• 대한수학교육학회지:학교수학
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• 제1권1호
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• pp.123-133
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• 1999

For an appropriate assessment in mathematics, students should play an active role in their learning by becoming aware of what they have learned in mathematics and by being able to assess their attainment of mathematical knowledge. The process of actively examining and monitoring students' own progress in learning and understanding of their mathematical knowledge, process, and attitude is called self-assessment, Researchers in mathematics education have found some important facts about the meta-cognitive process which is related to self-assessment : i. e. meta-cognition progress is composed of being aware of ones' own personal thinking of content knowledge and cognitive process(self-awareness) and engagement in self-evaluation. Tipical method for self-assessment in mathematics developed upon above finding about meta-cognitive progress is describing about students' knowledge and their problem solving strategies. In the beginning of the description in mathematics about themselves, students are required to answer which part they know and which part they don't know. Self-assessment of students' attitudes and dispositions can be just as important as assessment of their specific mathematical abilities. To make the self-assessment method a success, teachers should let students' have confidence and earn their cooperation by let them overcoming fear to be known the their ability to other students. In conclusion, self-assessment encourages students to assume an active role in development of mathematical power. For teachers, student self-assessment activities can provide a prism through which the development of students' mathematical power can be viewed.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.65-74
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• 2021

The rapid change in gold price is an issue of concern in the global economy and financial markets. Gold has been used as a means for trading and transaction around the world for long period of time and it plays an integral role in monetary, business, commercial and financial activities. More importantly, it is used as economic measure for the global economy and will continue to play an important economic vital role - both locally and globally. There has been an explosive growth in demand for efficient and effective scheme to predict gold price due its volatility and fluctuation. Hence, there is need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper primarily proposed an intelligent based system for predicting and characterizing the gold market trend. The simulation result shows that the proposed intelligent gold price scheme has been able to predict the gold price with high accuracy and precision, and ultimately it has significantly reduced the prediction error when compared to baseline neural network (NN).

• 한국수학교육학회지시리즈A:수학교육
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• 제41권3호
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• pp.329-339
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• 2002

This study analyzes the epistemological meaning of‘social construction’in mathematical instruction. The perspective that consider the cognition of mathematical concept as a social construction is explained by a cyclic scheme of an academic context and a school context. Both of the contexts require a public procedure, social conversation. However, there is a considerable difference that in the academic context it is Lakatos' ‘logic of mathematical discovery’In the school context, it is Vygotsky's‘instructional and learning interaction’. In the situation of mathematics education, the‘society’which has an influence on learner's cognition does not only mean‘collective members’, but‘form of life’which is constituted by the activity with purposes, language, discourse, etc. Teachers have to play a central role that guide and coordinate the educational process involving interactions with learners in this context. We can get useful suggestions to mathematics education through this consideration of the social contexts and levels to form didactical situations of mathematics.

• International Journal of Industrial Entomology and Biomaterials
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• 제38권1호
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• pp.1-5
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• 2019

Bee's population is declining and disappearing at alarming rate. There are many factors responsible for declining the population of bees including diseases, natural enemies, environmental conditions and pesticides. Insecticides play its role dramatically for their population decline and neonicotinoid insecticides are critically important due to their wide application for pest control. Keeping in view of above problem, effect of neonicotinoid insecticides on olfactory learning behavior in Apis mellifera was observed using Proboscis Extension Reflex (PER) method. In this method, bees were harnessed in centrifuges tubes and feed on insecticides mixed sugar solution after three hours hunger. Bees were checked by feeding on non-treated sugar solution to observe PER response. Minimum proboscis extension was observed for acetamiprid and imidacloprid with 26% and 20% respectively at their recommend field doses while it was maximum for dinotefuran and thiamethoxam with 73% and 60% respectively. Only 40% bees showed response when exposed at 1/10 concentration of field dose for imidacloprid and the least at 1/100 of field dose. At control (Sugar solution) about 90% bees showed PER response. Among these neonicotinoid insecticides tested, imidacloprid and acetamiprid were the most damaging which impaired the olfactory learning performance in Apis mellifera.

• Asia pacific journal of information systems
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• 제33권2호
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• pp.282-297
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• 2023

One of the emerging trends in the marketing field is digital video marketing. Online videos offer rich content typically containing more information than any other type of content (e.g., audible or textual content). Accordingly, previous researchers have examined factors influencing videos' popularity. However, few studies have examined what causes a video to remain popular. Some videos achieve continuous, ongoing popularity, while others fade out quickly. For practitioners, videos at the recommendation slots may serve as strong communication channels, as many potential consumers are exposed to such videos. So,this study will provide practitioners important advice regarding how to choose videos that will survive as long-lasting favorites, allowing them to advertise in a cost-effective manner. Using deep learning techniques, this study extracts text from videos and measured the videos' tones, including factual and emotional tones. Additionally, we measure the aesthetic score by analyzing the thumbnail images in the data. We then empirically show that the cognitive features of a video, such as the tone of a message and the aesthetic assessment of a thumbnail image, play an important role in determining videos' long-term popularity. We believe that this is the first study of its kind to examine new factors that aid in ensuring a video remains popular using both deep learning and econometric methodologies.

• 한국초등과학교육학회지:초등과학교육
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• 제19권1호
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• pp.85-99
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• 2000

Researches have shown that learning science frequently requires the process of conceptual change. As a result, many of the constructivist teaching and loaming approaches focus on this kind of loaming. In approaches that focus on conceptual change, cognitive conflict strategies play a key role. Students, however, still have much difficulty in loaming science. Theoretically, it underlies Piaget's genetic epistemology in which disequilibration demands an interplay between assimilation and accommodation until equilibrium is restored. Also, radical constructivism has its roots in a variety of disciplines, but has been most profoundly influenced by the theories of lean Piaget as interpreted and extended by Glasersfeld. This study is intended to interpret the conceptual change from radical constructivist perspective and explain difficulties of conceptual change which students have in learning science.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.51-73
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• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

• 한국융합학회논문지
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• 제12권11호
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• pp.467-473
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• 2021

본 연구는 플립러닝을 적용한 건강사정수업이 간호대학생의 자기주도 학습능력, 비판적 사고성향, 학업적 자기효능감에 미치는 효과를 확인하기 위한 연구이다. 경상북도 K시 일개 간호대학에서 플립러닝을 적용하여 건강사정을 수강하는 2학년 학생을 대상으로 하였으며, 단일군 전후 비교 연구이다. 최종분석은 104명을 대상으로 하였고, 사전 사후 차이는 대응표본검정으로 분석하였다. 그 결과 자기주도 학습능력(t=-3.23, p<.01), 비판적 사고성향(t=6.381, p<.001), 학업적 자기효능감(t=-4.62, p<.001) 모두 통계적으로 유의하게 증가하였다. 이 연구결과를 바탕으로 플립러닝 학습법이 간호대학생의 자기주도 학습능력, 비판적 사고능력, 학업적 자기효능감을 증진시키는 효과적인 프로그램임이 확인되었다. 플립러닝 학습범의 적용은 장기적으로는 교육환경을 개선하고 학생들의 능력을 강화시키는 역할을 할 것이다.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.426-432
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• 2022

HVAC systems play a critical role in reducing energy consumption in buildings. Integrating occupants' thermal comfort evaluation into HVAC control strategies is believed to reduce building energy consumption while minimizing their thermal discomfort. Advanced technologies, such as visual sensors and deep learning, enable the recognition of occupants' discomfort-related actions, thus making it possible to estimate their thermal discomfort. Unfortunately, it remains unclear how accurate a deep learning-based classifier is to recognize occupants' discomfort-related actions in a working environment. Therefore, this research evaluates the classification performance of occupants' discomfort-related actions while sitting at a computer desk. To achieve this objective, this study collected RGB video data on nine college students' cold discomfort-related actions and then trained a deep learning-based classifier using the collected data. The classification results are threefold. First, the trained classifier has an average accuracy of 93.9% for classifying six cold discomfort-related actions. Second, each discomfort-related action is recognized with more than 85% accuracy. Third, classification errors are mostly observed among similar discomfort-related actions. These results indicate that using human action data will enable facility managers to estimate occupants' thermal discomfort and, in turn, adjust the operational settings of HVAC systems to improve the energy efficiency of buildings in conjunction with their thermal comfort levels.

• International Journal of Internet, Broadcasting and Communication
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• 제14권1호
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• pp.44-52
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• 2022

With recent scientific advances and growing interest in AI technologies, AI-based chatbots have been viewed as a practical learning aid for English language development. The purpose of this study is to examine preservice teachers' perceptions on the potential benefits of employing AI chatbots in English instruction and its pedagogical aspects. 28 preservice teachers majoring in English education were asked to use Kuki chatbots for a week with a guidance of a researcher and then report on their perceptions of AI chatbots in terms of perceived usefulness after use, applicability, and educational benefits and drawbacks. Emerging codes and themes were identified and evaluated using Thematic Analysis(TA) based on qualitative data from surveys and interviews. The findings show that six emerging themes were identified, encompassing perspectives on teacher, learner, communication, linguistic, affective, and assessment. The overall findings of this study revealed that AI-based chatbots can play a significant role as learning tools for stimulating interactive communication in a target language. Most preservice primary teachers acknowledge that AI chatbots can be useful as teaching and learning aids for both teachers and students. Furthermore, when applying various learner data to chatbot technology, such as learner assessment and diagnosis, a guided approach is necessary to perform a conversation appropriate for the learner's level and characteristics. Finally, as chatbots have a variety of benefits in terms of affective aspects, they may improve EFL learners' confidence in speaking English and learning motivation.