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Artificial Intelligence - Crossref

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Last Updated: 10 September 2022

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Analysis of the Effect of Classroom Reform of English Literature on the Theme of Environmental Protection in Universities Based on Artificial Intelligence Technology

The impact of English literature classroom teaching reforms cannot be quantified quantitatively under the current trend of environmental safety. We present an analytic model of the effect of College English Literature Classroom Teaching Reform on environmental security based on artificial intelligence technology. We investigate the teaching reform of English literature classrooms with the theme of environmental protection under artificial intelligence technology, as well as the construction of the university English ecological teaching mode. This paper analyzes the effect of college English literature classroom reform on the topic of environmental protection in light of in-depth research of teaching evidence. The 90. 97, 86. 3, 84. 8, 94. 8, and 87. 4, respectively, according to the six effect analysis indicators of teaching attitude, teaching equipment, improvement curriculum, classroom organization, and reform rationality are the results of the model based on the BP neural network under the six effect analysis measures of teaching effectiveness, teaching methods, 85. 6, 84. 8, and 87. 4, respectively.

Source link: https://doi.org/10.1155/2022/2178579


Interwell Log Correlation Using Artificial Intelligence Approach and Multivariate Statistical Analysis

Abstract Introduction To automated interwell log correlation using both artificial intelligence and multivariate statistical analysis is discussed. Correlation of wireline logging results is based on a large number of subjective control for pattern recognition that is supposed to represent human logical processes. The shapes extracted along log traces by object-oriented programming are the characteristics of the shapes extracted along log traces. By a rule-based inference scheme, the correlating of zones between wells is achieved. Correspondence can be established by using the first principal component log, since it has the most common component of all available well-log data. Correlated results with logging data in the Korea Continental Shelf and oversea field show that this method can be used to improve interwell log correlations that are more accurate and cost effective to interwell log correlation rather than the traditional methods, in which only one approach was adopted.

Source link: https://doi.org/10.2118/54362-ms


Analysis of Psychological Shaping Function of Music Education under the Background of Artificial Intelligence

This paper explores the ways of integrating intelligent technology into music education in order to solve the problem of music education, music education, creation of a Yi Guzheng platform, the integration of online sparring technologies, and the efficient use of Mu class resources; and the design of a loop curriculum module with u201cintelligent pianos. The c3j refers to the learning process of music education in a region of exceptional psychological stability of music.

Source link: https://doi.org/10.1155/2022/7162069


Diagnostic Performance of Artificial Intelligence for Interpreting Thyroid Cancer in Ultrasound images

Thyroid ultrasonography is mainly used for the detection and analysis of thyroid nodules. The resident and the veteran radiologist, respectively, had similar diagnostic sensitivity and specificity to the experienced radiologist and the resident, with only slightly higher precision and accuracy in AI than the novice and the resident.

Source link: https://doi.org/10.4018/ijkss.309431


A Role of Artificial Intelligence in Healthcare Data for Diabetic People Affected by COVID-19

Diabetes sufferers are vulnerable, and if a COVID-19 infection is present, the patient must be treated effectively, with a focus on fighting the virus while simultaneously maintaining homeostasis and glycemic control. This report explores the current state of knowledge and limitations in using AI to help diabetic and chronic patients with diabetes and COVID-19 infections. In addition, patient satisfaction with diabetes care in the United States has risen by media and online. More research is needed in the future to ensure diabetic patients' psychological and nutritional wellbeing, as well as lowering their healthcare costs by developing targeted AI systems, but more research is needed.

Source link: https://doi.org/10.4018/ijoris.306196


Knowledge Management in Relationship Among Abusive Management, Self-Efficacy, and Corporate Performance Under Artificial Intelligence

The aim is to investigate the use of HCI technology under AI in enterprise productivity analysis and analysis of organization effectiveness, as well as the impact of abusive leadership and self-efficacy on enterprise results. The employee job satisfaction and performance measurement framework and system interface based on deep learning BPNN, SVM regression, and HCI are then introduced. According to the employee's verbal instructions, the HCI interface can be accessed properly. The findings show that according to the employee's verbal instructions, the HCI interface can be accessed more efficiently.

Source link: https://doi.org/10.4018/jgim.307067


The Progress of Business Analytics and Knowledge Management for Enterprise Performance Using Artificial Intelligence and Man-Machine Coordination

This research seeks to investigate the integration of human-computer interaction technology and the platform ecosystem in the artificial intelligence environment, providing a practical basis for the effective development of platform ecosystems. To build the fashion data warehouse in Then, the fashion knowledge management software is used. The platform-intel clothing ecosystem is being introduced by the innovative design of business analytics and management mode of the clothing e-commerce industry.

Source link: https://doi.org/10.4018/jgim.302642


Self-Regulated Learning and Scientific Research Using Artificial Intelligence for Higher Education Systems

Students in the learning process are highly involved in student retention, and SRL techniques are used to support students in learning effectively in higher education. The artificial intelligence framework for self-regulated learning overcame the SRL environment's challenges in higher education, resulting in this paper. Students who participate in their education are active participants in their learning, and they can choose from a strategic portfolio and monitor their progress toward the goal.

Source link: https://doi.org/10.4018/ijthi.306226

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions