With the rapid development of computer science and technology, the Chinese petroleum industry has ushered in the era of big data. In this study, by collecting fracturing data from 303 horizontal ...wells in the Fuling Shale Gas Demonstration Area in China, a series of big data analysis studies was conducted using Pearson’s correlation coefficient, the unweighted pair group with arithmetic means method, and the graphical plate method to determine which is best. The fracturing parameters were determined through a series of big data analysis studies. The big data analysis process is divided into three main steps. The first is data preprocessing to screen out eligible, high-yielding wells. The second is a fracturing parameter correlation clustering analysis to determine the reasonableness of the parameters. The third is a big data panel method analysis of specific fracturing construction parameters to determine the optimal parameter range. The analyses revealed that the current amount of 100 mesh sand in the Fuling area is unreasonable; further, there are different preferred areas for different fracturing construction parameters. We have combined different fracturing parameter schemes by preferring areas. This analysis process is expected to provide new ideas regarding fracturing scheme design for engineers working on the frontline.
Social networking is one of the major source of massive data. Such data is not only difficult to store, manipulate and maintain but it’s open access makes it security prone. Therefore, robust and ...efficient authentication should be devised to make it invincible against the known security attacks. Moreover, social networking services are intrinsically multi-server environments, therefore compatible and suitable authentication should be designed accordingly. Sundry authentication protocols are being utilized at the moment and many of them are designed for single server architecture. This type of remote architecture resists each user to get itself register with each server if multiple servers are employed to offer online social services. Recently multi-server architecture for authentication has replaced the single server architecture, and it enable users to register once and procure services from multiple servers. A short time ago, Lu et al. presented two authentication schemes based on three factors. Furthermore, both Lu et al.’s schemes are designed for multi-server architecture. Lu et al. claimed the schemes to be invincible against the known attacks. However, this paper shows that one of the Lu et al.’s scheme is susceptible to user anonymity violation and impersonation attacks, whereas Lu et al.’s second scheme is susceptible to user impersonation attack. Therefore an enhanced scheme is introduced in this paper. The proposed scheme is more robust than subsisting schemes. The proposed scheme is thoroughly verified and validated with formal and informal security discussion, and through the popular automated tool ProVerif. The in-depth analysis affirms that proposed scheme is lightweight in terms of computations while attaining mutual authentication and is invincible against the known attacks, hence is more suitable for automated big data analysis for social multimedia networking environments.
Purpose
Innovation in fintech presents great opportunities and huge challenges for accounting practices around the world. This paper aims to examine the impact of Fintech on accounting practices ...including financial reporting, performance management, budgeting, auditing, risk and fraud management. Fintech is proxied by the adoption of AI and big data analysis in accounting practices.
Design/methodology/approach
We chose African countries as our focus countries and surveyed chartered and qualified accountants in both Ghana and Nigeria. With 201 questionnaires qualified for our final analyses, we adopted the structural equation modelling to analyse the impact of Fintech on accounting practices.
Findings
The empirical results show that the impact of AI and big data on accounting practices is positive and significant, indicating that fintech could potentially mitigate the agency problem in accounting practices and lead to better accounting practices. Interestingly, we find that, in general, the impact of AI is larger than that of big data.
Originality/value
Our results provide significant insights to regulators, policymakers and managers about the future development of adopting fintech in the regulation and governance framework at both macro and micro levels for accounting practice.
Abstract
During the COVID-19 epidemic, the whole country suspended classes in schools without stopping studying. Under this circumstance, online teaching experienced a breakthrough development. This ...paper uses the method of questionnaire survey and the algorithm of big data analysis, and this paper explores the general situation of online teaching in local colleges and universities in southwest Guangxi which face challenges in online learning due to the relative shortage of educational resources and remote geographical location. This paper analyzes the supporting conditions, problems and shortcomings of online teaching in local colleges and universities in southwest Guangxi. Suggestions are also proposed on four aspects to improve online teaching and learning experiences, which are establishing the basis of online teaching conditions, strengthening the basic rules of online classroom management, improving teachers and students’ adaptation to online environment, and guiding students to improve independent learning ability.
In the era of big data, individual small data is aggregated into big data through various network interconnections. Big data has the characteristics of large volume, many types, and fast speed. More ...and more information is contained in it. Massive data resources and mature The data value mined by the big data analysis method can provide more powerful decision support for enterprises in the product development and design process. Based on this, this paper analyses the application of big data analysis in product R & D design decision. This paper conducts research through a combination of literature review method and experimental comparison method, and summarizes relevant domestic and foreign literature data. It is found that big data analysis solves product development. For user needs and experience, data sources are more accurate and convenient. Through the comparison of the experiments of two companies in a certain area, it is concluded that companies that use big data analysis for product R & D and design have more advantages. Their advantages are as follows: the systemization of R & D and design has increased by 70.0%, and the efficiency has increased by 93.3%. Collaboration The aspect has increased by 55.4%, and the cost has been reduced by 58.3%. The research results of this paper show that big data analysis has played an important role in product R & D and design decisions.
Filamentous fungi grow in form of multicellular tubular hyphae (‘simple multicellularity’). When hyphae aggregate, more complex three-dimensional structures emerge. Differentiation of hyphal cells ...adds to morphological and functional complexity of aggregated fungal organs (‘complex multicellularity’) that serve such different biological purposes as sustenance, resilience, or sexual or asexual reproduction. The most complex structures in the fungal kingdom are the multicellular sexual fruiting bodies with distinct fungal tissues and multiple cell types. Between fungal taxa, fruiting bodies come in various morphological shapes, colors and sizes. So far, it is largely unclear what genetically determines such complex multicellularity in fungi and how and how often core functions of such multicellularity evolved. Research targets at to find out what is behind the complex multicellularity in fungal fruiting body development. Combined inputs of environmental signals to transcription of participating genes are coordinated in the nuclei by distinctive transcription factors. Comparative analyses of big data sets derived from sequenced genomes of different fungal species and from sequenced situational transcriptomes can extract what is common in developmental programs as potential core functions in multicellularity and also identify that what is specific in individual development.
The accurate splice site prediction has several applications in the field of medical sciences and biochemistry. For instance, any mutation affecting the splice site will lead to genetic diseases and ...cancer such as Lynch syndrome and breast cancer. For this purpose, collecting the Ribonucleic Acid (RNA) samples is an efficient and convenient method to detect the involvement of splicing defects in disease formation. Therefore, the present study aims to develop an accurate and robust Computer-Aided Diagnosis (CAD) method for swift and precise targeting of splice site sequences. A composite features-based model is proposed by integrating three different sample representation methods i.e., Dinucleotide Composition (DNC), Trinucleotide Composition (TNC) and Tetranucleotide Composition (TetraNC) for precise splice site prediction after converting the DNA sequences into numerical descriptors. The precision and accuracy of these features are analyzed by applying different machine learning algorithms such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Naïve Bayes (NB). Results show that the proposed model of composite features vector with SVM classifier achieved an accuracy of 95.20% and 97.50% for donor and acceptor sites datasets, respectively.
Shi, L., 2019. Fuzzy evaluation model of economic loss in high density marine traffic accidents based on big data analysis. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water ...Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 768–774. Coconut Creek (Florida), ISSN 0749-0208. The traditional fault tree analysis method cannot accurately evaluate the economic loss of high-density marine traffic accidents, so a fuzzy evaluation model of high-density marine traffic accident economic loss based on big data analysis is proposed. Dimensionless processing is carried out for each variable value of the economic loss evaluation index of maritime traffic accidents. According to the processing results, the absolute and relative indexes of accidents are used to reasonably convert the economic loss data of traffic accidents into safety index for calculation. On this basis, the index of the safety condition of maritime traffic is determined, and finally the construction of the fuzzy evaluation of economic loss of maritime traffic accidents is realized. The simulation results show that compared with the traditional model, the model can better reflect the actual water safety situation, and can accurately analyze and evaluate the economic losses caused by maritime traffic accidents. It shows that the model is reliable in evaluating the economic losses caused by maritime traffic accidents, and can provide a strong guarantee for maritime traffic.
Zheng, S.; Wang, L.; Chen, R.; Xing, F., and Chen, J., 2019. Cost estimation method of coastal navigation sign measurement and control project based on Big Data's analysis. In: Guido-Aldana, P.A. and ...Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 830–835. Coconut Creek (Florida), ISSN 0749-0208. The method for estimating and controlling the coastal navigation mark measurement and control cost of the coastal navigation mark measurement and control project is to maintain the safety of the coastal navigation mark measurement and control project, to reduce the cost of the project and to guarantee the service level. The traditional cost estimation method of the coastal navigation mark measurement and control project is based on the experience-based evaluation of the cost prediction model of the coastal navigation mark measurement and control engineering, which cannot effectively meet the principle of minimizing the present value of the measurement and control cost of the coastal navigation mark and the maximization of the state index during the service life period. In this paper, a method for estimating the cost of a coastal navigation mark measurement and control project based on the characteristics of large data correlation is proposed, and the measurement and control model of the conventional coastal navigation mark is designed. Cost estimation model of coastal navigation mark measurement and control project based on performance and energy supply survival period assessment model based on comprehensive coastal navigation mark measurement and control strategy. The cost estimation model of the coastal navigation mark measurement and control engineering is designed by using the first-order Bessel function, a reliable index evaluation equation of the cost all-sample regression analysis is obtained, the measurement and control cost of the coastal navigation mark, the user cost and the social cost are calculated. The cost present value of the measurement and control project of the coastal navigation mark is minimized as the objective function, and the financial constraint and the performance constraint are obtained as the boundary conditions. The plan optimization of the cost of the measurement and control engineering of the coastal navigation mark is realized, and the measurement and control scheme of the coastal navigation mark with the minimum cost present value is obtained under the limited financial resources. The numerical simulation results show that the model can improve the reliability and reliability of the measurement and control engineering structure of the coastal navigation mark, optimize the measurement and control cost of the coastal navigation mark, and obtain the minimum measurement and control scheme of the coastal navigation mark with the minimum cost present value under the limited financial resources, thus saving the measurement and control cost of the coastal navigation mark by 15%.
PDF
