most abundant biopolymer on earth that accounts for up to 18-35 % by weight of lignocellulose biomass. Today, it is a by-product of the paper and pulping industry. Although lignin is available in huge amounts, mainly in form of so called black liquor produced via Kraft-pulping, processes for the valorization of lignin are still limited [1]. Due to its hyperbranched polyphenol-like structure, lignin gained increasing interest as biobased building block for polymer synthesis [2]. The present work is focused on extraction and purification of lignin from industrial black liquor and synthesis of lignin-based polyurethanes.
Mesenchymal stem cells (MSCs) are an attractive cell source for Regenerative Dentistry in particular due to their ability to differentiate towards osteoblasts, among other lineages. Tooth and jaw bone loss are frequent sequelae of traumatic and pathological conditions in both the young and the elderly and must be met by appropriate prosthetic replacements. For successful osseointegration of the dental implant a sufficient bone level is necessary. Besides the utilization of bone autografts or synthetic biomaterials, medical research is more and more focused on the utilization of MSCs. Compared to cells obtained from liposuction material, ectomesenchymal stem cells derived from the head area e.g. out of dental follicles or particulate, non-vascularized bone chips show a higher differentiation potential towards osteoblasts.