• Journal of The Korean Association For Science Education
• /
• v.22 no.5
• /
• pp.991-1009
• /
• 2002

This qualitative study investigated two preservice teachers' conceptual ecologies in professional development during the science teacher preparation program. The notion of a conceptual ecology contains nature of knowledge, science and science teaching, learning, and content knowledge and comfort level. The data were collected during the participants' preservice year and their practicum experience. Both data collections and analyzing were from the various sources of interviews, teaching observations, journals, and information and profiles by the participants' supervisor. Two preservice teachers serve as cases representative of this study. Results show that problems preventing the preservice teachers from moving closer to conceptual change teaching were their understandings of the nature of science and the nature of knowledge. The preservice teachers' views about knowledge come from, and what knowledge is, are largely shaped by the nature of science and learning drive pedagogy and classroom practice. Knowledge of and comfort with the subject matter are also important.

• Journal of Energy Engineering
• /
• v.15 no.4 s.48
• /
• pp.209-228
• /
• 2006

The learning effect is one of the theoretical frameworks that examine the mechanisms of the deployment of energy technologies. The objective of this paper is to provide a theoretical overview and a critical analysis of the literature on the experience curve for energy technology. For these objectives, we review a couple of theoretical aspects and applications and investigate the sources of learning and cost reductions to grasp the mechanisms of teaming effect. Finally we conclude some insights from our theoretical reviews.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.75-79
• /
• 2021

The article covered theoretical aspects use of information and communication technologies in teaching. Information and communication technologies are technologies that allow you to search, process and assimilate information from various sources, including the Internet. This is the presentation of information in electronic form, its processing and storage, the use of the computer, a variety of programs. The use of information and communication technologies in the work of a student gives an increase in motivation for learning; increased cognitive interest; evaluate their learning activities, identify the problems of their own educational activities; the formation of cognitive independence of students.

• New & Renewable Energy
• /
• v.18 no.2
• /
• pp.18-25
• /
• 2022

In this study, we propose a wind power generation prediction system that applies machine learning and data mining to predict wind power generation. This system increases the utilization rate of new and renewable energy sources. For time-series data, the data set was established by measuring wind speed, wind generation, and environmental factors influencing the wind speed. The data set was pre-processed so that it could be applied appropriately to the model. The prediction system applied the CNN (Convolutional Neural Network) to the data mining process and then used the LSTM (Long Short-Term Memory) to learn and make predictions. The preciseness of the proposed system is verified by comparing the prediction data with the actual data, according to the presence or absence of data mining in the model of the prediction system.

• Journal of Sensor Science and Technology
• /
• v.32 no.6
• /
• pp.475-480
• /
• 2023

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.2
• /
• pp.23-27
• /
• 2024

Underwater images are typically degraded due to color distortion, light absorption, scattering, and noise from artificial light sources. Restoration of these images is an essential task in many underwater applications. In this paper, we propose a two-phase deep learning-based method, Underwater Deep Curve Estimation (UWDCE), designed to effectively enhance the quality of underwater images. The first phase involves a white balancing and color correction technique to compensate for color imbalances. The second phase introduces a novel deep learning model, UWDCE, to learn the mapping between the color-corrected image and its best-fitting curve parameter maps. The model operates iteratively, applying light-enhancement curves to achieve better contrast and maintain pixel values within a normalized range. The results demonstrate the effectiveness of our method, producing higher-quality images compared to state-of-the-art methods.

• Nuclear Engineering and Technology
• /
• v.55 no.11
• /
• pp.4282-4286
• /
• 2023

Nuclear energy is estimated by the machine learning method as the mathematical quantifications where neural networking is the major algorithm of the data propagations from input to output. As the aspect of nuclear energy, the other energy sources of the traditional carbon emission-characterized oil and coal are compared. The artificial intelligence (AI) oriented algorithm like the intelligence of a robot is applied to the modeling in which the mimicking of biological neurons is utilized in the mathematical calculations. There are graphs for nuclear priority weighted by climate factor and for carbon dioxide mitigation weighted by climate factor in which the carbon dioxide quantities are divided by the weighting that produces some results. Nuclear Priority and CO2 Mitigation values give the dimensionless values that are the comparative quantities with the normalization in 2010. The values are 1.0 in 2010 of the graphs which are changed to 24.318 and 0.0657 in 2040, respectively. So, the carbon dioxide emissions could be reduced in this study.

• International Journal of Contents
• /
• v.15 no.4
• /
• pp.1-7
• /
• 2019

As the recent developments of artificial intelligence, particularly machine-learning, impact every aspect of society, they are also increasingly influencing creative fields manifested as new artistic tools and inspirational sources. However, as more artists integrate the technology into their creative works, the issues of diversity and fairness are also emerging in the AI-based creative practice. The data dependency of machine-learning algorithms can amplify the social injustice existing in the real world. In this paper, we present an interactive visualization system for raising the awareness of the diversity and fairness issues. Rather than resorting to education, campaign, or laws on those issues, we have developed a web & ML-based interactive data visualization system. By providing the interactive visual experience on the issues in interesting ways as the form of web content which anyone can access from anywhere, we strive to raise the public awareness of the issues and alleviate the important ethical problems. In this paper, we present the process of developing the ML-based interactive visualization system and discuss the results of this project. The proposed approach can be applied to other areas requiring attention to the issues.

• School Mathematics
• /
• v.12 no.1
• /
• pp.17-26
• /
• 2010

The purposes of this study were to understand mathematics teachers' difficulties under the context of community and to contribute to the research on professional development using a partnership between a high school and a university. I examined what struggles mathematics teachers had in building a learning community. I used data from a project in South East area in U.S.A. Three student teachers, three mentor teachers, and a university teacher participated in this study. Data sources included cluster meeting observations, interviews, and documents (such as open-ended surveys and e-mail responses). Data were analyzed using case study and narrative analysis methods. The results showed that the participants had power issues, issues about selecting topics to discuss, criticizing others, sharing goals, and managing time and the number of members.

• Journal of Information Science Theory and Practice
• /
• v.6 no.1
• /
• pp.45-64
• /
• 2018

The global information economy is transforming the way people connect with each other, learn new things, and contribute to the knowledge society. With the online platform, library services have also expanded beyond face to face interaction. Although studies of virtual reference services have been made in different parts of the world, a case study discussing various forms of online reference engagement in Kazakhstan has not been written. While most of the theories on connectivism emphasize the context of instruction, the researchers of this paper discussed the tenets as they relate to online engagement. Applying the theory of connectivism, this paper explores through a mixed method the use of various online platforms to enhance engagement connecting library users to information. Findings revealed that differences in patterns of interactions as to platforms, types of queries, and users reveal that students, faculty, and other members of the academic community served by the library have various preferences for communication. The case study further showed that respondents have not maximized the use of VLS but interest in using both synchronous and asynchronous services is clear. Finding connections between sources of information, creating useful information patterns, is essential in learning. Amplifying awareness on the use of VLS giving emphasis to the unique features of each service is useful in order to enable students to see how this platform facilitates learning.