scholarly journals POS-061 THE IMPACT OF NEGLECTING URINARY OUTPUT WHEN DEFINING AKI IN PREDICTION MODELLING: A BIG DATA ANALYSIS

2021 ◽  
Vol 6 (4) ◽  
pp. S27
Author(s):  
J. Vanmassenhove ◽  
J. Steen ◽  
W. Van Biesen
2020 ◽  
Vol 3 (1) ◽  
pp. 17-35
Author(s):  
Brian J. Galli

In today's fiercely competitive environment, most companies face the pressure of shorter product life cycles. Therefore, if companies want to maintain a competitive advantage in the market, they need to keep innovating and developing new products. If not, then they will face difficulties in developing and expanding markets and may go out of business. New product development is the key content of enterprise research and development, and it is also one of the strategic cores for enterprise survival and development. The success of new product development plays a decisive role both in the development of the company and in maintaining a competitive advantage in the industry. Since the beginning of the 21st century, with the continuous innovation and development of Internet technology, the era of big data has arrived. In the era of big data, enterprises' decision-making for new product development no longer solely relies on the experience of decision-makers; it is based on the results of big data analysis for more accurate and effective decisions. In this thesis, the case analysis is mainly carried out with Company A as an example. Also, it mainly introduces the decision made by Company A in the actual operation of new product development, which is based on the results of big data analysis from decision-making to decision-making innovation. The choice of decision-making is described in detail. Through the introduction of the case, the impact of big data on the decision-making process for new product development was explored. In the era of big data, it provides a new theoretical approach to new product development decision-making.


Nowadays, the digital technologies and information systems (i.e. cloud computing and Internet of Things) generated the vast data in terabytes to extract the knowledge for making a better decision by the end users. However, these massive data require a large effort of researchers at multiple levels to analyze for decision making. To find a better development, researchers concentrated on Big Data Analysis (BDA), but the traditional databases, data techniques and platforms suffers from storage, imbalance data, scalability, insufficient accuracy, slow responsiveness and scalability, which leads to very less efficiency in Big Data (BD) context. Therefore, the main objective of this research is to present a generalized view of complete BD system that consists of various stages and major components of every stage to process the BD. In specific, the data management process describes the NoSQL databases and different Parallel Distributed File Systems (PDFS) and then, the impact of challenges, analyzed for BD with recent developments provides a better understanding that how different tools and technologies apply to solve real-life applications.


2021 ◽  
Vol 33 (6) ◽  
pp. 1-18
Author(s):  
Jianfei Li ◽  
Juxing Li ◽  
Jin Ji ◽  
Shengjun Meng

The coronavirus disease 2019 (COVID-19) epidemic that began in early 2020 quickly formed a global trend, bringing unprecedented shocks to many countries’ and even the global trade economy. Big data is the main feature of the Internet era, which has transformed the industrial development pattern of modern society and has now flourished in the field of trade economy; therefore, it is of great significance to apply the big data analysis technology to study the impact of the COVID-19 epidemic on the global trade economy. On the basis of summarizing and analyzing previous research works, this paper, expounded the research status and significance of the impact of the COVID-19 epidemic on the global trade economy, elaborated the development background, The study results of this paper provide a reference for further researches on the impact of the impact of the COVID-19 epidemic on the global trade economy based on big data analysis.


Author(s):  
J. Li ◽  
F. Biljecki

Abstract. With the fast expansion and controversial impacts of short-term rental platforms such as Airbnb, many cities have called for regulating this new business model. This research aims to establish an approach to understand the impact of Airbnb (and similar services) through big data analysis and provide insights potentially useful for its regulation. The paper reveals how Airbnb is influencing Beijing’s neighbourhood housing prices through machine learning and GIS. Machine learning models are developed to analyse the relationship between Airbnb activities in a neighbourhood and prevailing housing prices. The model of the best fit is then used to analyse the neighbourhood price sensitivity in view of increasing Airbnb activities. The results show that the sensitivity is variable: there are neighbourhoods that are likely to be more price sensitive to Airbnb activities, but also neighbourhoods that are likely to be price robust. Finally, the paper gives policy recommendations for regulating short-term rental businesses based on neighbourhood’s price sensitivity.


2021 ◽  
Vol 10 (3) ◽  
pp. 630-646
Author(s):  
Abd El Rahman Mohammed Rashwan ◽  
Mohammed Atef Madi

The study was aimed at identifying the impact of big data analysis on supporting the competitive advantage of industrial companies listed on the Palestine Stock Exchange, the study used the descriptive analytical approach, and conducted the study on a sample of (49) general managers, financial and administrative in the industrial companies listed on the Palestine Stock Exchange, and concluded the study there is a significant impact of the analysis of big data on (strengthening competitive position, cost leadership strategy, strategy of excellence, strategy of focus) in the industrial companies listed on the Palestine Stock Exchange, and recommended that companies listed industrial in Palestine work on Do more big data analysis to support and enhance investors' decision-making ability by improving the quality of data obtained, and you need to have correct information about customers, products and the environment around the company in the fastest and least time to access the competitive advantage that big data analysis can provide.


Author(s):  
Suleiman Mustafa El- Dalahmeh

This study aims to identifying the impact of big data analysis on the accounting Profession in Jordanian business environment. To achieve the study objectives researcher distributed a questionnaire to (147) out of certified public accounts, financial analysis and experts in big data analysis in the kingdom of Jordan. (108) questionnaires were returned. The response rate was (51.7%) of the population. In addition, the study sought to verify the hypothesis of the study. In order to analysis the data, the researcher used means, standard deviation and T-test. The result of the study revealed that the big data analysis have a significant role on the accounting roles and improve the quality of accounting characteristics in Jordan with an overall means (4.52). Based on the results of hypotheses, rejected the null basic hypothesis of the study, and the two null sub-hypotheses were rejected. In light of findings the researcher gave a number of recommendations:1- The necessity of teaching big data and business analysis in the accounting education curricula at the undergraduate level to enhance students' knowledge of the importance of that data.2- Holding workshops and training courses for researchers and academics to knowing them the importance of analyzing big data and how to process, store, manage and invest it in the accounting and financial field.


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