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The book starts with a social and cultural overview of the history of per-forming arts in Egypt until the beginning of the 20th century. The birth of the professional and institutionalised theatre and the connections with the foreign political domination until 1952 with the transformation of the ruling system into a republic. The state-owned theatre, its discourse, role and functions from the 1950's to the end of the 1960's and the socio-political conditions and legislative foundation. The rise of capitalism and the open market economy in 1970's till 1980's and its impact on the flour-ishing of the commercial theatre.
The study then moves towards focusing on the period from the 1980's till end of 1990's, the rise of the university theatre groups and students' movement as a political and cultural form of activism against the regime and the fundamentalist thinking. The relation of the gulf war in 1990 to-wards the development of the university theatre into professional theatre. The history of the independent performing arts movement from 1990's to 2010 as a model of transforming cultural production/management. The role of foreign cultural policy in supporting the development of the inde-pendent performing arts, and the creation of the Cairo Opera House and the Hanager Arts Centre.
The focus then goes to the analysis of the events of the revolution of 25 January 2011, the artists' advocacy and its forms, the lobbying and pres-sure groups from the independent performing arts scene to create new laws to support independent cultural productions and cultural justice, and to guarantee the basic connections to the articles of the human rights convention related to culture and the arts. In 2015 comes the establish-ment of the "Unit for the Support of Independent Theatre" which is con-sidered as a turning point in Egypt's legislation and perspective in the arts and cultural/political rights. The book concludes with a proposal for cultural policy in Egypt with a special focus on how to provide stability, freedom and growth for the independent theatre sector.
The EXPLAIN project (EXPLanatory interactive Artificial intelligence for INdustry) aims at enabling explainable Machine Learning in industry. MLOps (Machine Learning Operations) includes tools, practices, and processes for deploying ML (Machine Learning) in production. These will be extended by explainability methods as part of the project.
This study aims to determine to what extent MLOps is implemented by four project partner companies. Further, the study describes the ML use cases, MLOps software architecture, tools, and requirements in the companies perspective. Besides, requirements for a novel MLOps software architecture, including explainability methods, are collected.
As a result the interviews show that each of the interviewed industry partners use MLOps differently. Different tools and architectural patterns are used depending on the particular use case. Overall, most information we gathered focused on architecture decisions in the MLOps tool landscape used by the interviewed companies.
The discourse about pathways of sustainability transitions is dominated by two opposing approaches. On the one hand, the transition studies literature follows a green growth efficiency-driven approach and argues that technological innovations will pave the way to more sustainable modes of living. On the other hand, postcapitalist scholars reject the efficiency paradigm and advocate an alternative, sufficiency-driven turn to sustainability characterized by degrowth-oriented downscaling and rightsizing.
This habilitation thesis contributes to this field of research and investigates how transitions towards more sustainable paths can be initiated and fostered. It focuses on tourism in rural regions that have been growing intensely in recent years and are characterized by mass tourism causing ecological and socio-cultural pressure. The thesis thus analyses what influence particularly tourists and tourism businesses have on the production of rural space regarding sustainability and rural tourism resilience and what role rural regions may generally play in sustainability transition processes.
The study recognizes that tourists and tourism businesses have a strong influence on the production of rural space while their sustainability orientations are heterogeneous. Rural tourism resilience and sustainable change are challenged by the growing popularity of rural tourism and the still dominantly growth-oriented rural tourism sector. Future rural development paths will be positioned within a spectrum of green growth-oriented mass tourism on the one hand and degrowth-oriented tourism on the other hand. With respect to shared responsibilities of urban and rural regions, this thesis pleads for financial compensation as a degrowth-oriented incentive for those rural tourism regions that are willing to follow a concept of reduced use of economic resources for the sake of greater ecological and socio-cultural goals that are of value for our societies on different geographical scales.
Das neue Kinder- und Jugendstärkungsgesetz (KJSG) will die Rechte von jungen Menschen und Eltern in der Kinder- und Jugendhilfe nachhaltig stärken. Der neue § 4a SGB VIII hat zum Ziel, die Selbstvertretungen und Selbsthilfe von Adressat*innen anzuregen, zu fördern und diese in die Kinder- und Jugendhilfe strukturell einzubeziehen. Dies bedeutet, dass in der Kinder- und Jugendhilfe neben allen individuellen Hilfeentscheidungen auch zukünftig Organisations- und Strukturplanungen gemeinsam mit jungen Menschen und Eltern mit und ohne Behinderung ausgestaltet werden müssen. In einem Expert*innengespräch, das am 12.12.2022 von der Internationalen Gesellschaft für erzieherische Hilfen (IGfH) in Frankfurt am Main ausgerichtet wurde, trafen sich Fachvertreter*innen aus unterschiedlichen Verbänden, Selbstorganisationen und der Wissenschaft mit Know-how zu Selbstvertretungen, um erste Perspektiven für die Zukunft inklusiver und strukturell verankerter Selbstvertretungen zu entwickeln. Die Ausrichter*innen des Fachgespräches haben auf der Basis der Diskussionen 11 Thesen zur Absicherung und Weiterentwicklung der Selbstvertretungen ausgearbeitet und stellen diese zur Diskussion.
Automated machine learning represents the next generation of machine learning that involves efficiently identifying model hyperparameters and configurations that ensure decent generalization behavior beyond the training data. With a proper setup in place, considerable resources can be saved by practitioners and academics. Beyond naive approaches, e.g. random sampling or grid search, sequential model-based optimization has been at the forefront of solutions that attempt to optimize the black-box function representing the generalization surface, for example, the validation loss.
With the abundance of data and algorithm evaluations being available, transfer learning techniques and meta-knowledge can be utilized to further expedite hyperparameter optimization. In this thesis, we cover 4 ways in which meta-knowledge can be leveraged to improve hyperparameter optimization.
In the first part, we present two large-scale meta-datasets, i.e. a collection of hyperparameters and their respective response for a machine learning algorithm trained on several datasets. We describe in detail the implementation details and descriptive analytics that highlight the heterogeneity of the resulting response surface. The two meta-datasets are used as benchmark datasets upon which the subsequent methods developed in this thesis have been empirically evaluated.
In the second part, we introduce the first work that automates the process of learning meta-features, i.e. dataset characteristics, directly from the dataset distribution. Previously, meta-features required expert-domain knowledge and a lot of engineering to properly represent datasets as entities for a meta-learning task. Following this work, we integrate the meta-feature extractor as a module in the machine learning algorithm, and optimize it jointly for the meta-learning task, further promoting the benefits of differentiable meta-features. Finally, we carry over the concept of meta-feature learning in the absence of the underlying dataset. Specifically, we design a deep Gaussian kernel that allows for a richer representation of the attributes via non-linear transformation. The resulting surrogate is conditioned on landmark meta-features extracted from the history of task-specific evaluations.
In the third part, we formulate the problem of hyperparameter optimization as a Markov Decision Process. As such, we introduce the first paper on hyperparameter optimization in a reinforcement learning framework and define a novel transferable policy that acts as an acquisition function for hyperparameter optimization. Furthermore, we study the impact of planning in hyperparameter optimization through a novel non-myopic acquisition function.
Finally, we present hyperparameter optimization in a zero-shot setting. In contrast to sequential model-based optimization, the fastest way for HPO is by learning a zero-shot approach, that identifies the best configuration with a single trial. Our Zap-HPO approach outperforms the state-of-the-art in algorithm selection for deep learning pipelines that comprise a machine learning algorithm and its associated hyperparameters, given simple meta-features.
The University of Hildesheim owns many different software systems for teaching. So far,
no one has attempted to cover all systems and create an architectural description of e-learning at the University of Hildesheim. This report describes the applications relevant to education. These include software developed by the university, third-party tools provided by the university, cloud tools closely associated with the university, and tools provided by the university under contract. Implemented functionalities are explored,
and functional specifcations are described, including information about technical and operational requirements. Here, the software is primarily teaching tools. However, the report does not include software and development environments in which students are taught but rather tools that apply to teaching. The variety of tools in different courses makes it impossible to cover all the applications that are used by work groups or individuals.
The main goal of this investigation is to capture the university's e-learning state and describe the architecture - mainly to ease the development of applications for developers.
Further objectives are to identify new ideas and summarize current goals.
We conducted surveys of the teaching staff to determine the current status. Transcripts of interviews, tables provided by interviewed persons, and websites were used as references to prepare this document. We hope that future investigations will provide updates on current information and add information in this context.
Post- bzw. dekoloniale Perspektiven auf Tanzhistoriografie sind ein aktuell viel diskutiertes und zugleich wenig beforschtes Thema in der Tanzwissenschaft. Bisherige Studien fokussieren entweder die Beweglichkeit tanzgeschichtlicher Formationen oder schärfen den Blick für explizit politische Befragungen von Tanz in Theorie und Praxis. Anna Wieczorek entwickelt ein Analysemodell, das versucht beide Richtungen zusammenzubringen und dabei methodisch neue Wege erschließt. Anhand choreografischer Arbeiten von Faustin Linyekula und Trajal Harrell schlägt die Autorin ein Modell vor, dass kulturelle Muster und deren machtvolle Übersetzungen einbezieht und sie mit zeitlichen Relationierung historiografischer Forschung kombiniert. Beide Denkrichtungen werden über die Anfertigung eines Scores verbunden, der zugleich den methodisch konkreten Vorschlag dieser Studie liefert. Der Begriff Score stammt aus der Tanzpraxis und enthält bspw. Bewegungsanweisungen, die Tänzer*innen oder Performer*innen zur Generierung von Bewegung oder Choreographie nutzen. Für das hier vorgeschlagene Modell wird der Score zu einem operativen Begriff, der für die Analyse von Bewegung eingesetzt werden kann. Er ist dabei kein neutraler Übermittler, sondern durch ihn wird eine bestimmte Version der Choreographie abgebildet, die dann, in einem zweiten Schritt, in einen Text übersetzt wird. Demnach übersetzt sich tänzerisches Wissen in den Score, gleichzeitig wird der Score erst durch dieses Wissen hervorgebracht. Diese Wechselbeziehung bildet die relationale Grundannahme dieser Studie und führt zum Denkmodell für die post. bzw. dekoloniale Analyse beweglicher Prozesse im wortwörtlichen Sinn.
Recommender systems have been deployed in many diverse settings, and they aim to provide a personalized ranked list of items to users that they are likely to interact with. In order to provide an accurate list of items, models need to capture various aspects of the users' profiles, behaviors, and items' dynamics. Depending on the recommendation settings, these aspects can be mined from the different auxiliary information sources that might be readily available in these settings as side information. The more aspects being covered, the more accurate the learned user and item representations will be, improving prediction performance and overcoming various challenges such as sparse interaction data.
These auxiliary information sources might contain static attributes related to the users' and items' profiles or contain historical multi-relational implicit interactions between users and items, users and users, and items and items such as clicks, views, bought-together, and friendships. These interactions can be exploited to capture complex implicit relations that are usually not visible if the model only focuses on one user-item relationship.
Besides attributes and interaction data, auxiliary information might also contain contextual information that accompanies the interaction data, such as timestamps and locations. Incorporating such contextual information allows the models to comprehend the dynamics of users and items and learn the influence of time and environment.
In this thesis, we present four ways in which auxiliary information can be leveraged to improve the prediction performance of recommender systems and allow them to overcome many challenges.
Firstly we introduce an attribute-ware co-embedding model that can leverage user and item attributes along with a set of graph-based features for rating prediction. In particular, the model treats the user-item relation as a bipartite graph and constructs generic user and item attributes via the Laplacian of the co-occurrence graph. We also demonstrate that our attribute-ware model outperforms existing state-of-the-art attribute-aware recommender systems.
Next, we extend the model to handle different multi-relational interactions to overcome the challenges of having few and sparse interaction data between users and items. First, we extend the model by adding the capability to capture multi-relational interactions between the same entity types, particularly between users and users and between items and items. This is done by simultaneously scoring the different relations using a weighted joint loss. Later, we extend the model further by including the ability to accommodate different user and item interactions simultaneously by having an independent scoring function for each interaction type. The later extension allows the model to be employed in scenarios where the main relation between users and items is extremely sparse such as in auction settings which pose a significant challenge to traditional and state-of-the-art models.
Additionally, we introduce a sequential context and attribute-aware model that captures users' and items' dynamics through their sequential interaction patterns and their timestamps. The model can also capture various aspects of the users' and items' profiles through their static attributes and content information.
Finally, in the end, we also present a framework for optimizing ranking metrics directly, such as the Normalized Discounted Cumulative Gain (NDCG) using surrogate losses as an additional way of improving the models' performance.
Die documenta in Kassel als eine der bedeutendsten Ausstellungen für zeitgenössische Kunst wurde zunehmend populär für ein kunstinteressiertes Freizeitpublikum und erwies sich zugleich als besonders „vermittlungsbedürftig“, weil es für viele der Positionen noch keine vertrauten Rezeptionsmuster gibt. Dies gilt um so mehr für die documenta fifteen mit ihrem Anspruch, künstlerisch-politische Aktionen und Interventionen von Kunstschaffenden des globalen Südens zu diskutieren. Welche Erwartungen haben die Besucher*innen an Vermittlung auf der documenta, was macht für sie Qualität von Kunstvermittlung aus? Welche Auswirkung hat die Vermittlung auf ihre Rezeption der documenta sowie ihr Verständnis von Kunst?
Dies sind zentrale Fragen einer empirischen Studie von Studierenden des Masters Kulturvermittlung der Universität Hildesheim. Hierfür wurde ein Mixed-Methods-Ansatz auf Basis von Erkenntnissen zu Kunstvermittlung und Publikum vorhergehender documenta-Ausstellungen entwickelt. Umfangreiche Daten aus qualitativen Leitfadeninterviews, ergänzt durch eine quantitative Befragung, liefern tiefergehende Einblicke in Teilnahmemotivation, Erwartungshaltung und Gütekriterien von Kunstvermittlungsangeboten aus Sicht des Publikums.
Mit dem Inkrafttreten des Kinder- und Jugendstärkungsgesetzes (KJSG) im Jahr 2021 hat der Gesetzgeber die Einführung von Verfahrenslotsen beschlossen. Dieser Beitrag gibt einen kurzen Einblick in ihre Verortung und Aufgaben. Welche Herausforderungen sind, vor allem für Jugendämter, mit dieser Stelle verbunden und welche Umsetzungsmodelle werden in der Praxis bereits entwickelt und diskutiert?
