Model of Knowledge-Based Process Management System Using Big Data in the Wireless Communication Environment

Noh, Kyoo-Sung

doi:10.1007/s11277-017-4769-z

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…This value is greater than 39%, indicating that the excess fluid retains the extracellular fluid, and the increase of the extracellular water is greater than the normal value. More than 30% increase can be observed [ 6 ]. By accurately measuring the intracellular and extracellular parameters of water and edema, it is possible to know whether there is an abnormal distribution of water in patients without clinical manifestations [ 7 ], and diuretic treatment may be enhanced or weakened according to its value.…”

Section: Respiratory Care Of Big Data Communication On the Nursing An...mentioning

confidence: 99%

[Retracted] Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure

Lin

Feng

et al. 2022

BioMed Research International

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Heart failure is the final stage of the development of heart disease, with a high mortality and disability rate. It poses a serious threat to human health and brings tremendous pressure to human society. Preventing respiratory infections in patients with heart failure is also the first priority of care. This article is aimed at studying the nursing analysis of respiratory tract care based on big data exchanges to prevent respiratory tract infections in patients with heart failure. This article uses benchmark and sample collection. Studies have shown that for Pseudomonas aeruginosa, its resistance to ampicillin, amoxicillin/clavulanic acid, cefazolin, cefuroxime, ceftriaxone, cefotaxime, and cefoxitin has reached more than 80%. It is also suitable for piperacillin, ticarcillin/clavulanic acid, piperacillin/tazobactam, cefepime, aztreonam, gentamicin, tobramycin, ciprofloxacin, and levofloxacin. The resistance rate of stars is within 10%-30%. These antibiotics are effective and can be used for clinical treatment. The drug resistance rates of ceftazidime, imipenem, meropenem, and amikacin were all lower than 10%, and the drug resistance rates of ceftazidime and imipenem were much lower than those reported in the 2016 literature. These antibiotics have become the most effective drugs for the treatment of Pseudomonas aeruginosa infections. Basically, good communication of respiratory care data is realized, thereby preventing respiratory care analysis of patients with heart failure.

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Section: Respiratory Care Of Big Data Communication On the Nursing An...mentioning

confidence: 99%

[Retracted] Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure

Lin

Feng

et al. 2022

BioMed Research International

View full text Add to dashboard Cite

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“…O Big Data é uma tecnologia inteligente criada para administrar um grande volume de informações, por meio da aplicação de técnicas analíticas utilizadas para avaliar conjuntos de dados extremamente grandes, de alta complexidade, de origens diversificadas, que variam de sensores às mídias sociais (Chen, Chiang & Storey, 2012). O Big Data pode contribuir para o desenvolvimento de pesquisas, para o design, cadeia de suprimento, serviços, vendas, marketing, entre outras áreas (Noh, 2018).…”

Section: Autônomo E Inteligenteunclassified

Economia e administração: ligação para o desenvolvimento

2022

Economia E Administração: Ligação Para O Desenvolvimento

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A Indústria 4.0 é um conceito que vem se expandindo pelo mundo, oferecendo uma nova configuração para a indústria a partir de um conjunto de inovações e princípios que, quando somados, podem alavancar os resultados organizacionais, modificando sua estrutura produtiva, gerencial e cultural, impactando, inclusive, a forma como a organização se relaciona com seus stakeholders e comunica seu valor para o consumidor.O termo "indústria 4.0" faz alusão aos avanços mais recentes da tecnologia, que visam a promover a interação entre os mundos físico, digital e biológico, criando um modelo de cadeia de valor inteligente, interligada e ágil (Cara, 2021). A criação de condições favoráveis ao desenvolvimento da indústria 4.0 engloba inúmeros fatores, tais como incentivos fiscais, acesso a mercados globais, proximidade a centros de ensino e investigação, disponibilidade de capital, cultura empreendedora, integração em rede, motivações pessoais dos investidores, infraestruturas de tecnológica de informação, dimensão empresarial, relutância à mudança, a idade da empresa, os recursos financeiros e os recursos humanos (Balasingham, 2016).Apesar da Indústria 4.0 ser um fenômeno global, implementável em toda a cadeia produtiva, inclusive de empresas de pequeno porte, muitas organizações ainda se encontram distantes dessa realidade (Kupfer, 2016). De acordo com o Índice Global de Inovação 2018, o Brasil tem alcançado resultados significativos em várias áreas da sociedade, contudo, no que diz respeito à inovação e tecnologia, o país ainda se encontra na 64ª posição no ranking mundial das economias com maiores capacidades e sucesso de inovação. Dados do Ministério da Ciência, Tecnologia, Inovações e Comunicações (MCTIC, 2018) informam que investimentos em Pesquisa e Desenvolvimento (P&D) ainda são escassos, sendo dispendidos apenas US$ 43 bilhões de dólares em 2015, enquanto na China o capital nesse setor chegou a US$ 407 bilhões, e nos Estados Unidos, a US$ 496 bilhões. Estudos realizados pela Confederação Nacional da Indústria (CNI, 2016) revelam que apenas 48% da indústria nacional utiliza tecnologias digitais. No que diz respeito às pequenas e médias empresas, o problema é ainda maior, levando em consideração as dificuldades das empresas desse porte de sobreviver a crises econômicas e acessar linhas de financiamento para modernização do parque fabril, se comparadas às grandes empresas (Finep, 2019).

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“…Combined with fuzzy C-means clustering and linear regression analysis [23,24], the statistical analysis of big data's numerical attribute feature information is carried out, and the statistical feature equation is described as follows:…”

Section: Big Data Fuzzy Weighted Clustering Optimizationmentioning

confidence: 99%

Fuzzy Weighted Clustering Method for Numerical Attributes of Communication Big Data Based on Cloud Computing

2020

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It is necessary to optimize clustering processing of communication big data numerical attribute feature information in order to improve the ability of numerical attribute mining of communication big data, and thus a big data clustering algorithm based on cloud computing was proposed. The cloud extended distributed feature fitting method was used to process the numerical attribute linear programming of communication big data, and the mutual information feature quantity of communication big data numerical attribute was extracted. Combined with fuzzy C-means clustering and linear regression analysis, the statistical analysis of big data numerical attribute feature information was carried out, and the associated attribute sample set of communication big data numerical attribute cloud grid distribution was constructed. Cloud computing and adaptive quantitative recurrent classifiers were used for data classification, and block template matching and multi-sensor information fusion were combined to search the clustering center automatically to improve the convergence of clustering. The simulation results show that, after the application of this method, the information fusion performance of the clustering process was better, the automatic searching ability of the data clustering center was stronger, the frequency domain equalization control effect was good, the bit error rate was low, the energy consumption was small, and the ability of fuzzy weighted clustering retrieval of numerical attributes of communication big data was effectively improved.

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Model of Knowledge-Based Process Management System Using Big Data in the Wireless Communication Environment

Cited by 8 publications

References 12 publications

[Retracted] Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure

[Retracted] Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure

Economia e administração: ligação para o desenvolvimento

Fuzzy Weighted Clustering Method for Numerical Attributes of Communication Big Data Based on Cloud Computing

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