With the advancement of technology, generative AI systems, especially models like ChatGPT, show significant potential for development in future smart court systems. Traditional adjudication models are dominated by judges, but with the intervention of AI, algorithms and data will jointly influence the entire adjudication process. The quality of data governance will directly impact the outcomes of judicial cases. By exploring the application of ChatGPT in judicial decision support and analyzing its data processing advantages, usability, feedback capability, and trainability, we can see how these factors facilitate the judicial decision-making process. The efficient and precise algorithms, combined with vast amounts of data, demonstrate ChatGPT's superiority in processing and analyzing legal information. Undoubtedly, the application of AI technology can greatly improve judicial efficiency and promote the progress of smart adjudication. However, judicial decision-making is not merely a mechanical, data-driven process. The application scenarios of generative AI systems also face numerous challenges, including data deficiencies and the issue of generating hallucinations.
Literature education plays a pivotal role in fostering critical thinking, creativity, empathy, and cultural understanding among students. The traditional approaches to teach literature often face challenges in engaging students and catering to individual learning needs. There are some obstacles facing literature education, including inaccurate education, lack of varied ideas, inadequate investment, and restricted access to materials. The problems impede students' development of analytical skills and involvement in poetry education. The research proposed a novel advanced Sand cat swarm driven consecutive convolutional neural network (ASCS-CCNN) technique to investigate literature education of primary and secondary students, which improves the poetry fluency and literature strategies. Recommendation system is used to predict the best sequence of educational resource using collaborative filter. In the study, poetry data is gathered, we utilize the tokenization for data preprocessing and to extract the tokenized data, we utilize term frequency inverse document frequency (TF-IDF). The findings of the study use parameters like similarity, tone accuracy and rhyme accuracy, to evaluate student performance in poetry education. The study concludes that education in primary and secondary education improves student learning through thoughtfully selected readings that complement curricular objectives and encourage greater student involvement in appreciation of poetry.
1. Herein, the purpose of this study was to use the perspective of computational mechanics to clarify the effects of differences in the mechanical properties of welding joints, which are used as an initial process in mold-less spherical container molding, on the final molded shape. We scrutinized how factors such as the quantity and placement of explosive charges, alongside the mechanical properties of the joints, influence the final spherical shape. Our results confirm that the pressure generated from 2,4,6-trinitrotoluene (TNT) propagates through water as a shock wave, eventually reaching stainless steel (SUS304) and inducing deformation. Through computational analysis, we derived the following insights:A TNT explosive dosage of 10 g proves optimal for the model. 2. Depending on the position of the explosive charge, convex deformation occurs, with the degree of convexity increasing with the position of the explosive charge. 3. Material heterogeneity stemming from welding joints results in the generation of low pressure. As a culmination of this computational investigation, we were able to investigate moldless hydro plastic processing, offering valuable insights from a mechanics viewpoint.
With the rapid development of science and technology, the era of big data has arrived comprehensively. Based on cognitive big data, this study conducted a survey of over 265 university teachers through questionnaire surveys. Teachers play a vital part in society, and maintaining good mental health is critical to their effectiveness in the classroom as well as to the students they guide in their personal growth and professional advancement. The fundamental mechanism that underlies the effect of social support on the psychological well-being of teachers was investigated in the present research. Big data is not only about resources and technology, but this article is based on big data processing technology. A quantitative and qualitative research design was employed, utilizing surveys, interviews, and focus group discussions to gather rich and in-depth data regarding the psychological mental health and social support of the teachers. The study participants included a purposive sample of teachers from a local college teacher. The results of the study indicated that college teachers had a substantial number of concerns regarding both their mental health and their overall welfare. Most respondents expressed anxiety regarding their current responsibilities as well as their capacity to balance their professional and personal lives. This underscores the need for good task management as well as the building of welcoming workplaces for employees. In addition, depression, stress, and anxiety were all identified as important difficulties, which highlights the requirement for mental health support services that are particularly tailored to the requirements of teachers. The findings underlined the substantial impact that perceived social support plays in the mental well-being of teachers, giving light to the issues that teachers confront as well as the support systems that they rely upon. The research highlights how vital it is for educational institutions to cultivate an atmosphere of support for their faculty members to improve their emotional health and overall well-being. In the context of big data, based on network analysis results, design intervention measures to enhance social support networks, and examine the relationship between mental health and perceived social support among College teachers. The findings demonstrate the importance of social support networks in mitigating the detrimental effects of stress on the mental health of teachers. The study highlights the significance of creating a supportive work environment and implementing interventions that address the challenges teachers experience. By prioritizing the mental health of teachers, educational institutions may establish an environment that fosters their well-being and, in turn, has a positive effect on student learning outcomes. At local College, improving teachers' mental health and their sense that they have social support can have a beneficial impact on both their overall well-being.
Web applications are utilized everywhere these days to share services and data online. Because companies deal with sensitive data, hackers have found them attractive targets. Vulnerabilities persist despite the numerous security procedures we've created to safeguard these applications. Major security issues have been identified in web applications used by various organizations, such as banks, healthcare providers, finance companies, and retail businesses. Cross-site scripting (XSS) attacks are one of the most significant issues, according to a report from White Hat Security. These attacks enable hackers to execute harmful programs on a user's web browser, resulting in issues such as the theft of data, cookies, passwords, and credit card numbers. This study focuses on the primary weaknesses present in contemporary web applications, particularly XSS attacks. We go over the many kinds of XSS attacks, provide instances from the real world, and describe how they operate. We also examine defenses against these attacks, discussing what works and what doesn't.
