Hasil untuk "Art"

Wei Hsin Chen, Jiang Peng, X. Bi

Sina Parhizi, H. Lotfi, A. Khodaei et al.

The significant benefits associated with microgrids have led to vast efforts to expand their penetration in electric power systems. Although their deployment is rapidly growing, there are still many challenges to efficiently design, control, and operate microgrids when connected to the grid, and also when in islanded mode, where extensive research activities are underway to tackle these issues. It is necessary to have an across-the-board view of the microgrid integration in power systems. This paper presents a review of issues concerning microgrids and provides an account of research in areas related to microgrids, including distributed generation, microgrid value propositions, applications of power electronics, economic issues, microgrid operation and control, microgrid clusters, and protection and communications issues.

A. Moors, P. Ellsworth, K. Scherer et al.

B. Meerbeek, K. Yoshihara, Y. Yoshida et al.

Jose Antonio Urigüen, Begonya García-Zapirain Soto

J. Horner

Guoqiang Zhang, B. Patuwo, M. Hu

M. Zeidner

Brian Steensland, Jerry Z. Park, Mark Regnerus et al.

E. Gustafson

A. Salgado, O. Coutinho, R. Reis

Although several major progresses have been introduced in the field of bone regenerative medicine during the years, current therapies, such as bone grafts, still have many limitations. Moreover, and in spite of the fact that material science technology has resulted in clear improvements in the field of bone substitution medicine, no adequate bone substitute has been developed and hence large bone defects/injuries still represent a major challenge for orthopaedic and reconstructive surgeons. It is in this context that TE has been emerging as a valid approach to the current therapies for bone regeneration/substitution. In contrast to classic biomaterial approach, TE is based on the understanding of tissue formation and regeneration, and aims to induce new functional tissues, rather than just to implant new spare parts. The present review pretends to give an exhaustive overview on all components needed for making bone tissue engineering a successful therapy. It begins by giving the reader a brief background on bone biology, followed by an exhaustive description of all the relevant components on bone TE, going from materials to scaffolds and from cells to tissue engineering strategies, that will lead to "engineered" bone. Scaffolds processed by using a methodology based on extrusion with blowing agents.

R. J. Cline, K. M. Haynes

M. J. Antal, M. Grønli

R. Kanter

K. Ho, S. Newman

J. Labadie

David Stutz, Alexander Hermans, B. Leibe

Abstract Superpixels group perceptually similar pixels to create visually meaningful entities while heavily reducing the number of primitives for subsequent processing steps. As of these properties, superpixel algorithms have received much attention since their naming in 2003 (Ren and Malik, 2003). By today, publicly available superpixel algorithms have turned into standard tools in low-level vision. As such, and due to their quick adoption in a wide range of applications, appropriate benchmarks are crucial for algorithm selection and comparison. Until now, the rapidly growing number of algorithms as well as varying experimental setups hindered the development of a unifying benchmark. We present a comprehensive evaluation of 28 state-of-the-art superpixel algorithms utilizing a benchmark focussing on fair comparison and designed to provide new insights relevant for applications. To this end, we explicitly discuss parameter optimization and the importance of strictly enforcing connectivity. Furthermore, by extending well-known metrics, we are able to summarize algorithm performance independent of the number of generated superpixels, thereby overcoming a major limitation of available benchmarks. Furthermore, we discuss runtime, robustness against noise, blur and affine transformations, implementation details as well as aspects of visual quality. Finally, we present an overall ranking of superpixel algorithms which redefines the state-of-the-art and enables researchers to easily select appropriate algorithms and the corresponding implementations which themselves are made publicly available as part of our benchmark at http://www.davidstutz.de/projects/superpixel-benchmark/ .

Marija Griniuk

Through my work as an artist, educator, and activist, I aim to promote the interconnectedness of arts, management, creativity, curating, research, and technology by developing courses for art academies, art students, and interdisciplinary students at universities. I believe that future university and art academy education will increasingly integrate interdisciplinarity, combining fields such as management, creativity, technology (including artificial intelligence), curating, and other disciplines. This approach aligns with the interdisciplinary nature of professional life after graduation, whether one pursues a career as an artist or as a director of an institution. I reference both the art academy and university environments due to my experience as a lecturer in both settings. The article explores the relationship between authentic leadership and creativity within the context of university pedagogy, utilizing a reflexive research method based on a case study of creativity education. This case study focuses solely on the university environment, specifically on teaching creativity to interdisciplinary groups of students. My experience as a lecturer contains teaching artists, performers, and interdisciplinary students at both the Bachelor of Arts and Master of Arts levels. Data includes my notes as a facilitator-lecturer, as well as the creative output and feedback from the interdisciplinary student groups. This data is analyzed using qualitative methods. The case study, derived from a Digital Creativity course, is examined speculatively to assess how the skills acquired may impact students post-graduation. As I was not in contact with students after the course ended, observations are limited to the processes observed during the course itself. The research question addressed is: how can digital learning of authentic leadership and creativity be facilitated within university pedagogy to create a safe and empathetic learning environment for students? Leadership is discussed from the perspective of authentic leadership and its relationship to creativity. Digital literacy is framed as critical thinking and responsibility in the context of collaboration with non-human entities, such as artificial intelligence. This study is relevant for university and art academy professionals working in cross-disciplinary contexts related to authentic leadership and creativity.

Ming Han, Ge Sun, Paul F. Nealey et al.

Abstract Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data, for ML training. In this study, we report a data-efficient, deep-learning framework for molecular discovery that integrates a coarse-grained functional-group representation with a self-attention mechanism to capture intricate chemical interactions. Our approach exploits group-contribution concepts to create a graph-based intermediate representation of molecules, serving as a low-dimensional embedding that substantially reduces the data demands typically required for training. Using a self-attention mechanism to learn the subtle but highly relevant chemical context of functional groups, the method proposed here consistently outperforms existing approaches for predictions of multiple thermophysical properties. In a case study focused on adhesive polymer monomers, we train on a limited dataset comprising only 6,000 unlabeled and 600 labeled monomers. The resulting chemistry prediction model achieves over 92% accuracy in forecasting properties directly from SMILES strings, exceeding the performance of current state-of-the-art techniques. Furthermore, the latent molecular embedding is invertible, enabling the design pipeline to automatically generate new monomers from the learned chemical subspace. We illustrate this functionality by targeting several properties, including high and low glass transition temperatures (Tg), and demonstrate that our model can identify new candidates with values that surpass those in the training set. The ease with which the proposed framework navigates both chemical diversity and data scarcity offers a promising route to accelerate and broaden the search for functional materials.

Jarief Farabi, Christos Mourouzidis, Pericles Pilidis

Hydrogen as fuel in civil aviation gas turbines is promising due to its no-carbon content and higher net specific energy. For an entry-level market and cost-saving strategy, it is advisable to consider reusing existing engine components whenever possible and retrofitting existing engines with hydrogen. Feasible strategies of retrofitting state-of-the-art Jet A-1 fuelled turbofan engines with hydrogen while applying minimum changes to hardware are considered in the present study. The findings demonstrate that hydrogen retrofitted engines can deliver advantages in terms of core temperature levels and efficiency. However, the engine operability assessment showed that retrofitting with minimum changes leads to a ~5% increase in the HP spool rotational speed for the same thrust at take-off, which poses an issue in terms of certification for the HP spool rotational speed overspeed margin.