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Handbuch China-Kompetenzen
(2022)
Angesichts des rasanten wirtschaftlichen und wissenschaftlichen Aufstrebens Chinas offenbart sich an deutschen Hochschulen ein deutlicher Mangel an China-Kompetenzen auf allen Ebenen. Wie sind chinesische Kooperationspartner*innen einzuschätzen? Wie sollten Studierende ausgebildet werden, damit sie in Zukunft informiert und (selbst-)bewusst zusammenarbeiten können? Wie kann erreicht werden, dass chinesische Studierende ihre Zeit in Deutschland als akademisch und persönlich bereichernd empfinden? Best practice-Beispiele von elf deutschen Hochschulen geben Anregungen, die sich auch übergreifend auf verschiedene Bildungseinrichtungen und Partnerländer übertragen lassen.
Lidar sensors are widely used for environmental perception on autonomous robot vehicles (ARV). The field of view (FOV) of Lidar sensors can be reshaped by positioning plane mirrors in their vicinity. Mirror setups can especially improve the FOV for ground detection of ARVs with 2D-Lidar sensors. This paper presents an overview of several geometric designs and their strengths for certain vehicle types. Additionally, a new and easy-to-implement calibration procedure for setups of 2D-Lidar sensors with mirrors is presented to determine precise mirror orientations and positions, using a single flat calibration object with a pre-aligned simple fiducial marker. Measurement data from a prototype vehicle with a 2D-Lidar with a 2 m range using this new calibration procedure are presented. We show that the calibrated mirror orientations are accurate to less than 0.6° in this short range, which is a significant improvement over the orientation angles taken directly from the CAD. The accuracy of the point cloud data improved, and no significant decrease in distance noise was introduced. We deduced general guidelines for successful calibration setups using our method. In conclusion, a 2D-Lidar sensor and two plane mirrors calibrated with this method are a cost-effective and accurate way for robot engineers to improve the environmental perception of ARVs.
Code-based cryptosystems are promising candidates for post-quantum cryptography. Recently, generalized concatenated codes over Gaussian and Eisenstein integers were proposed for those systems. For a channel model with errors of restricted weight, those q-ary codes lead to high error correction capabilities. Hence, these codes achieve high work factors for information set decoding attacks. In this work, we adapt this concept to codes for the weight-one error channel, i.e., a binary channel model where at most one bit-error occurs in each block of m bits. We also propose a low complexity decoding algorithm for the proposed codes. Compared to codes over Gaussian and Eisenstein integers, these codes achieve higher minimum Hamming distances for the dual codes of the inner component codes. This property increases the work factor for a structural attack on concatenated codes leading to higher overall security. For comparable security, the key size for the proposed code construction is significantly smaller than for the classic McEliece scheme based on Goppa codes.
The growing error rates of triple-level cell (TLC) and quadruple-level cell (QLC) NAND flash memories have led to the application of error correction coding with soft-input decoding techniques in flash-based storage systems. Typically, flash memory is organized in pages where the individual bits per cell are assigned to different pages and different codewords of the error-correcting code. This page-wise encoding minimizes the read latency with hard-input decoding. To increase the decoding capability, soft-input decoding is used eventually due to the aging of the cells. This soft-decoding requires multiple read operations. Hence, the soft-read operations reduce the achievable throughput, and increase the read latency and power consumption. In this work, we investigate a different encoding and decoding approach that improves the error correction performance without increasing the number of reference voltages. We consider TLC and QLC flashes where all bits are jointly encoded using a Gray labeling. This cell-wise encoding improves the achievable channel capacity compared with independent page-wise encoding. Errors with cell-wise read operations typically result in a single erroneous bit per cell. We present a coding approach based on generalized concatenated codes that utilizes this property.
Der Urban-Heat-Island-Effekt in Städten wird sich, angetrieben durch den globalen Klimawandel, weiter verstärken. Dem können städtebauliche Maßnahmen mildernd entgegenwirken.
Aus diesem Grund soll in dieser Bachelorarbeit im Rahmen des CoKLIMAx-Projekts eine Maßnahmentoolbox für resiliente Stadtplanung erstellt werden. Im Fokusbereich Wärme werden Maßnahmen näher betrachtet, die dazu beitragen können, Städte bezüglich zu erwartender vermehrter Hitzeereignisse zukünftig klimaresilienter zu gestalten.
Ziel dieser Arbeit ist die Zusammenstellung ausgewählter, konkreter Hitze-Resilienz-Maßnahmen für den städtischen Raum in einer Maßnahmentoolbox. Mithilfe dieser Toolbox sollen Möglichkeiten aufgezeigt werden, die Auswirkungen von Hitzeextremereignissen auf den städtischen Raum durch städtebauliche Maßnahmen zu minimieren beziehungsweise zu vermeiden.
Adressaten sollen in erster Linie Behörden auf kommunaler Ebene sein. Diese sollen bezüglich zunehmender Hitzeextremereignisse und ihrer negativen Auswirkungen auf Mensch, Wirtschaft sowie Gebäude und Infrastruktur, besser vorbereitet bzw. handlungsfähiger gemacht werden.
Mutual Information Analysis for Generalized Spatial Modulation Systems With Multilevel Coding
(2022)
Generalized Spatial Modulation (GSM) enables a trade-off between very high spectral efficiencies and low hardware costs for massive MIMO systems. This is achieved by transmitting information via the selection of active antennas from a set of available antennas besides the transmission of conventional data symbols. GSM systems have been investigated concerning various aspects like suitable signal constellations, efficient detection algorithms, hardware implementations, spatial precoding, and error control coding. On the other hand, determining the capacity of GSM is challenging because no closed-form expressions have been found so far. This paper investigates the mutual information for different GSM variants. We consider a multilevel coding approach, where the antenna selection and IQ modulation are encoded independently. Combined with multistage decoding, such an approach enables low-complexity capacity-achieving coded modulation. The influence of the data symbols on the mutual information is illuminated. We analyze the portions of mutual information related to antenna selection and the IQ modulation processes which depend on the GSM variant and the signal constellation. Moreover, the potential of spatial modulation for massive MIMO systems with many transmit antennas is investigated. Especially in systems with many transmit antennas much information can be conveyed by antenna selection.
This research project has been awarded as part of the research competition organized by Connect2Recover, which is a global initiative by the International Telecommunication Union (ITU) with the priority of reinforcing and strengthening the digital infrastructure and ecosystems of developing countries. Carried out by an international and transdisciplinary research consortium, the project sets out to analyze the prospects of digital federation and data sharing within the context of Botswana. Considering the country’s stage of economic and digital development, the project team identified Botswana’s smallholder agricultural sector as the most important area of digital transformation given the development need of the country’s primary sector.
Derived from semi-structured interviews, a focus group, as well as secondary research, the project team developed a digital transformation roadmap based on three development stages: (a) crowdfarming pilot, (b) crowdfarming marketplace, and (c) digital ecosystem for smallholder agriculture. Based on a detailed review of Botswana’s smallholder agriculture and the government’s digitalization strategy, the report envisions each phase, especially the pilot project, in terms of a minimal viable product. This is to consider the low level of digital penetration of Botswana’s primary sector, while providing an incentive to connect smallholders with consumers, traders, and retailers.
The project team has been successful in receiving commitment from actual smallholder farmers, the farmer association and government, as well as support for the idea of developing a crowdfarming marketplace as a novel production model and, eventually, a digital agriculture ecosystem for smallholder farmers, livestock producers, and agricultural technology companies and start-ups. The report is a proposal for a phase-one pilot project with the objective to advance smallholder agribusiness in Botswana.
Purpose
The goal of this research survey was to propose an entrepreneurship education model for students in higher education institutions.
Methodology
A questionnaire was distributed to 246 randomly sampled students at the Universitas Negeri Jakarta. The data was analyzed through Structural Equation Modeling to study the variables of entrepreneurship education for higher education students and examine whether it can be predicted by the university leadership as a facilitator of entrepreneurial culture, university departments as promoters of entrepreneurial skills, and university research as an incubator of local business
development.
Findings
The results show that university leadership as a facilitator of entrepreneurial culture is supported by the university leadership’s fostering a culture of entrepreneurial thinking. It was also evident that the university placed sufficient emphasis on entrepreneurial education, and it successfully motivated lecturers to embrace entrepreneurship education, and students to embrace entrepreneurship education. The results also indicated that university departments acted as promoters of entrepreneurial skills and stimulated students to attain sufficient entrepreneurial skills during their university education. Lastly, the university research also proved as an incubator of local business development and was found influenced by the university conducting research projects with local
private sector businesses and supporting graduates planning to launch start-ups.
Implications to Research and Practice
The survey results will provide valuable policy insights to improve entrepreneurship education. The university faculty and students would have opportunities to gain practical experience in local private sector businesses. The model of entrepreneurship education proposed herein can be applied for higher education students.
Ein Wandel weg von der linearen und hin zu einer Kreislaufwirtschaft, wie man ihn bereits in verschiedenen Bereichen erkennen kann, hat positive Auswirkungen auf das Klima und die Umwelt. Die Baubranche könnte durch ihre hohe Ressourcen- und Energieintensität ein wichtiger Beitrag zur Klima- und Umweltschonung durch Kreislaufpraktiken leisten. Im Fokus sollte nicht mehr nur eine effiziente Gebäudehülle stehen, sondern eine ganzheitliche Nachhaltigkeitsbetrachtung.
Aufgrund mangelnden Bewusstseins, fehlender rechtlicher Rahmenbedingungen, Organisationen, Softwaretools und fehlender Anreize durch Förderungen oder Geschäftsmodelle kann und wird eine ganzheitliche Kreislaufwirtschaft derzeit noch nicht in der Baubranche umgesetzt. Ein weiterer bedeutsamer Grund sind fehlende Materialpässe und deren Umsetzungsmöglichkeiten in der Praxis.
Ziel dieser Arbeit ist es, die Lücke zwischen den Anforderungen an Materialpässe und deren Umsetzung in der Praxis, speziell für WeberHaus und somit den Holz-Fertighausbau, frühzeitig zu schließen. Durch Experteninterviews werden der Ist-Zustand des Material- und Informationsflusses beschrieben und gleichzeitig die Themen Kreislaufwirtschaft, Rückverfolgung und Materialpässe mit den Mitarbeitern diskutiert und nähergebracht. Aus dem Ist- Zustand des Material- und Informationsflusses werden Möglichkeiten einer Umsetzung in Form von zwei Varianten für Materialpässe geliefert, welche die zuvor festgelegten Anforderungen erfüllen.
Zur Beschreibung des Materialflusses hat es sich als sinnvoll erwiesen, eine Einteilung des gesamten Unternehmens auf Gebäude- und Elementebene vorzunehmen. Der Informationsfluss wird für den Materialpass hauptsächlich durch die vorhandenen Softwaresysteme Bentley, Dietrich´s, SAP und WeKo bestimmt. Um die Anforderungen, die an die Materialpässe gestellt werden, bestmöglich und mit geringem Aufwand erfüllen zu können, stellt sich BIM in Kombination mit der Plattform Madaster als sinnvolles Instrument heraus. Hierzu sind jedoch aufwendige Fachmodelle oder ein Koordinationsmodell nötig, welche von WeberHaus noch nicht vollständig realisiert werden. Als Übergangslösung bietet sich ein Materialpass auf Elementebene an, der durch diese Betrachtung standardisiert und ergänzt werden kann. Eine Ergänzung dieser Variante durch QR-Codes bietet zusätzlich eine direkte Verknüpfung von Informationen mit Bauteilen.
Image novelty detection is a repeating task in computer vision and describes the detection of anomalous images based on a training dataset consisting solely of normal reference data. It has been found that, in particular, neural networks are well-suited for the task. Our approach first transforms the training and test images into ensembles of patches, which enables the assessment of mean-shifts between normal data and outliers. As mean-shifts are only detectable when the outlier ensemble and inlier distribution are spatially separate from each other, a rich feature space, such as a pre-trained neural network, needs to be chosen to represent the extracted patches. For mean-shift estimation, the Hotelling T2 test is used. The size of the patches turned out to be a crucial hyperparameter that needs additional domain knowledge about the spatial size of the expected anomalies (local vs. global). This also affects model selection and the chosen feature space, as commonly used Convolutional Neural Networks or Vision Image Transformers have very different receptive field sizes. To showcase the state-of-the-art capabilities of our approach, we compare results with classical and deep learning methods on the popular dataset CIFAR-10, and demonstrate its real-world applicability in a large-scale industrial inspection scenario using the MVTec dataset. Because of the inexpensive design, our method can be implemented by a single additional 2D-convolution and pooling layer and allows particularly fast prediction times while being very data-efficient.