• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.15-24
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• 2023

One of the objectives and aspirations of scientists and engineers ever since the development of computers has been to interact naturally with machines. Hence features of artificial intelligence (AI) like natural language processing and natural language generation were developed. The field of AI that is thought to be expanding the fastest is interactive conversational systems. Numerous businesses have created various Virtual Personal Assistants (VPAs) using these technologies, including Apple's Siri, Amazon's Alexa, and Google Assistant, among others. Even though many chatbots have been introduced through the years to diagnose or treat psychological disorders, we are yet to have a user-friendly chatbot available. A smart generative cognitive behavioral therapy with spoken dialogue systems support was then developed using a model Persona Perception (P2) bot with Generative Pre-trained Transformer-2 (GPT-2). The model was then implemented using modern technologies in VPAs like voice recognition, Natural Language Understanding (NLU), and text-to-speech. This system is a magnificent device to help with voice-based systems because it can have therapeutic discussions with the users utilizing text and vocal interactive user experience.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.19-22
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• 2022

In this work, we studied consumers' attractiveness/usefulness perceptions (CAUP) of online commerce product photos when exposed to alternative dark/light user interface (UI) modes. We analyzed time-series EEG data from 31 individuals and performed neuroscience mining (NSM) to ascertain (a) how the CAUP of products differs among UI modes; and (b) which deep learning model provides the most accurate assessment of such neuroscience mining (NSM) business difficulties. The dark UI style increased the CAUP of the products displayed and was predicted with the greatest accuracy using a unique EEG power spectra separated wave brainwave 2D-ConvLSTM model. Then, using relative importance analysis, we used this model to determine the most relevant power spectra. Our findings are considered to contribute to the discovery of objective truths about online customers' reactions to various user interface modes used by various online marketplaces that cannot be uncovered through more traditional research approaches like as surveys.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.403-418
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• 2023

Purpose: The acceleration of technological innovation, specifically Industry 4.0, has triggered the emergence of a quality management paradigm known as Quality 4.0. This study aims to provide a systematic overview of dispersed studies on Quality 4.0 across various disciplines and to stimulate further academic discussions and industrial transformations. Methods: Text mining and machine learning approaches are applied to learn and identify key research topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview of Quality 4.0. Results: 1) A total of 27 key research topics were identified based on the analysis of 1234 research papers related to Quality 4.0. 2) A relationship among the 27 key research topics was identified. 3) A multilevel framework consisting of technological enablers, business methods and strategies, goals, application industries of Quality 4.0 was developed. 4) The trends of key research topics was analyzed. Conclusion: The identification of 27 key research topics and the development of the Quality 4.0 framework contribute to a better understanding of Quality 4.0. This research lays the groundwork for future academic and industrial advancements in the field and encourages further discussions and transformations within the industry.

• Economic and Environmental Geology
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• v.57 no.3
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• pp.329-342
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• 2024

The exponential increase in nitrate pollution of river water poses an immediate threat to public health and the environment. This contamination is primarily due to various human activities, which include the overuse of nitrogenous fertilizers in agriculture and the discharge of nitrate-rich industrial effluents into rivers. As a result, the accurate prediction and identification of contaminated areas has become a crucial and challenging task for researchers. To solve these problems, this work leads to the prediction of nitrate contamination using machine learning approaches. This paper presents a novel approach known as Grey Wolf Optimizer (GWO) based on the Stacked Ensemble approach for predicting nitrate pollution in the Cauvery Delta region of Tamilnadu, India. The proposed method is evaluated using a Cauvery River dataset from the Tamilnadu Pollution Control Board. The proposed method shows excellent performance, achieving an accuracy of 93.31%, a precision of 93%, a sensitivity of 97.53%, a specificity of 94.28%, an F1-score of 95.23%, and an ROC score of 95%. These impressive results underline the demonstration of the proposed method in accurately predicting nitrate pollution in river water and ultimately help to make informed decisions to tackle these critical environmental problems.

• Journal of The Korean Association For Science Education
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• v.27 no.8
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• pp.711-723
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• 2007

As the discourse of scientific literacy has broadly summed up the goals of science education in the current decade, this study attempts to question how we contextualize appropriate interpretations and feasible approaches to scientific literacy in K-6 science education. With respect to the complex praxis of scientific knowledge and practice, this study emphasizes the participatory framework of scientific literacy which interweaves children's everyday experiences and science learning. This study also concerns children's abilities to understand and enact scientific enterprises (i.e., children's fundamental sense of scientific literacy). As a way of developing K-6 scientific literacy, this study investigates how using science books can broaden the scope of children's understandings of science in life connections and promote a fundamental sense of scientific literacy through talking, reading, and writing skills in Grade two science classrooms in Canada. Second graders were engaged in learning "sound" for five weeks. During science lessons, children's talks were recorded and their writings were collected for data interpretation. This research finds that using science books can encourage children to become engaged in communicative activities such as talking, reading, and writing in science; furthermore, using science books develops children's inquiry skills. These findings open a further discussion on scientific literacy at the K-6 levels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2012-2027
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• 2019

Nutritional disorders are one of the most common diseases of crops and they often result in significant loss of agricultural output. Moreover, the imbalance of nutrition element not only affects plant phenotype but also threaten to the health of consumers when the concentrations above the certain threshold. A number of disease identification systems have been proposed in recent years. Either the time consuming or accuracy is difficult to meet current production management requirements. Moreover, most of the systems are hard to be extended, only detect a few kinds of common diseases with great difference. In view of the limitation of current approaches, this paper studies the effects of different trace elements on crops and establishes identification system. Specifically, we analysis and acquire eleven types of tomato nutritional disorders images. After that, we explore training and prediction effects and significances of super resolution of identification model. Then, we use pre-trained enhanced deep super-resolution network (EDSR) model to pre-processing dataset. Finally, we design and implement of diagnosis system based on deep learning. And the final results show that the average accuracy is 81.11% and the predicted time less than 0.01 second. Compared to existing methods, our solution achieves a high accuracy with much less consuming time. At the same time, the diagnosis system has good performance in expansibility and portability.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1261-1272
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• 2018

It is important to measure the Arctic surface air temperature because it plays a key-role in the exchange of energy between the ocean, sea ice, and the atmosphere. Although in-situ observations provide accurate measurements of air temperature, they are spatially limited to show the distribution of Arctic surface air temperature. In this study, we proposed machine learning-based models to estimate the Arctic surface air temperature in summer based on buoy data and Advanced Microwave Scanning Radiometer 2 (AMSR2)satellite data. Two machine learning approaches-random forest (RF) and support vector machine (SVM)-were used to estimate the air temperature twice a day according to AMSR2 observation time. Both RF and SVM showed $R^2$ of 0.84-0.88 and RMSE of $1.31-1.53^{\circ}C$. The results were compared to the surface air temperature and spatial distribution of the ERA-Interim reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). They tended to underestimate the Barents Sea, the Kara Sea, and the Baffin Bay region where no IABP buoy observations exist. This study showed both possibility and limitations of the empirical estimation of Arctic surface temperature using AMSR2 data.

• Journal of the Korean earth science society
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• v.22 no.5
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• pp.360-376
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• 2001

This qualitative research investigated in-service science teachers' perceptions about cooperative learning and their perceived barriers in implementing cooperative learning in their classrooms. The underlying premise for cooperative learning is founded in constructivist epistemology. Cooperative learning (CL) is presented as an alternative frame to the current educational system which emphasizes content memorization and individual student performance through competition. An in-depth interview was conducted with 18 in-service science teachers who enrolled in the first-class teacher certification program during 2001 summer vacation. These secondary school teachers's interview data were analyzed and categorized into three areas: teachers' definition of cooperative learning, issues with implementing cooperative learning in classrooms, and teachers' and students' responses towards cooperative learning. Each of these areas are further subdivided into 10 themes: teachers' perceived meaning of cooperative learning, the importance of talk in learning, when to use cooperative learning, how to end a cooperative class, how to group students for cooperative learning, obstacles to implementing cooperative learning, students' reactions to cooperative learning, teachers' reasons for choosing (not choosing) student-centered approaches to learning/teaching, characteristics of teachers who use cooperative learning methods, and teachers' reasons for resisting cooperative learning. Detailed descriptions of the teachers' responses and discussion on each category are provided. For the development and implementation of CL in more classrooms, there should be changes and supports in the following five areas: (1) teachers have to examine their pedagogical beliefs toward constructivist perspectives, (2) teacher (re)education programs have to provide teachers with cooperative learning opportunities in methods courses, (3) students' understanding of their changed roles (4) supports in light of curriculum materials and instructional resources, (5) supports in terms of facilities and administrators. It's important to remember that cooperative learning is not a panacea for all instructional problems. It's only one way of teaching and learning, useful for specific kinds of teaching goals and especially relevant for classrooms with a wide mix of student academic skills. Suggestions for further research are also provided.

• Journal of The Korean Association For Science Education
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• v.24 no.1
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• pp.29-47
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• 2004

Two project-centered secondary school programs were studied as part of an effort to elucidate successful components for science reform-based curriculum development. The Teachers for Exciting Science (TES), and Foundational Approaches in Science Teaching (FAST) programs in Korea and U.S., respectively, are project-centered programs because their curricula are centered on the activities initiated and engaged in by the students. Students serve as principal investigators in their projects, and teachers serve as guides. Both programs were analyzed based on criteria such as curriculum design, teaching, lives of students, lives of teachers, evaluation of program, from the Third International Mathematics and Science Study (TIMSS). In the programs, teachers and students directed the development of curricula and their implementation. Students assumed teacher roles as mentors of other students. And emphasis was on development of communication skills through student-delivered talks and written papers, and professional development of teachers as educators and scientists. Participation in TES stimulated secondary school student interest in science, encouraged inquiry thinking, increased achievement in learning science, and promoted better awareness of science related to real life. FAST students practice laboratory and field techniques, experimental design, hypothesis formation, generalization, and practical implications of research as academic and applied disciplinarians. These project-centered programs have been successfully implemented in field, lab, and classroom curricula for secondary science education. Comparison of these programs will provide an opportunity for identifying key elements instrumental in successful implementation of guidelines for science education, as measured through successful outcomes.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.85-93
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• 2004

We investigated the proper display environment for japanese electronic character reading lessons through the experiment with a projection TV and a computer. For the purpose of finding out the effect of prior learning activities at the context of authentic Japanese text orthography, which includes dual notation, words spacing, etc., we also made an experiment on comprehending the web documents which are extracted from japanese web sites. From the experimental results, we acquired a conclusion that two approaches are needed to enhance the ability of comprehending Japanese web documents which is newly added to the 7th curriculum revision. For short-term approach, we need to utilize Japanese web documents as learning materials. For long-term approach, we have to reconsider whether the orthography of the current Japanese textbooks is suitable or not.