Evaluation of food safety problems based on the fuzzy comprehensive analysis method

Zhao, Yingwen; Talha, Muhammad

doi:10.1590/fst.47321

Cited by 22 publications

(15 citation statements)

References 51 publications

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“…Traditional lecturing teachers can no longer meet the longitudinal and horizontal development of classroom teaching in colleges and universities, and teachers in colleges and universities must improve their information literacy and develop to TPACK ability comprehensively. On the one hand is the challenge brought by the change of teaching methods and teaching model in the new era; on the other hand is the challenge brought by the general enhancement of students' information literacy [ 24 ]. To a large extent, this is due to the fact that many noninformation college instructors were never exposed to contemporary information technology in school.…”

Section: Analysis Of Resultsmentioning

confidence: 99%

A Coordinated and Optimized Mechanism of Artificial Intelligence for Student Management by College Counselors Based on Big Data

Yang

Talha

2021

Computational and Mathematical Methods in Medicine

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The purpose of this article is to perform in-depth research and analysis on the artificial intelligence coordination and optimization mechanism of college counseling student management using big data technology. This study places the collaborative ideological and political work of colleges and universities in the context of big data, and by analyzing its basic connotation and changes in the real situation, it explores the development progression of colleges and universities making full use of big data resources to cultivate a collaborative education model, which is conducive to promoting colleges and universities to cultivate a whole staff, whole process, and all-round accurate ideological education and value-led services and to shape excellent young college students with comprehensive growth. The first is to scientifically build a multilevel linked big data management platform for counselor professionalization construction, plan the technical architecture of the organizational platform, build a cloud database of counselor career files, and extract valuable information and data from the organizational activities at the macrolevel and personal activities at the microlevel with counselor professionalization construction activities; the second is to realize the integrated application of information resources for counselor team construction. The second is to realize the integrated application of counselor team construction information resources, visualise and accurately analyze and evaluate the counselor group’s focus on career development and individual counselors’ feedback on career capacity construction, and improve the overall construction, personalized education management level, and self-improvement development ability. Fourth, in the professionalization of counselors, attention should be paid to the scientific selection and prevention of risks of big data application, ensuring the authenticity and reliability of data and leakage prevention and control, etc.

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Section: Analysis Of Resultsmentioning

confidence: 99%

A Coordinated and Optimized Mechanism of Artificial Intelligence for Student Management by College Counselors Based on Big Data

Yang

Talha

2021

Computational and Mathematical Methods in Medicine

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“…The goal of correlation analysis is to find frequently recurring patterns in data and then describe the connection between two events or objects concealed in the data; however, these correlations can only be utilised as a starting point for further research. The economic activities of any unit are not carried out in isolation and always have to contact the relevant external departments or units, and it is generally believed that external data has greater credibility [ 21 ]. Auditors may only conduct an objective and fair assessment of the audit object by creating a systemic perspective, that is, auditing the economic behavior of the audited unit itself and evaluating its relationship with the outside, while auditing a particular unit.…”

Section: Discussionmentioning

confidence: 99%

Audit Data Analysis and Application Based on Correlation Analysis Algorithm

Chen

Talha

2021

Computational and Mathematical Methods in Medicine

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Traditional audit data analysis algorithms have many shortcomings, such as the lack of means to mine the hidden audit clues behind the data, the difficulty of finding increasingly hidden cheating techniques caused by the electronic and networked environment, and the inability to solve the quality defects of the audited data. Correlation analysis algorithm in data mining technology is an effective means to obtain knowledge from massive data, which can complete, muffle, clean, and reduce defective data and then can analyze massive data and obtain audit trails under the guidance of expert experience or analysts. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounds the research status and significance of audit data analysis and application; elaborates the development background, current status, and future challenges of correlation analysis algorithm; introduces the methods and principles of data model and its conversion and audit model construction; conducts audit data collection and cleaning; implements audit data preprocessing and its algorithm description; performs audit data analysis based on correlation analysis algorithm; analyzes the hidden node activation value and audit rule extraction in correlation analysis algorithm; proposes the application of audit data based on correlation analysis algorithm; discusses the relationship between audit data quality and audit risk; and finally compares different data mining algorithms in audit data analysis. The findings demonstrate that by analyzing association rules, the correlation analysis algorithm can determine the significance of a huge quantity of audit data and characterise the degree to which linked events would occur concurrently or sequentially in a probabilistic manner. The correlation analysis algorithm first inputs the collected audit data through preprocessing module to filter out useless data and then organizes the obtained data into a format that can be recognized by data mining algorithm and executes the correlation analysis algorithm on the sorted data; finally, the obtained hidden data is divided into normal data and suspicious data by comparing it with the pattern in the rule base. The algorithm can conduct in-depth analysis and research on the company’s accounting vouchers, account books, and a large number of financial accounting data and other data of various natures in the company’s accounting vouchers; reveal its original characteristics and internal connections; and turn it into an audit. People need more direct and useful information. The study results of this paper provide a reference for further researches on audit data analysis and application based on correlation analysis algorithm.

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“…In this way, a vector of cortical voxel responses corresponding to each image stimulus can be obtained, which makes up the final fMRI dataset. In addition, multiple subjects are usually selected to perform the same experiment and to acquire and process the data, thus including multiple sets of fMRI data from multiple subjects for subsequent validation of the robustness of the computational model on different subject data [ 18 ].

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Section: Analysis Of Neuroimaging Recognition Techniques For Assessing the Complexity Of Chronic Pain In Elderly Knee Osteoarthritismentioning

confidence: 99%

Complexity Assessment of Chronic Pain in Elderly Knee Osteoarthritis Based on Neuroimaging Recognition Techniques

Liu

et al. 2021

Computational and Mathematical Methods in Medicine

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The chronic pain of knee osteoarthritis in the elderly is investigated in detail in this paper, as well as the complexity of chronic pain utilising neuroimaging recognition techniques. Chronic pain in knee osteoarthritis (KOA) has a major effect on patients’ quality of life and functional activities; therefore, understanding the causes of KOA pain and the analgesic advantages of different therapies is important. In recent years, neuroimaging techniques have become increasingly important in basic and clinical pain research. Thanks to the application and development of neuroimaging techniques in the study of chronic pain in KOA, researchers have found that chronic pain in KOA contains both injury-receptive and neuropathic pain components. The neuropathic pain mechanism that causes KOA pain is complicated, and it may be produced by peripheral or central sensitization, but it has not gotten enough attention in clinical practice, and there is no agreement on how to treat combination neuropathic pain KOA. As a result, using neuroimaging techniques such as magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS), this review examines the changes in brain pathophysiology-related regions caused by KOA pain, compares the latest results in pain assessment and prediction, and clarifies the central brain analgesic mechanistic. The capsule network model is introduced in this paper from the perspective of deep learning network structure to construct an information-complete and reversible image low-level feature bridge using isotropic representation, predict the corresponding capsule features from MRI voxel responses, and then, complete the accurate reconstruction of simple images using inverse transformation. The proposed model improves the structural similarity index by about 10%, improves the reconstruction performance of low-level feature content in simple images by about 10%, and achieves feature interpretation and analysis of low-level visual cortical fMRI voxels by visualising capsule features, according to the experimental results.

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Evaluation of food safety problems based on the fuzzy comprehensive analysis method

Cited by 22 publications

References 51 publications

A Coordinated and Optimized Mechanism of Artificial Intelligence for Student Management by College Counselors Based on Big Data

A Coordinated and Optimized Mechanism of Artificial Intelligence for Student Management by College Counselors Based on Big Data

Audit Data Analysis and Application Based on Correlation Analysis Algorithm

Complexity Assessment of Chronic Pain in Elderly Knee Osteoarthritis Based on Neuroimaging Recognition Techniques

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