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Reasons and potential solution approaches for the shortage of nursing staff in German hospitals
(2021)
The aim of this scientific paper was to find out the reasons for the shortage of nursing staff in German hospitals and to provide potential solution approaches for this shortage. Over the last years, the shortage of nursing staff has become a more and more important topic in the news: Not only due to the increasing amount of missing nurses, but also due to the ageing population in Germany, which leads to an increasing amount of patients in German hospitals. To reach this aim two surveys were done, of which one was for nursing staff only and the other one was for people from all occupational groups with the intention of creating comparative values. The surveys were done from March to April 2019 and were analysed afterwards. After a detailed analysis of the survey results, it can be summarized that the reasons for the shortage of nursing staff in German hospitals are very diverse: Starting with a weak salary, improvable working conditions – for example the shift work and the high amount of physical and psychological stress -, a difficult compatibility of family and job as well as the unattractive image of the job as a nurse in the society. It can be concluded that the solution for the shortage of nursing staff is very difficult. The future will show whether the governmental support will help to make the job as a nurse more attractive – not only for the current nurses, but also for potential future nurses.
For a detailed discussion of process mining, the objective of this paper is the analysis of the successful implementation of process mining in the practical fields of supply chain management. The research comprises the investigation of use cases in companies that are already actively using process mining.
Purpose: This research aims to highlight the applicability of process mining in the supply chain management business field.
Research Methodology: In order to examine the applicability of process mining in supply chain management a research study was conducted among experts in this business field. Further, theoretical findings were compared to the results and evaluated.
Results: Process Mining can be applied very well in the SCM area. The advantages that arise primarily reflect significant potential benefits and improved process throughput times. The information that can be gained from the operational areas supported by process mining is suitable for reliable decisions, both in the tactical and strategic areas.
Limitations: The results on the application of process mining show a certain generalization and have to be adapted and adjusted to the respective application case.
Contribution: This study is useful, especially for the purchasing and logistics business area.
The integration of genetic algorithms to optimize the networks of value chains could enormously improve the performance of supply chains. For this reason, this paper describes in more detail the application of genetic algorithms in the value chains of the automotive industry. For this purpose, a theoretical model is built up to evaluate whether the application of the model can optimize the value chain. This option is described, analyzed and its restrictions are shown. Instead of looking at the entire network, individual finished goods and their bill of material are used as a basis for optimization, which greatly reduces the complexity of the original problem. The original complexity of the supply chain networks can thus be reduced and considered based on the bill of material.
Multimodal meaning making: The annotation of nonverbal elements in multimodal corpus transcription
(2021)
The article discusses how to integrate annotation for nonverbal elements (NVE) from multimodal raw data as part of a standardized corpus transcription. We argue that it is essential to include multimodal elements when investigating conversational data, and that in order to integrate these elements, a structured approach to complex multimodal data is needed. We discuss how to formulate a structured corpus-suitable standard syntax and taxonomy for nonverbal features such as gesture, facial expressions, and physical stance, and how to integrate it in a corpus. Using corpus examples, the article describes the development of a robust annotation system for spoken language in the corpus of Video-mediated English as a Lingua Franca Conversations (ViMELF 2018) and illustrates how the system can be used for the study of spoken discourse. The system takes into account previous research on multimodality, transcribes salient nonverbal features in a concise manner, and uses a standard syntax. While such an approach introduces a degree of subjectivity through the criteria of salience and conciseness, the system also offers considerable advantages: it is versatile and adaptable, flexible enough to work with a wide range of multimodal data, and it allows both quantitative and qualitative research on the pragmatics of interaction.
As productive biofilms are increasingly gaining interest in research, the quantitative monitoring of biofilm formation on- or offline for the process remains a challenge. Optical coherence tomography (OCT) is a fast and often used method for scanning biofilms, but it has difficulty scanning through more dense optical materials. X-ray microtomography (μCT) can measure biofilms in most geometries but is very time-consuming. By combining both methods for the first time, the weaknesses of both methods could be compensated. The phototrophic cyanobacterium Tolypothrix distorta was cultured in a moving bed photobioreactor inside a biocarrier with a semi-enclosed geometry. An automated workflow was developed to process µCT scans of the biocarriers. This allowed quantification of biomass volume and biofilm-coverage on the biocarrier, both globally and spatially resolved. At the beginning of the cultivation, a growth limitation was detected in the outer region of the carrier, presumably due to shear stress. In the later phase, light limitations could be found inside the biocarrier. µCT data and biofilm thicknesses measured by OCT displayed good correlation. The latter could therefore be used to rapidly measure the biofilm formation in a process. The methods presented here can help gain a deeper understanding of biofilms inside a process and detect any limitations.
Aim: The aim of this scientific paper was to examine important trends and developments influencing the nursing care in order to forecast future opportunities and challenges and how to deal with them in the best possible way.
Background: The Corona-pandemic demonstrated the importance of nursing care in the entire world and had drawn attention to the issue of a well-educated and enough nursing staff. The nursing care will face opportunities and challenges due to current trends and developments, which are important to examine in order to provide the best possible nursing care.
Methods: To reach the above-mentioned aim, intensive research was done by using secondary sources and surveys.
Results/Findings: After a detailed analysis of the research it can be summarized that there are three important topics influencing the nursing care: The demographical development with an increasing life expectancy leading to an increasing amount of old people with a demand for care and decreasing birth rates leading to less working people. Cultural transformation and diversity imply many opportunities because the employment market can fill gaps with foreign workers and the immigrating people can compensate the decreasing birth rates. Nevertheless, it can imply many challenges and potential problems which need to be solved by the society and the immigrating people. Furthermore, the changing gender roles can lead to more men becoming a nurse, which might have a significant impact on the shortage of nursing staff. The third important topic influencing the nursing care is technological trends which can help to decrease physiological stress, by facilitating the nurses’ work and by taking over some work from them.
Conclusion: It can be concluded that the trends and developments influencing the nursing care are very diverse and imply many different opportunities as well as challenges.
Big Data is now poised to mutate decision-making systems. Indeed, the decision is no longer based solely on the structured information that was hitherto collected and stored by the organization, but also on all data not structured outside the corporate straitjacket. The cloud and the information it contains impacts decisions and the industry is witnessing the emergence of business intelligence 3.0. With the growth of the internet, social networks, connected objects and communication information are now more abundant than ever before, along with rapid and substantial growth in their production. In 2012, 2.5 exabytes of data (one exabyte representing a million gigabytes of data) came every day to swell the ranks of big data (McAfee et al., 2012), which should weigh more than 40 zettabytes from 2020 (Valduriez, 2014) for 30 billion connected devices (The Internet Of Nothings, 2014) and 50 billion sensors (Davenport & Soulard, 2014). One of the most critical aspects of all of this information flow is the impact these will have on the way decisions are made. Indeed, in the part of an environment in which data was scarce and difficult to obtain, it was logical to let decision-making be conditioned by the intuition of the experienced decision-maker (Klein, Phillips, Rall, & Peluso, 2007). However, since information and knowledge are now available to everyone, the role of experts and decision-makers is gradually changing. Big data, in particular, makes it possible for analytical and decision-making systems to base their decision-making on global models. However, considering all the dimensions of the situations encountered, it was not until now that these systems were not within the reach of man, but were rationally limited (Simon & Newell, 1971). Big data and however, the processing of unstructured data requires modifying the architecture of decision support systems (DSS) of organizations. This paper is an inventory of developments undergone by aid systems decision-making, under the pressure of big data. Finally, it opens the debate on ethical questions raised by these new technologies, and it is observed that now, data analysis of personal data has become more debatable than in the past.
Bauprojekte sind in der Regel komplexe Vorhaben. Sie werden mit Hilfe des Projektmanagements und dessen Verfahren, Prozessen und Techniken bewältigt. Dennoch sind deutsche Bauprojekte nicht selten von Kosten- und Terminüberschreitungen betroffen. Ziel dieser Arbeit ist es, mögliche Optimierungsfelder im Planungs- und Steuerungsprozess eines Unternehmens für Industriebauprojekte zu identifizieren und darauf aufbauende Verbesserungsansätze zu erarbeiten. Um die Ziele verfolgen zu können, wurde eine qualitative Sozialforschung mittels Experteninterviews durchgeführt. Die Expertenaussagen verdeutlichen weiterhin Optimierungspotenzial, sowohl im Planungs- als auch im Steuerungsprozess. Ausgewählte Techniken (hauptsächlich aus dem klassischen Projektmanagement) dienen indessen dazu, die Effektivität und Effizienz des Planungsprozesses zu erhöhen. Innerhalb des Steuerungsprozesses zeigt sich, dass viele Optimierungsbereiche der Steuerung auf den Defiziten der Planung beruhen.
This text will explain which role “Green Bonds” play in financing projects and how the green factor is weighted. It will be discussed on how the term “green” can change the price of the bond, if there is a “green premium” and for which group of investors this type of bond is interesting. We will discuss ways to reduce their cost of capital, also considering the risks and on ways on how to improve their conditions. The sustainable and eco-friendly aspects are also highlighted in this text and they might become crucial in future investing, which gives the bond an interesting role.
Agility and digital trends go hand in hand, but the advantages of digitalization perform a high pressure on the established automotive companies. For years now, automotive groups have no longer been innovation drivers in the industry. This status is reserved for radical companies like Tesla. But is there any chance that conservative companies will reinvent themselves, establish leaner structures and thus regain market dominance and innovation?