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In 2015, Google engineer Alexander Mordvintsev presented DeepDream as technique to visualise the feature analysis capabilities of deep neural networks that have been trained on image classification tasks. For a brief moment, this technique enjoyed some popularity among scientists, artists, and the general public because of its capability to create seemingly hallucinatory synthetic images. But soon after, research moved on to generative models capable of producing more diverse and more realistic synthetic images. At the same time, the means of interaction with these models have shifted away from a direct manipulation of algorithmic properties towards a predominance of high level controls that obscure the model's internal working. In this paper, we present research that returns to DeepDream to assess its suit-ability as method for sound synthesis. We consider this research to be necessary for two reasons: it tackles a perceived lack of research on musical applications of DeepDream, and it addresses DeepDream's potential to combine data driven and algorithmic approaches. Our research includes a study of how the model architecture, choice of audio data-sets, and method of audio processing influence the acoustic characteristics of the synthesised sounds. We also look into the potential application of DeepDream in a live-performance setting. For this reason, the study limits itself to models consisting of small neural networks that process time-domain representations of audio. These models are resource-friendly enough to operate in real time. We hope that the results obtained so far highlight the attractiveness of Deep-Dream for musical approaches that combine algorithmic investigation with curiosity driven and open ended exploration.
This paper describes the authors' first experiments in creating an artificial dancer whose movements are generated through a combination of algorithmic and interactive techniques with machine learning. This approach is inspired by the time honoured practice of puppeteering. In puppeteering, an articulated but inanimate object seemingly comes to live through the combined effects of a human controlling select limbs of a puppet while the rest of the puppet's body moves according to gravity and mechanics. In the approach described here, the puppet is a machine-learning-based artificial character that has been trained on motion capture recordings of a human dancer. A single limb of this character is controlled either manually or algorithmically while the machine-learning system takes over the role of physics in controlling the remainder of the character's body. But rather than imitating physics, the machine-learning system generates body movements that are reminiscent of the particular style and technique of the dancer who was originally recorded for acquiring training data. More specifically, the machine-learning system operates by searching for body movements that are not only similar to the training material but that it also considers compatible with the externally controlled limb. As a result, the character playing the role of a puppet is no longer passively responding to the puppeteer but makes movement decisions on its own. This form of puppeteering establishes a form of dialogue between puppeteer and puppet in which both improvise together, and in which the puppet exhibits some of the creative idiosyncrasies of the original human dancer.
Generative machine learning models for creative purposes play an increasingly prominent role in the field of dance and technology. A particularly popular approach is the use of such models for generating synthetic motions. Such motions can either serve as source of ideation for choreographers or control an artificial dancer that acts as improvisation partner for human dancers. Several examples employ autoencoder-based deep-learning architectures that have been trained on motion capture recordings of human dancers. Synthetic motions are then generated by navigating the autoencoder's latent space. This paper proposes an alternative approach of using an autoencoder for creating synthetic motions. This approach controls the generation of synthetic motions on the level of the motion itself rather than its encoding. Two different methods are presented that follow this principle. Both methods are based on the interactive control of a single joint of an artificial dancer while the other joints remain under the control of the autoencoder. The first method combines the control of the orientation of a joint with iterative autoencoding. The second method combines the control of the target position of a joint with forward kinematics and the application of latent difference vectors. As illustrative example of an artistic application, this latter method is used for an artificial dancer that plays a digital instrument. The paper presents the implementation of these two methods and provides some preliminary results.
Strings P
(2021)
Strings is an audiovisual performance for an acoustic violin and two generative instruments, one for creating synthetic sounds and one for creating synthetic imagery. The three instruments are related to each other conceptually , technically, and aesthetically by sharing the same physical principle, that of a vibrating string. This submission continues the work the authors have previously published at xCoAx 2020. The current submission briefly summarizes the previous publication and then describes the changes that have been made to Strings. The P in the title emphasizes, that most of these changes have been informed by experiences collected during rehearsals (in German Proben). These changes have helped Strings to progress from a predominantly technical framework to a work that is ready for performance.
Strings
(2020)
This article presents the currently ongoing development of an audiovisual performance work with the title Strings. This work provides an improvisation setting for a violinist, two laptop performers, and two generative systems. At the core of Strings lies an approach that establishes a strong correlation among all participants by means of a shared physical principle. The physical principle is that of a vibrating string. The article discusses how this principle is used in both natural and simulated forms as main interaction layer between all performers and as natural or generative principle for creating audio and video.
Variable refrigerant flow (VRF) and variable air volume (VAV) systems are considered among the best heating, ventilation, and air conditioning systems (HVAC) thanks to their ability to provide cooling and heating in different thermal zones of the same building. As well as their ability to recover the heat rejected from spaces requiring cooling and reuse it to heat another space. Nevertheless, at the same time, these systems are considered one of the most energy-consuming systems in the building. So, it is crucial to well size the system according to the building’s cooling and heating needs and the indoor temperature fluctuations. This study aims to compare these two energy systems by conducting an energy model simulation of a real building under a semi-arid climate for cooling and heating periods. The developed building energy model (BEM) was validated and calibrated using measured and simulated indoor air temperature and energy consumption data. The study aims to evaluate the effect of these HVAC systems on energy consumption and the indoor thermal comfort of the building. The numerical model was based on the Energy Plus simulation engine. The approach used in this paper has allowed us to reach significant quantitative energy saving along with a high level of indoor thermal comfort by using the VRF system compared to the VAV system. The findings prove that the VRF system provides 46.18% of the annual total heating energy savings and 6.14% of the annual cooling and ventilation energy savings compared to the VAV system.
The increasing diffusion of rapidly developing AI technologies led to the idea of the experiment to combine TRIZ-based automated idea generation with the natural language processing tool ChatGPT, using the chatbot to interpret the automatically generated elementary solution principles. The article explores the opportunities and benefits of a novel AI-enhanced approach to teaching systematic innovation, analyses the learning experience, identifies the factors that affect students' innovation and problem-solving performance, and highlights the main difficulties students face, especially in interdisciplinary problems.
Inner Congo
(2023)
This research-creation project, part of the DE\GLOBALIZE artistic research cycle presented at the #IFM2022 Conference, investigates the complexities of Congo violence, care, and colonialism. Drawing on Michel Serres' metaphor of the great estuaries, the study explores the topology of interactive documentaries, blending theory, emotion, and personal experiences. Accessible through the interactive web documentation at http://deglobalize.com, the platform offers a media-archaeological archive for speculative ethnography, enabling the forensic processing of single documents in line with actor-network theory.
Enhancing engineering creativity with automated formulation of elementary solution principles
(2023)
The paper describes a method for the automated formulation of elementary creative stimuli for product or process design at different levels of abstraction and in different engineering domains. The experimental study evaluates the impact of structured automated idea generation on inventive thinking in engineering design and compares it with previous experimental studies in educational and industrial settings. The outlook highlights the benefits of using automated ideation in the context of AI-assisted invention and innovation.
Established robot manufacturers have developed methods to determine and optimize the accuracy of their robots. These methods vary from robot manufacturers to their competitors. Due to the lack of published data, a comparison of robot performance is difficult. The aim of this article is to find methods to evaluate important characteristics of a robot with an accurate and cost-effective setup. A laser triangulation sensor and geometric referenced spheres were used as a base to compare the robot performance.
The paper compares different anti-windup strategies for the current control of inverter-fed permanent magnet synchronous machines (PMSM) controlled by pulse-width modulation. In this respect, the focus is on the drive behavior with a relatively large product of stator frequency and sampling time. A requirement for dynamically high-quality anti-windup measures is, among other things, a sufficiently accurate decoupling of the stator current direct axis and quadrature axis components even at high stator frequencies. Discrete-time models of the electrical subsystem of the PMSM are well suited for this purpose, of which the method found to be the most accurate in a preliminary investigation is used as the basis for all anti-windup methods examined. Simulation studies and measurement results document the performance of the compared methods.
Digital, virtual environments and the metaverse are rapidly taking shape and will generate disruptive changes in the areas of ethics, privacy, safety, and how the relationships between human beings will be developed. To uncover some of some of the implications that will impact those areas, this study investigates the perceptions of 101 younger people from the generations Y and Z. We present a first exploratory analysis of the findings, focusing on knowledge and self-perception. Results show that these young generations are seriously doubting their knowledge on the metaverse and virtual worlds – regarding both the definition and the usage. It is interesting to see only a medium confidence level, considering that the participants are young and from an academic environment, which should increase their interest in and the affinity towards virtual worlds. Males from both generations perceive themselves as significantly more knowledgeable than females. Regarding a fitting definition, almost 40% agreed on the metaverse as a “universal and immersive virtual world that is made accessible using virtual reality and augmented reality technologies”. Regarding the topic in general, several participants (almost 40%) considered themselves sceptics or “just” users (38%). Interestingly, generation Y participants were more likely than the younger generation Z participants to identify themselves as early adopters or innovators. In result, the considerable amount of “mixed feelings” regarding digital, virtual environments and the metaverse shows that in-depth studies on the perception of the metaverse as well as its ethical and integrity implications are required to create more accessible, inclusive, safe, and inclusive digital, virtual environments.
Als Fortsetzung des FHOP-Projektes wurde an der Fachhochschule Offenburg auf Basis des bestehenden Mikroprozessorkerns im Rahmen einer Diplomarbeit ein Mikrocontroller in ES2-0.7 μm-Technologie entworfen. Der Controller wurde modular aufgebaut mit den Komponenten: FHOP-Mikroprozessor, Buscontroller, Waitstate-Chipselect-Einheit, 16x16 Bit Multiplizierer, 2KB ROM, 256 Byte RAM, Watchdog, PIO mit 16 konfigurierbaren Ports, SIO, 2 Timer und ein Interruptcontroller für 8 Interrputquellen.
Der Chip benötigt bei einer Komplexität von ca. 65400 Transistoren eine Siliziumfläche von etwa 27 mm². Er wurde im September 1996 zur Fertigung gegeben und mittlerweile erfolgreich getestet. Das interne ROM des Mikrocontrollers enthält das BIOS sowie ein Testprogramm. Zur Erstellung der Software steht eine komplette Entwicklungsumgebung zur Verfügung. Sämtliche Komponenten stehen im FHOP-Design-Kit in Kürze zur Verfügung.
Nach dem Nachweis der Funktionalität des an der Fachhochschule Offenburg entwickelten Mikroprozessorkernels FHOP (First Homemade Operational Processor), wird eine Anwendung des Kernels in einem Applikationschip beschrieben.
Der Thermologger-ASIC soll mit Hilfe eines Temperatursensors die Umgebungstemperatur bei technischen Prozessen in regelmäßigen Zeitabständen erfassen und abspeichern. Die Meßwerte werden bei Bedarf ber eine serielle Schnittstelle des Thermologger-ASICs an einen PC übertragen und ausgewertet. Zur Verringerung der Leistungsaufnahme wird zwischen zwei Temperaturmessungen in einen Power-Down-Mode geschaltet.
Der ASIC soll später in einer Chipkarte integriert werden.
Im Frühjahr 1995 entstand die Idee, einen Lottozahlengenerator als Demonstrations- und Studienobjekt, für die Anwendung komplexer digitaler Entwurfsmethoden, zu entwerfen. Mit Hilfe der Schaltung ist es möglich, 6 verschiedene Zahlen zufällig aus 49 Zahlen zu ermitteln. Bei der Ziehung der einzelnen Zahlen werden verschiedene Töne und Melodien erzeugt. Die Schaltung ist so konzipiert, daß eine einfache Bedienung möglich ist. Der Chip wurde als Standardzellen-Entwurf mit einer Fläche von ca. 7 um² geroutet.
An der Fachhochschule Offenburg wurde im Sept. 93 das Projekt eines implantierbaren 16 Bit Mikroprozessor-Kernels FHOP ins Leben gerufen. Ausgehend von dem in einem Testchip erfolgreich erprobten umstrukturierten Entwurf wurde durch gezielten Einsatz von strukturiertem Routen unter Nutzung der Fähigkeiten zum hierarchischen Arbeiten in der MENTOR-IC-Station eine erheblich verkleinerte und flächenmäßig optimierte Struktur abgeleitet, die sich mit 4 Quadratmilimetern Fläche durchaus mit kommerziellen Mikroprozessor-Kerneln vergleichen läßt.
FHOP-Mikroprozessor-Kernel
(1995)
Für die Implementation in ASIC's wurde ein kompakter Mikroprozessor-Kernel als Standardzellen-Makro entworfen. Durch konsequenten Einsatz von Hochsprachen und CAE-Werkzeugen (VHDL, Synthese) konnte ein vollständiges Design in nur vier Monaten durchgeführt werden. Der Prozessor wird in einem Testchip erprobt.
Erstellen von Hardmakros und Aufbau einer Zellbibliothek unter Verwendung des ES2-Library-Kits
(1993)
Es wird eine Anleitung zur Erstellung von Hardmakros mit der Mentor-Graphics-Software gegeben. Die Hardmakros werden mit Standardzellen aus der ES2-Bibliothek der Firma EUROCHIP aufgebaut. Die Hardmakros werden in eine eigenständige Bibliothek abgelegt und können in neuen Chip-Designs verwendet werden.