This research examines those related to Artificial Intelligence, stock robotics, and revenue intruments portfolio diversity in the context of the Fourth Industrial Revolution era, artificial intelligence, and concern for the environment. First, our results suggest that a portfolio of these assets is highly dependent, suggesting that large mutual losses are likely to occur during times of disruption in the economy. Second, it supports a large market mood in the near future, indicating that this disruption in the approaching time can increase the market mood of assets, while to support the market mood decreases for a long time.
This research examines those related to Artificial Intelligence, stock robotics, and revenue intruments portfolio diversity in the context of the Fourth Industrial Revolution era, artificial intelligence, and concern for the environment. First, our results suggest that a portfolio of these assets is highly dependent, suggesting that large mutual losses are likely to occur during times of disruption in the economy. Second, it supports a large market mood in the near future, indicating that this disruption in the approaching time can increase the market mood of assets, while to support the market mood decreases for a long time.
In the Information Systems Department of Raharja University, where blended learning is used, this study intends to describe the propensity for student learning independence. Data analysis is done using percentages utilizing a descriptive quantitative methodology. There were 90 respondents in the study, which included students from the class of 2021 in the department of information systems at Raharja University. An open-ended statement-style questionnaire with a Likert scale was utilized to collect the data. According to the findings, student learning about independence is generally beneficial. Each variable indicative of learning independence yielded analytical results that fell into the group of favorable outcomes. The percentage results for each indicator are as follows: 1) independence from other people is 78%; 2) confidence is 75%; 3) disciplined behavior is 74%; 4) sense of responsibility is 78%; 5) act on own initiative is 75%; and 6) exercising self control is 76%. While using blended learning, teachers can more easily guide their students through the learning process.
For its potential to facilitate the development of cutting-edgetechnologies with enhanced environmental performances,projected useat basic levels of life cycle analysis (LCA)technological readiness levels (TRL) has attracted enormousinterest in recent literature. But the normal LCA standardsfind it very difficult to evaluate developing technologies,necessitating methodological advancements in the presentLCA framework due to inadequate data, questionablefunctioning, scale-up problems, and uncertainties. We reviewpublished literature in this paper to identify majormethodological challenges and key research efforts to addressthese issues, with a focus on recent developments in five keyareas: cross-study comparability, data availability and quality,scale-up issues, uncertainty and uncertainty communication,and assessment time. Additionally, we provide a number ofsuggestions for further study to assist in the assessment of newtechnologies at low technical readiness level: (1) the creation of auniform framework and reporting procedures for life cycleassessments (LCAs) of developing technologies; (2) theincorporation of additional tools with LCA; and (3) the creation of adata repository for cutting-edge materials, procedures, andtechnologies. Decision-making techniques, such as multicriteriadecision analysis, risk analysis, and techno-economic analysis.
In the Information Systems Department of Raharja University, where blended learning is used, this study intends to describe the propensity for student learning independence. Data analysis is done using percentages utilizing a descriptive quantitative methodology. There were 90 respondents in the study, which included students from the class of 2021 in the department of information systems at Raharja University. An open-ended statement-style questionnaire with a Likert scale was utilized to collect the data. According to the findings, student learning about independence is generally beneficial. Each variable indicative of learning independence yielded analytical results that fell into the group of favorable outcomes. The percentage results for each indicator are as follows: 1) independence from other people is 78%; 2) confidence is 75%; 3) disciplined behavior is 74%; 4) sense of responsibility is 78%; 5) act on own initiative is 75%; and 6) exercising self control is 76%. While using blended learning, teachers can more easily guide their students through the learning process.
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