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Ecuador, traditionally an agricultural based economy, has a great potential for valorizing their industrial residues. This study, presents a techno-economic analysis for applying a novel biomass oxidation method to produce formic and acetic acids from coffee husk residues in Machala, Ecuador. The analysis determined that the time of return of investment was lower than 5 years, making this project economically feasible, when producing approx. 1000 tons of formic acid per year, which is enough for supplying the Ecuadorian market. This production, would reduce imports costs and develop the chemical industry in the country.
Ein Ansatz des Dienstleistungsmarketings, mit dessen Hilfe Gesundheitsleistungen ganz aus Perspektive der behandelten Person und ihrer Customer Journey durch den Leistungsprozess analysiert werden kann, ist das sogenannte Service Blueprinting. Die vorliegende Fallstudie beginnt mit einer kurzen Einführung zur Begründung und zum Vorgehen dieses Ansatzes. Im Anschluss wird der Ansatz anhand der holprigen Customer Journey des imaginären Patienten Torben Schulz im Rahmen einer Bandscheiben-Operation kritisch diskutiert und auf einen Teilaspekt dieser Dienstleistung angewendet.
Near-Data Processing (NDP) is a key computing paradigm for reducing the ever growing time and energy costs of data transport versus computations. With their flexibility, FPGAs are an especially suitable compute element for NDP scenarios. Even more promising is the exploitation of novel and future non-volatile memory (NVM) technologies for NDP, which aim to achieve DRAM-like latencies and throughputs, while providing large capacity non-volatile storage.
Experimentation in using FPGAs in such NVM-NDP scenarios has been hindered, though, by the fact that the NVM devices/FPGA boards are still very rare and/or expensive. It thus becomes useful to emulate the access characteristics of current and future NVMs using off-the-shelf DRAMs. If such emulation is sufficiently accurate, the resulting FPGA-based NDP computing elements can be used for actual full-stack hardware/software benchmarking, e.g., when employed to accelerate a database.
For this use, we present NVMulator, an open-source easy-to-use hardware emulation module that can be seamlessly inserted between the NDP processing elements on the FPGA and a conventional DRAM-based memory system. We demonstrate that, with suitable parametrization, the emulated NVM can come very close to the performance characteristics of actual NVM technologies, specifically Intel Optane. We achieve 0.62% and 1.7% accuracy for cache line sized accesses for read and write operations, while utilizing only 0.54% of LUT logic resources on a Xilinx/AMD AU280 UltraScale+ FPGA board. We consider both file-system as well as database access patterns, examining the operation of the RocksDB database when running on real or emulated Optane-technology memories.
In today's business landscape, companies compete more and more as integrated supply chains rather than as individual firms. The success of the entire supply chain determines the economic well-being of each company involved. With management attention shifting to supply chains, the role of management accounting naturally must extend to the cross-company layer as well. This book demonstrates how management accounting can make a significant contribution to supply chain success. It targets students who are already familiar with the fundamentals of accounting and want to extend their expertise in the field of cross-company (or network) management accounting. Practitioners will draw valuable insights from the text as well.
This second edition includes a new chapter on Digitalization and Supply Chain Accounting, as well as new opener cases to each chapter that provide real-world examples.
Military organizations have special features like following different organizational laws in times of peace and war and their specific embeddedness in society and politics. Especially the latter aspect has made the military an important object of study since the beginnings of modern sociology. In the wake of establishing specific sociological accounts, military sociology has been developed, dedicated to the different facets of the military. This research is based on different theoretical perspectives, but has hardly embraced the frameworks from economics and sociology of conventions (EC/SC) so far. The aim of the chapter is to explore and demonstrate the potentials of this approach. In a first step, the state of the art of military sociology research is outlined, and potential avenues for analyzing military forces based on EC/SC are identified. It is argued that especially the connection to organizational theory (military as organization) and civil-military relations, including leadership and professionalism, offer starting points. After introducing existing studies addressing military-related topics with reference to EC/SC, relevant concepts and approaches of convention theory that prove to be particularly enriching for military research are discussed. An outlook on possible further fields and topics of research is given to concretize how an inclusion of the perspective of EC/SC could look like.
Geopolitische Risiken sind nicht erst seit Ausbruch des Ukraine-Kriegs für den Erfolg und die Überlebensfähigkeit von Unternehmen von großer Relevanz. Nur durch den Aufbau von Methodenkompetenz, diese besonderen Risiken zu identifizieren, schaffen Unternehmen die notwendigen Voraussetzungen für ein erfolgreiches Management von geopolitischen Ereignissen.
Traditionelle Organisationen wandeln sich in komplexe Wertschöpfungssysteme mit zunehmend dezentralisierten und digitalisierten Formen der Arbeitsorganisation. Indem sich die Vorstellungen von Mitgliedschaft verändern und sich Arbeit in digitalisierte Räume verschiebt, lösen sich die Grenzen von Organisationen auf. Im Beitrag wird argumentiert, dass sich in solch grenzaufgelösten Organisationen die Machtdynamiken verändern. Im Beitrag werden zwei Dynamiken exemplarisch betrachtet: erstens diejenigen, die sich aus der abnehmenden Wirkung bürokratischer Strukturen als Machtressourcen ergeben, wenn sich die Formen der organisationalen Mitgliedschaft und Zugehörigkeit verändern (z. B. Freelancer, hybride Arbeit). Zweitens werden die Schnittstellen zwischen Menschen und intelligenten Technologien in digitalen Arbeitsräumen und die sich dadurch verschiebenden Machtverhältnisse betrachtet. Der Beitrag zielt darauf ab, die veränderten Machtdynamiken sichtbarer zu machen und damit einen reflektierten Umgang mit Macht in digital transformierten Organisationen zu ermöglichen.
Silicon neurons represent different levels of biological details and accuracies as a trade-off between complexity and power consumption. With respect to this trade-off and high similarity to neuron behaviour models, relaxation-type oscillator circuits often yield a good compromise to emulate neurons. In this chapter, two exemplified relaxation-type silicon neurons are presented that emulate neural behaviour with energy consumption under the scale of nJ/spike. The first proposed fully CMOS relaxation SiN is based on mathematical Izhikevich model and can mimic a broad range of physiologically observable spike patterns. The results of kinds of biologically plausible output patterns and coupling process of two SiNs are presented in 0.35 μm CMOS technology. The second type is a novel ultra-low-frequency hybrid CMOS-memristive SiN based on relaxation oscillators and analog memristive devices. The hybrid SiN directly emulates neuron behaviour in the range of physiological spiking frequencies (less than 100 Hz). The relaxation oscillator is implemented and fabricated in 0.13 μm CMOS technology. An autonomous neuronal synchronization process is demonstrated with two relaxation oscillators coupled by an analog memristive device in the measurement to emulate the synchronous behaviour between spiking neurons.
Context
Web APIs are one of the most used ways to expose application functionality on the Web, and their understandability is important for efficiently using the provided resources. While many API design rules exist, empirical evidence for the effectiveness of most rules is lacking.
Objective
We therefore wanted to study 1) the impact of RESTful API design rules on understandability, 2) if rule violations are also perceived as more difficult to understand, and 3) if demographic attributes like REST-related experience have an influence on this.
Method
We conducted a controlled Web-based experiment with 105 participants, from both industry and academia and with different levels of experience. Based on a hybrid between a crossover and a between-subjects design, we studied 12 design rules using API snippets in two complementary versions: one that adhered to a rule and one that was a violation of this rule. Participants answered comprehension questions and rated the perceived difficulty.
Results
For 11 of the 12 rules, we found that violation performed significantly worse than rule for the comprehension tasks. Regarding the subjective ratings, we found significant differences for 9 of the 12 rules, meaning that most violations were subjectively rated as more difficult to understand. Demographics played no role in the comprehension performance for violation.
Conclusions
Our results provide first empirical evidence for the importance of following design rules to improve the understandability of Web APIs, which is important for researchers, practitioners, and educators.
In den letzten Jahren hat der Trend zur Digitalisierung und Konnektivität die Kundenerwartungen an den B2B-Kundenservice verändert. Vorliegender Artikel arbeitet mit zwei klaren Studienzielen und untersucht zum einen die Rolle von IoT (Internet of Things) und Cybersicherheit als Erfolgsfaktoren für den Business-to-Business (B2B) Kundenservice und zum anderen wie eine sichere Integration zu einem Wettbewerbsvorteil auf dem deutschen Markt beitragen kann. Durch einen qualitativen Ansatz mithilfe von 20 Befragungen wurde untersucht, dass IoT und Cybersicherheit als Erfolgsfaktoren für den deutschen B2B-Kundenservice angesehen werden können. Als Ergebnis liefert diese Studie fünf Kernaussagen (Hypothesen) aus qualitativen Interviews. Neben der Diskussion allgemeiner Erfolgsfaktoren und deren Einfluss, wurde die Rolle von IoT bei der Optimierung des B2B Kundendienstes diskutiert. Zudem werden potenzielle Sicherheitsrisken in Zusammenhang mit den Dienstleistungsmodellen, notwendige Anforderungen an Cybersicherheit sowie Datenerfassung erörtert. Abschließend wurde ein Modell entwickelt, das interne und externe Aspekte aufzeigt, die dazu beitragen, dass IoT und Cybersicherheit als Erfolgsfaktoren in der Aktivitätskette des Kunden in der Pre-Sales‑, Sales- und After-Sales-Phase erlebt werden.
Dieser praxis-nahe und industrie-übergreifende Artikel liefert somit Einblicke basierend auf qualitativen Erkenntnissen für weitere Forschung in der Theorie und befähigt Organisationen das Thema ganzeinheitlich zu betrachten.
Mode & Musik
(2023)
Dieses Buch wird das Verständnis der Leser für die Verbindungen zwischen der Musik- und der Modeindustrie erweitern. Es hebt die Herausforderungen hervor, denen sich die Modeindustrie derzeit in Bezug auf den Hyperwettbewerb, die Definition immer schnellerer Trends, sich ändernde Verbraucherwünsche usw. gegenübersieht. Die Modeindustrie wird in der Tat stark von der digitalen Revolution in der Musikindustrie beeinflusst, die das Gesicht des individuellen Musikkonsums und des sozialen Bezugs verändert hat und sich daher auch auf den Modekonsum und den sozialen Bezug auswirkt. Dieses Verständnis ist von entscheidender Bedeutung, um die Strategien eines Modeunternehmens auf die Anforderungen der modernen Modekonsumenten auszurichten.
Ziel des Beitrages ist es, sinnlich-ästhetisch Weltzugänge am Beispiel des Designs für pädagogische Kontexte herauszuarbeiten. Gleichermaßen soll eine Reflexion darüber in Gang gesetzt werden, welche Potenziale transdisziplinär geprägte Gestaltungsprozesse für das Lernen und Lehren bereithalten. Zunächst wird daher die transdisziplinäre Natur des Designs geschichtlich hergeleitet und verschiedene Prozesse beleuchtet. Das sich anschließende Kapitel arbeitet unter dem Begriff der Gestaltung jene Merkmale und Qualitäten professionellen Designs heraus, die allen Prozessen zugrunde liegen. Abschließend wird das Konzept des Design Thinking vor dem Hintergrund erfahrungsbasierten Lernens in der Schulbildung diskutiert und mit Beispielen aus empirischen Studien untermauert.
The relevance of Robotic Process Automation (RPA) has increased over the last few years. Combining RPA with Artificial Intelligence (AI) can further enhance the business value of the technology. The aim of this research was to analyze applications, terminology, benefits, and challenges of combining the two technologies. A total of 60 articles were analyzed in a systematic literature review to evaluate the aforementioned areas. The results show that by adding AI, RPA applications can be used in more complex contexts, it is possible to minimize the human factor during the development process, and AI-based decision-making can be integrated into RPA routines. This paper also presents a current overview of the used terminology. Moreover, it shows that by integrating AI, some unseen challenges in RPA projects can emerge, but also a lot of new benefits will come along with it. Based on the outcome, it is concluded that the topic offers a lot of potential, but further research and development is required. The result of this study help researches to gain an overview of the state-of-the-art in combining RPA and AI.
Sprachassistenten gewinnen als Alltagshelfer immer mehr an Bedeutung. Sie beeinflussen die Art und Weise, wie Menschen Aufgaben erledigen und mit Unternehmen interagieren. Eine qualitative Studie hat die Nutzungsbereitschaft beim Kauf von High-Involvement-Produkten über Sprachassistenten untersucht. Zukünftig könnte Voice Commerce für diese Produkte an Relevanz gewinnen.
Purpose
For the modeling, execution, and control of complex, non-standardized intraoperative processes, a modeling language is needed that reflects the variability of interventions. As the established Business Process Model and Notation (BPMN) reaches its limits in terms of flexibility, the Case Management Model and Notation (CMMN) was considered as it addresses weakly structured processes.
Methods
To analyze the suitability of the modeling languages, BPMN and CMMN models of a Robot-Assisted Minimally Invasive Esophagectomy and Cochlea Implantation were derived and integrated into a situation recognition workflow. Test cases were used to contrast the differences and compare the advantages and disadvantages of the models concerning modeling, execution, and control. Furthermore, the impact on transferability was investigated.
Results
Compared to BPMN, CMMN allows flexibility for modeling intraoperative processes while remaining understandable. Although more effort and process knowledge are needed for execution and control within a situation recognition system, CMMN enables better transferability of the models and therefore the system. Concluding, CMMN should be chosen as a supplement to BPMN for flexible process parts that can only be covered insufficiently by BPMN, or otherwise as a replacement for the entire process.
Conclusion
CMMN offers the flexibility for variable, weakly structured process parts, and is thus suitable for surgical interventions. A combination of both notations could allow optimal use of their advantages and support the transferability of the situation recognition system.
In recent years, 3D facial reconstructions from single images have garnered significant interest. Most of the approaches are based on 3D Morphable Model (3DMM) fitting to reconstruct the 3D face shape. Concurrently, the adoption of Generative Adversarial Networks (GAN) has been gaining momentum to improve the texture of reconstructed faces. In this paper, we propose a fundamentally different approach to reconstructing the 3D head shape from a single image by harnessing the power of GAN. Our method predicts three maps of normal vectors of the head’s frontal, left, and right poses. We are thus presenting a model-free method that does not require any prior knowledge of the object’s geometry to be reconstructed.
The key advantage of our proposed approach is the substantial improvement in reconstruction quality compared to existing methods, particularly in the case of facial regions that are self-occluded in the input image. Our method is not limited to 3d face reconstruction. It is generic and applicable to multiple kinds of 3D objects. To illustrate the versatility of our method, we demonstrate its efficacy in reconstructing the entire human body.
By delivering a model-free method capable of generating high-quality 3D reconstructions, this paper not only advances the field of 3D facial reconstruction but also provides a foundation for future research and applications spanning multiple object types. The implications of this work have the potential to extend far beyond facial reconstruction, paving the way for innovative solutions and discoveries in various domains.
The aim of this work is the development of artificial intelligence (AI) application to support the recruiting process that elevates the domain of human resource management by advancing its capabilities and effectiveness. This affects recruiting processes and includes solutions for active sourcing, i.e. active recruitment, pre-sorting, evaluating structured video interviews and discovering internal training potential. This work highlights four novel approaches to ethical machine learning. The first is precise machine learning for ethically relevant properties in image recognition, which focuses on accurately detecting and analysing these properties. The second is the detection of bias in training data, allowing for the identification and removal of distortions that could skew results. The third is minimising bias, which involves actively working to reduce bias in machine learning models. Finally, an unsupervised architecture is introduced that can learn fair results even without ground truth data. Together, these approaches represent important steps forward in creating ethical and unbiased machine learning systems.
Automatic segmentation is essential for the brain tumor diagnosis, disease prognosis, and follow-up therapy of patients with gliomas. Still, accurate detection of gliomas and their sub-regions in multimodal MRI is very challenging due to the variety of scanners and imaging protocols. Over the last years, the BraTS Challenge has provided a large number of multi-institutional MRI scans as a benchmark for glioma segmentation algorithms. This paper describes our contribution to the BraTS 2022 Continuous Evaluation challenge. We propose a new ensemble of multiple deep learning frameworks namely, DeepSeg, nnU-Net, and DeepSCAN for automatic glioma boundaries detection in pre-operative MRI. It is worth noting that our ensemble models took first place in the final evaluation on the BraTS testing dataset with Dice scores of 0.9294, 0.8788, and 0.8803, and Hausdorf distance of 5.23, 13.54, and 12.05, for the whole tumor, tumor core, and enhancing tumor, respectively. Furthermore, the proposed ensemble method ranked first in the final ranking on another unseen test dataset, namely Sub-Saharan Africa dataset, achieving mean Dice scores of 0.9737, 0.9593, and 0.9022, and HD95 of 2.66, 1.72, 3.32 for the whole tumor, tumor core, and enhancing tumor, respectively.
The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual procedure requires considerable human and financial resources, and incorporates some subjectivity, an automated approach could result in several advantages. There have been many developments in this area, and in order to provide a comprehensive overview, it is essential to review relevant recent works and summarise the characteristics of the approaches, which is the main aim of this article. To achieve it, we examined articles published between 2018 and 2022 that dealt with the automated scoring of sleep stages. In the final selection for in-depth analysis, 125 articles were included after reviewing a total of 515 publications. The results revealed that automatic scoring demonstrates good quality (with Cohen's kappa up to over 0.80 and accuracy up to over 90%) in analysing EEG/EEG + EOG + EMG signals. At the same time, it should be noted that there has been no breakthrough in the quality of results using these signals in recent years. Systems involving other signals that could potentially be acquired more conveniently for the user (e.g. respiratory, cardiac or movement signals) remain more challenging in the implementation with a high level of reliability but have considerable innovation capability. In general, automatic sleep stage scoring has excellent potential to assist medical professionals while providing an objective assessment.
Enterprises and societies currently face essential challenges, and digital transformation can contribute to their resolution. Enterprise architecture (EA) is useful for promoting digital transformation in global companies and information societies covering ecosystem partners. The advancement of new business models can be promoted with digital platforms and architectures for Industry 4.0 and Society 5.0. Therefore, products from the sector of healthcare, manufacturing and energy, etc. can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 and the design thinking approach is expected to promote and implement the digital platforms and digital products for healthcare, manufacturing and energy communities more efficiently. In this paper, we propose various cases of digital transformation where digital platforms and products are designed and evaluated for digital IT, digital manufacturing and digital healthcare with Industry 4.0 and Society 5.0. The vision of AIDAF applications to perform digital transformation in global companies is explained and referenced, extended toward the digitalized ecosystems such as Society 5.0 and Industry 4.0.