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Weltweit und in Deutschland erreicht das Thema Inflation neue Höchststände in der Aufmerksamkeit (Google-Trends 2022). Nach einer vielbeachteten und millionenfach angesehenen Online-Weihnachtsvorlesung aus dem Jahre 2020 hat der Ökonomieprofessor Hans-Werner Sinn das Buch mit gleichnamigem Titel „Die wundersame Geldvermehrung“ veröffentlicht. Abermals könnte es dem Autor gelingen die politische Öffentlichkeit damit aufzurütteln.
Stetiger Wandel macht auch vor dem Vertriebsprozess deutscher KMU nicht Halt. Evolutive Umwelteinflüsse sowie revolutionäres Handeln stehen im Zentrum eines Umbruchs im Vertrieb. Ergebnisse aus einem quantitativen Stimmungsbarometer deutscher KMU ermöglichen das Ableiten unternehmerischer Handlungsempfehlungen für Vertriebsorganisationen.
Autonomous navigation is one of the main areas of research in mobile robots and intelligent connected vehicles. In this context, we are interested in presenting a general view on robotics, the progress of research, and advanced methods related to this field to improve autonomous robots’ localization. We seek to evaluate algorithms and techniques that give robots the ability to move safely and autonomously in a complex and dynamic environment. Under these constraints, we focused our work in the paper on a specific problem: to evaluate a simple, fast and light SLAM algorithm that can minimize localization errors. We presented and validated a FastSLAM 2.0 system combining scan matching and loop closure detection. To allow the robot to perceive the environment and detect objects, we have studied one of the best deep learning technique using convolutional neural networks (CNN). We validate our testing using the YOLOv3 algorithm.
The digitization of factories will be a significant issue for the 2020s. New scenarios are emerging to increase the efficiency of production lines inside the factory, based on a new generation of robots’ collaborative functions. Manufacturers are moving towards data-driven ecosystems by leveraging product lifecycle data from connected goods. Energy-efficient communication schemes, as well as scalable data analytics, will support these various data collection scenarios. With augmented reality, new remote services are emerging that facilitate the efficient sharing of knowledge in the factory. Future communication solutions should generally ensure connectivity between the various production sites spread worldwide and new players in the value chain (e.g., suppliers, logistics) transparent, real-time, and secure. Industry 4.0 brings more intelligence and flexibility to production. Resulting in more lightweight equipment and, thus, offering better ergonomics. 5G will guarantee real-time transmissions with latencies of less than 1 ms. This will provide manufacturers with new possibilities to collect data and trigger actions automatically.
Academic research is vital for innovation and industrial growth. However, a potential burden of processing ever more knowledge could be affecting research output and researchers’ careers. We look at a dataset of researchers who have published in journals in the field of economics during a period of 45 years. For a subset of these researchers, we amass data from journals listed in the EconLit database, supplemented with years of birth from public sources. Our results show an increase in the age of researchers at their first publication, in the number of articles referenced in debut articles, and in the number of co-authors. Simultaneously, we observe a decline in the probability of researchers changing research fields. Our findings extend earlier findings on patents and hint at a burden of knowledge pervading different areas of human progress. Moreover, our results indicate that researchers develop strategies of specialisation to deal with this challenge.
The main aim of presented in this manuscript research is to compare the results of objective and subjective measurement of sleep quality for older adults (65+) in the home environment. A total amount of 73 nights was evaluated in this study. Placing under the mattress device was used to obtain objective measurement data, and a common question on perceived sleep quality was asked to collect the subjective sleep quality level. The achieved results confirm the correlation between objective and subjective measurement of sleep quality with the average standard deviation equal to 2 of 10 possible quality points.
Assistant platforms are becoming a key element for the business model of many companies. They have evolved from assistance systems that provide support when using information (or other) systems to platforms in their own. Alexa, Cortana or Siri may be used with literally thousands of services. From this background, this paper develops the notion of assistant platforms and elaborates a conceptual model that supports businesses in developing appropriate strategies. The model consists of three main building blocks, an architecture that depicts the components as well as the possible layers of an assistant platform, the mechanism that determines the value creation on assistant platforms, and the ecosystem with its network effects, which emerge from the multi-sided nature of assistant platforms. The model has been derived from a literature review and is illustrated with examples of existing assistant platforms. Its main purpose is to advance the understanding of assistant platforms and to trigger future research.
Many modern DBMS architectures require transferring data from storage to process it afterwards. Given the continuously increasing amounts of data, data transfers quickly become a scalability limiting factor. Near-Data Processing and smart/computational storage emerge as promising trends allowing for decoupled in-situ operation execution, data transfer reduction and better bandwidth utilization. However, not every operation is suitable for an in-situ execution and a careful placement and optimization is needed.
In this paper we present an NDP-aware cost model. It has been implemented in MySQL and evaluated with nKV. We make several observations underscoring the need for optimization.
Context:
Test-driven development (TDD) is an agile software development approach that has been widely claimed to improve software quality. However, the extent to which TDD improves quality appears to be largely dependent upon the characteristics of the study in which it is evaluated (e.g., the research method, participant type, programming environment, etc.). The particularities of each study make the aggregation of results untenable.
Objectives:
The goal of this paper is to: increase the accuracy and generalizability of the results achieved in isolated experiments on TDD, provide joint conclusions on the performance of TDD across different industrial and academic settings, and assess the extent to which the characteristics of the experiments affect the quality-related performance of TDD.
Method:
We conduct a family of 12 experiments on TDD in academia and industry. We aggregate their results by means of meta-analysis. We perform exploratory analyses to identify variables impacting the quality-related performance of TDD.
Results:
TDD novices achieve a slightly higher code quality with iterative test-last development (i.e., ITL, the reverse approach of TDD) than with TDD. The task being developed largely determines quality. The programming environment, the order in which TDD and ITL are applied, or the learning effects from one development approach to another do not appear to affect quality. The quality-related performance of professionals using TDD drops more than for students. We hypothesize that this may be due to their being more resistant to change and potentially less motivated than students.
Conclusion:
Previous studies seem to provide conflicting results on TDD performance (i.e., positive vs. negative, respectively). We hypothesize that these conflicting results may be due to different study durations, experiment participants being unfamiliar with the TDD process, or case studies comparing the performance achieved by TDD vs. the control approach (e.g., the waterfall model), each applied to develop a different system. Further experiments with TDD experts are needed to validate these hypotheses.
This paper presents the concept of the system architecture of a flexible cyber-physical factory control system. The system allows the automation of process structures using cyber-physical fractal nodes. These nodes have a functional and independent form and can be clustered to larger structures. This makes it possible to equip the factory with a flexible, freely scalable, modular system. The description of this system architecture and the associated rules and conditions is outlined in the concept.