big data analysis
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2022 ◽  
Vol 34 (3) ◽  
pp. 0-0

This paper takes the listed companies in China from 2008 to 2017 as the research sample to study the relationship between accounting information quality (AIQ) and company innovation investment efficiency. The results show that AIQ is negatively correlated with both the underinvestment and overinvestment of corporate innovation. Further, AIQ can alleviate financing constraints and reduce the lack of innovation investment; At the same time, AIQ can also alleviate the agency conflict and reduce the excessive investment in innovation. Finally, AIQ can promote the innovation investment efficiency of companies with low information environment.

2022 ◽  
Vol 30 (7) ◽  
pp. 0-0

To solve the dilemma between the increasing demand for cross-border e-commerce talents and incompatible students’ skill level, Industry-University-Research cooperation, as an essential pillar for inter-disciplinary talent cultivation model adopted by colleges and universities, brings out the synergy from relevant parties and builds the bridge between the knowledge and practice. Nevertheless, industry-university-research cooperation developed lately in the cross-border e-commerce field with several problems such as unstable collaboration relationships and vague training plans.

2022 ◽  
Vol 99 ◽  
pp. 103627
Richard van der Weide ◽  
Vincent van der Vlies ◽  
Frank van der Meer

Xin Lao ◽  
Xinghua Deng ◽  
Hengyu Gu ◽  
Jian Yang ◽  
Hanchen Yu ◽  

Dae Hyun Jung

This study emphasizes the necessity of introducing a blockchain-based joint logistics system to strengthen the competency of medical supply chain management (SCM) and tries to develop a healthcare supply chain management (HSCM) competency measurement item through an analytic hierarchy process. The variables needed for using blockchain-based joint logistics are the performance expectations, effort expectations, promotion conditions, and social impact of the UTAUT model, and the HSCM competency results in increased reliability and transparency, enhanced SCM, and enhanced scalability. Word cloud results, analyzing the most important considerations to realize work efficiency among medical industry-related agencies, mentioned numerous words, including sudden situations, delivery, technology trust, information sharing, effectiveness, urgency, etc. This might imply the need to establish a system that can respond immediately to emergency situations during holidays. It could also suggest the importance of real-time information sharing to increase the efficiency of inventory management. Therefore, there is a need of a business model that can increase the visibility of real-time medical SCM through big data analysis. By analyzing the importance of securing reliability based on the blockchain technology in the establishment of a supply chain network for HSCM competency, we reveal that joint logistics can be achieved and synergistic effects can be created by implementing the integrated database to secure HSCM competency. Strengthening partnerships, such as joint logistics, will eventually lead to HSCM competency. In particular, HSCM should seek ways to upgrade its competitive capabilities through big data analysis based on the establishment of a joint logistics system.

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Yanmei Xia ◽  
Xiuzhe Wang ◽  
Weidong Wu ◽  
Haipeng Shi

The objective of this study was to explore rehabilitation of patients with acute kidney injury (AKI) treated with Xuebijing injection by using intelligent medical big data analysis system. Based on Hadoop distributed processing technology, this study designed a medical big data analysis system and tested its performance. Then, this analysis system was used to systematically analyze rehabilitation of sepsis patients with AKI treated with Xuebijing injection. It is found that the computing time of this system does not increase obviously with the increase of cases. The results of systematic analysis showed that the glomerular filtration rate (59.31 ± 3.87% vs 44.53 ± 3.53%) in the experimental group was obviously superior than that in the controls after one week of treatment. The levels of urea nitrogen (9.32 ± 2.21 mmol/L vs. 14.32 ± 0.98 mmol/L), cystatin C (1.65 ± 0.22 mg/L vs. 2.02 ± 0.13 mg/L), renal function recovery time (6.12 ± 1.66 days vs. 8.66 ± 1.17 days), acute physiology and chronic health evaluation system score (8.98 ± 2.12 points vs. 12.45 ± 2.56 points), sequential organ failure score (7.22 ± 0.86 points vs. 8.61 ± 0.97 points), traditional Chinese medicine (TCM) syndrome score (6.89 ± 1.11 points vs. 11.33 ± 1.23 points), and ICU time (16.43 ± 2.37 days vs. 12.15 ± 2.56 days) in the experimental group were obviously lower than those in the controls, and the distinctions had statistical significance ( P < 0.05 ). The significant efficiency (37.19% vs. 25.31%) and total effective rate (89.06% vs. 79.06%) in the experimental group were obviously superior than those in the controls, and distinction had statistical significance ( P < 0.05 ). In summary, the medical big data analysis system constructed in this study has high efficiency. Xuebijing injection can improve the renal function of sepsis patients with kidney injury, and its therapeutic effect is obviously better than that of Western medicine, and it has clinical application and promotion value.

2022 ◽  
Vol 9 (1) ◽  
Loris Belcastro ◽  
Riccardo Cantini ◽  
Fabrizio Marozzo ◽  
Alessio Orsino ◽  
Domenico Talia ◽  

AbstractIn the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. This data, commonly referred to as Big Data, is challenging current storage, processing, and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from Big Data. Most of the recent surveys provide a global analysis of the tools that are used in the main phases of Big Data management (generation, acquisition, storage, querying and visualization of data). Differently, this work analyzes and reviews parallel and distributed paradigms, languages and systems used today to analyze and learn from Big Data on scalable computers. In particular, we provide an in-depth analysis of the properties of the main parallel programming paradigms (MapReduce, workflow, BSP, message passing, and SQL-like) and, through programming examples, we describe the most used systems for Big Data analysis (e.g., Hadoop, Spark, and Storm). Furthermore, we discuss and compare the different systems by highlighting the main features of each of them, their diffusion (community of developers and users) and the main advantages and disadvantages of using them to implement Big Data analysis applications. The final goal of this work is to help designers and developers in identifying and selecting the best/appropriate programming solution based on their skills, hardware availability, application domains and purposes, and also considering the support provided by the developer community.

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Li Xue ◽  
Chuangjian Yang

In order to improve the effect of copying and recreation of painting works, this paper combines mobile digital multimedia big data technology to improve the image coding algorithm, identify the characteristics of existing works, apply the algorithm to the detailed analysis of painting works, and construct the main functional structure modules of the system. Moreover, this paper combines the existing hardware equipment to construct the painting works’ recreation system and obtains the image processing module. After the system is constructed, the effect of copying and recreating painting works is analyzed through the mobile digital multimedia big data analysis technology. Finally, this paper constructs the system of this paper through simulation methods and uses experiments to calculate the feature recognition effect and copy effect of the painting works of the system. Through experimental analysis, it can be known that the copying and recreation system of painting works based on mobile digital multimedia big data analysis proposed in this paper can help painters effectively improve the effect of recreation.

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