• Journal of Sensor Science and Technology
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• v.30 no.1
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• pp.1-9
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• 2021

This mini review summarizes some of the recent advances in machine-learning (ML)-driven chemical and biological sensors. Specific focus is on field-effect-transistor (FET)-based sensors with a description of their structures and detection mechanisms. Key ML techniques are briefly reviewed for an audience not familiar with the basic principles. We mainly discuss two aspects: (1) data analysis based on ML and (2) ML applied to sensor design. In conclusion, the challenges and opportunities for the advancement of ML-based sensors are briefly considered.

• Korean Medical Education Review
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• v.23 no.3
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• pp.145-146
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• 2021

• The Mathematical Education
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• v.43 no.3
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• pp.291-307
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• 2004

This study focused on the developing a system of computer adaptive diagnosis and instruction(CADI). This system is a conceptual model that connected learning with assesment by using new media such as computers, multimedia, and new technologies. In this conceptual model, adaptive diagnosis means tailored or customized diagnostic evaluation, and adaptive instruction implies tailored or customized instruction. The connection between learning and assesment suggests that they are closely related to determine following learning contents and learning methods. CADI's expected effect are 1) it can contribute to real learning of core concept, 2) it can enlarge the educational opportunities, 3) it can help students study by student himself and learn media literacy, 4) information for evaluation functions more essential roles, 5) it is possible to work cooperatively with any other school subject.

• Education of Primary School Mathematics
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• v.24 no.4
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• pp.203-216
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• 2021

Seeing the elapsed time as a quantity that can be measured is quite challenging for students while making students see it is also challenging for teachers. Tuning on these challenges, this article reports on what learning opportunities elementary teachers provide when they teach elapsed time focusing on quantitative objectification. I observed three mathematics classrooms where the elapsed time was taught by three elementary teachers and did a narrative analysis on the instructions. All three teachers utilized certain tools to support students access to the elapsed time as a quantity. They appropriated various quantitative attributes of the tool. In the case of the analog clock, one teacher tried to quantification the elapsed time with the number of minute hand's turning, while the other teacher indicated the distance of minute hand's moving. One teacher represented the elapsed time with the longitudinal attribute of the time band. Standing on the findings, the didactical implications of various attempts for quantitative objectification of the elapsed time implemented were discussed.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.293-300
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• 2018

To realize various opportunities to choose careers for adolescent sports players, first, it is necessary to help them choose a job suitable for each student's aptitude. In reality, adolescent sports players absolutely have insufficient time for choosing various careers unlike general adolescents and realizing them. Thus, differentiated and specialized convergence learning materials are needed by each job cluster suitable for adolescent sports players' aptitude. The learning materials, specialized for these individual job clusters are a method to show a great effect on education with investing the minimum time, so they have a high value for utilization as necessary learning information for the realization of various opportunities to choose various careers for adolescent sports players.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1085-1092
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• 2022

Travel distance is a parameter mainly used in the objective function of Construction Site Layout Planning (CSLP) automation models. To obtain travel distance, common approaches, such as linear distance, shortest-distance algorithm, visibility graph, and access road path, concentrate only on identifying the shortest path. However, humans do not necessarily follow one shortest path but can choose a safer and more comfortable path according to their situation within a reasonable range. Thus, paths generated by these approaches may be different from the actual paths of the workers, which may cause a decrease in the reliability of the optimized construction site layout. To solve this problem, this paper adopts reinforcement learning (RL) inspired by various concepts of cognitive science and behavioral psychology to generate a realistic path that mimics the decision-making and behavioral processes of wayfinding of workers on the construction site. To do so, in this paper, the collection of human wayfinding tendencies and the characteristics of the walking environment of construction sites are investigated and the importance of taking these into account in simulating the actual path of workers is emphasized. Furthermore, a simulation developed by mapping the identified tendencies to the reward design shows that the RL agent behaves like a real construction worker. Based on the research findings, some opportunities and challenges were proposed. This study contributes to simulating the potential path of workers based on deep RL, which can be utilized to calculate the travel distance of CSLP automation models, contributing to providing more reliable solutions.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.63-66
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• 2000

WBI provides new opportunities to realize the flexible learning environment based on hypermedia and to support distance learning with a diverse interaction. The instructors or learners in WBI claim to be able to resolve reluctant fluctuations such as disorientation and cognitive overload. To overcome these phenomena, a supplementary tool able to manage learning space organized by the instructor's or learner's own way and offer effective navigation techniques is presented in this paper. A learning space management and navigation tool called HyperMap dynamically represents the learning space in the form of a two-dimensional labeled graph. This HyperMap also can be used for an instruction design tool, learner's portfolio for the exchange of learning experiences. and the assessment of WBI.

• Smart Media Journal
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• v.11 no.2
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• pp.39-52
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• 2022

In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

• Educational Technology International
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• v.8 no.2
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• pp.21-52
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• 2007

Research related to Web-based learning (WBL) has grown exponentially in the last decade. Scholars have explored a variety of areas related to WBL, including techniques, strategies and best practices. One area of particular interest to scholars is the potential of WBL to support and facilitative collaborative learning. Despite the continued exploration, there continues to be a concern related to the theoretical foundations of WBL. The purpose of this article is to explore how different theories may be used to guide research and inform practice in online collaborative learning. We integrate the major points drawn from current research and theory from a variety of perspectives so as to gain a better understanding of how learning is enabled by asynchronous modes of online collaborative learning. We then use this understanding to identify opportunities and challenges for theory development and research in WBL.

• Journal of Engineering Education Research
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• v.27 no.1
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• pp.32-40
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• 2024

This study attempted to develop an efficient management plan that allows both workers and organizations to coexist by analyzing the factors that influence the level of organizational immersion of engineering students. Analysis methods included frequency analysis, t-test, pearson correlation analysis, and hierarchical analysis. Firstly, self-esteem and transfer of learning were influential factors on organizational commitment. Second, self-esteem and transfer of learning were influencing factors of self-efficacy. Third, self-efficacy was an influential factor in organizational commitment. Fourth, self-efficacy appeared as a mediating effect on self-esteem and organizational immersion in learning transfer. Therefore, it is necessary to look for various factors that can increase self-efficacy, and to find opportunities for students to be highly immersed in the organization while studying at the same time.