• 제목/요약/키워드: Learning media

검색결과 1,571건 처리시간 0.023초

Review, Assessment, and Learning Lesson on How to Design a Spectroelectrochemical Experiment for the Molten Salt System

  • Killinger, Dimitris;Phongikaroon, Supathorn
    • 방사성폐기물학회지
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    • 제20권2호
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    • pp.209-229
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    • 2022
  • This work provided a review of three techniques-(1) spectrochemical, (2) electrochemical, and (3) spectroelectrochemical-for molten salt medias. A spectroelectrochemical system was designed by utilizing this information. Here, we designed a spectroelectrochemical cell (SEC) and calibrated temperature controllers, and performed initial tests to explore the system's capability limit. There were several issues and a redesign of the cell was accomplished. The modification of the design allowed us to assemble, align the system with the light sources, and successfully transferred the setup inside a controlled environment. A preliminary run was executed to obtain transmission and absorption background of NaCl-CaCl2 salt at 600℃. It shows that the quartz cuvette has high transmittance effects across all wavelengths and there were lower transmittance effects at the lower wavelength in the molten salt media. Despite a successful initial run, the quartz vessel was mated to the inner cavity of the SEC body. Moreover, there was shearing in the patch cord which resulted in damage to the fiber optic cable, deterioration of the SEC, corrosion in the connection of the cell body, and fiber optic damage. The next generation of the SEC should attach a high temperature fiber optic patch cords without introducing internal mechanical stress to the patch cord body. In addition, MACOR should be used as the cell body materials to prevent corrosion of the surface and avoid the mating issue and a use of an adapter from a manufacturer that combines the free beam to a fiber optic cable should be incorporated in the future design.

Exploring How Gamification Design Drives Customers' Co-Creation Behavior in Taiwan

  • CHEN, Tser-Yieth;HUANG, Yu-Chen;LI, Pei-Fang
    • The Journal of Asian Finance, Economics and Business
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    • 제9권4호
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    • pp.109-120
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    • 2022
  • This study has incorporated the mechanics-dynamics-emotions (MDE) and two behavioral learning paths to investigate the customers' co-creation behavior in Taiwan. The intuitive path begins with a gamification design that reflects the customers' proactive and innovative behavior; the cognitive path begins with persuasion knowledge remarks based on rational and reactive reasoning. These two paths conclude what forms user co-creation. The study collects data of 505 active social media users in Taiwan and employs structural equation modeling. The empirical findings demonstrate persuasive knowledge and gamification design are significantly associated with self-reference, and in turn, positively associated with co-creation. It indicates that cognitive behavior plays the main role in forming co-creation. Participants are more drawn to co-creation behaviors by the marketing contents that prompt reactive behaviors than proactive ones. Therefore, marketing managers can use appropriate stimuli to enhance co-creation behavior. Companies can design activities related to users, and more accessible for reactive, instead of proactive behavior, i.e., asking for their initiatives. It also suggests that companies' marketing campaigns should involve key opinion leaders matching the product image and the target audience's preferences. The novelty of this study is to introduce a novel augmented MDE framework to extend the "dynamics" into the incubation and implementation stage.

Framework for Reconstructing 2D Data Imported from Mobile Devices into 3D Models

  • Shin, WooSung;Min, JaeEun;Han, WooRi;Kim, YoungSeop
    • 반도체디스플레이기술학회지
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    • 제20권4호
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    • pp.6-9
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    • 2021
  • The 3D industry is drawing attention for its applications in various markets, including architecture, media, VR/AR, metaverse, imperial broadcast, and etc.. The current feature of the architecture we are introducing is to make 3D models more easily created and modified than conventional ones. Existing methods for generating 3D models mainly obtain values using specialized equipment such as RGB-D cameras and Lidar cameras, through which 3D models are constructed and used. This requires the purchase of equipment and allows the generated 3D model to be verified by the computer. However, our framework allows users to collect data in an easier and cheaper manner using cell phone cameras instead of specialized equipment, and uses 2D data to proceed with 3D modeling on the server and output it to cell phone application screens. This gives users a more accessible environment. In addition, in the 3D modeling process, object classification is attempted through deep learning without user intervention, and mesh and texture suitable for the object can be applied to obtain a lively 3D model. It also allows users to modify mesh and texture through requests, allowing them to obtain sophisticated 3D models.

Differentiation among stability regimes of alumina-water nanofluids using smart classifiers

  • Daryayehsalameh, Bahador;Ayari, Mohamed Arselene;Tounsi, Abdelouahed;Khandakar, Amith;Vaferi, Behzad
    • Advances in nano research
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    • 제12권5호
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    • pp.489-499
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    • 2022
  • Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

AR기술을 활용한 어린이 교육 어플리케이션 디자인 (Children's Education Application Design Using AR Technology)

  • 정혜경;고장혁
    • 반도체디스플레이기술학회지
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    • 제20권4호
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    • pp.23-28
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    • 2021
  • Augmented reality is a technique for combining virtual images into real life by showing information of virtual 3D objects on top of a real-world environment (Azuma et al., 2001). This study is an augmented reality-based educational content delivery device that receives user input that selects either a preset object or a photographed object for augmented reality-based training; It includes a three-dimensional design generation unit that generates a stereoscopic model of the augmented reality environment from an object, a three-dimensional view of the scene, a disassembly process of the developing road from a three-dimensional model, and a content control unit provided by the user terminal by generating educational content including a three-dimensional model, a scene chart, a scene, a decomposition process, and a coupling process to build a coupling process from the scene to the three-dimensional model in an augmented reality environment. The next study provides a variety of educational content so that children can use AR technology as well as shapes to improve learning effectiveness. We also believe that studies are needed to quantitatively measure the efficacy of which educational content is more effective when utilizing AR technology.

최근접 이웃 커널을 이용한 깊이 영상 완성 기술 (Depth Map Completion using Nearest Neighbor Kernel)

  • 정태현;우딘 쿠툽;오병태
    • 방송공학회논문지
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    • 제27권6호
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    • pp.906-913
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    • 2022
  • 본 논문에서는 희소 깊이 영상과 컬러 영상을 이용해 조밀한 깊이 영상을 추정하는 깊이 완성을 수행하기 위해 최근접 이웃 커널 기술을 사용하는 방식의 네트워크를 제안한다. 먼저 예측하고자 하는 깊이 영상을 대략적인 깊이 정보의 구조 정보를 포함하는 부분과 세밀한 깊이 정보를 가지는 상세 부분으로 분할하여 예측하는 방식을 제안한다. 이 과정에서 깊이 영상의 구조 및 상세 정보는 분류 기법과 회귀 기법을 활용하여 각각 추정하였으며, 특히 분류 과정에서 최근접 이웃 커널 정보를 활용하여 주변 정보를 통해 분류를 진행하는 방식을 제안하였다. 제안 방식은 기존의 희소 깊이 완성 방식과 비교하여 우수한 성능을 나타냈고, 시각적으로도 만족할만한 결과를 보이게 됨을 확인하였다.

Deep Learning Based Rumor Detection for Arabic Micro-Text

  • Alharbi, Shada;Alyoubi, Khaled;Alotaibi, Fahd
    • International Journal of Computer Science & Network Security
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    • 제21권11호
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    • pp.73-80
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    • 2021
  • Nowadays microblogs have become the most popular platforms to obtain and spread information. Twitter is one of the most used platforms to share everyday life event. However, rumors and misinformation on Arabic social media platforms has become pervasive which can create inestimable harm to society. Therefore, it is imperative to tackle and study this issue to distinguish the verified information from the unverified ones. There is an increasing interest in rumor detection on microblogs recently, however, it is mostly applied on English language while the work on Arabic language is still ongoing research topic and need more efforts. In this paper, we propose a combined Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) to detect rumors on Twitter dataset. Various experiments were conducted to choose the best hyper-parameters tuning to achieve the best results. Moreover, different neural network models are used to evaluate performance and compare results. Experiments show that the CNN-LSTM model achieved the best accuracy 0.95 and an F1-score of 0.94 which outperform the state-of-the-art methods.

A Study on Social Perceptions of Public Libraries Utilizing the sentiment analysis

  • Noh, Younghee;Kim, Dongseok
    • International Journal of Knowledge Content Development & Technology
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    • 제12권4호
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    • pp.41-65
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    • 2022
  • This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.

Effects of Nursing Skills Educational Programs Using Multimedia

  • Choi, Keum-Bong
    • International journal of advanced smart convergence
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    • 제11권2호
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    • pp.163-170
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    • 2022
  • Nursing students who play a role as future nursing professions are provided with education through various teaching and learning methods in order to develop necessary competencies. The purpose of this study is to confirm the effect of nursing practice education using multimedia. A quasi experimental study with a nonequivalent control group pretest-posttest design was used, and the participants of the study were students from two nursing colleges, who received an educational intervention using multimedia as the experimental group and those without education were selected as the control group. Data collection was conducted immediately before and after educational intervention, and data analysis was performed using the SPSS 21.0 program by x2-test, Fisher's exact probability, and t-test. As a result of the study, the experimental group was statistically significant in self-efficacy (t=3.402, p=0.015), resilience (t=2.047, p=0.045) and performance confidence (t=2.128, p=0.018) compared to the control group. Through these results, we could confirm that multi-media practical education is effective educational method for enhancing nursing students' self-efficacy, resilience, and performance confidence. Therefore, in order to establish a systematization of the nursing profession, it is essential and should be continued for nursing students to use structured multimedia and core fundamental nursing skills.

Featured Student Profiles: An Instructional Blogging Strategy to Promote Student Interactions in Online Courses

  • LIM, Taehyeong;DENNEN, Vanessa P.
    • Educational Technology International
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    • 제23권1호
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    • pp.67-96
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    • 2022
  • Although blogs have been used in online learning environments with optimistic expectations, the distributed nature of blogs can pose some challenges. Currently, we do not have a robust collection of tested blogging strategies to help students interact more effectively with each other when blogs are used as a primary form of engagement in an online class. Thus, the purpose of the study was to test an early iteration of an instructional blogging strategy, "Featured Student Profiles," which is designed to help students become acquainted with each other better and encourage them to visit and comment on each other's blogs. Sixteen pre-service teachers who were enrolled in an online course in which student blogs are the primary medium of peer interactions, participated in the study. Using a design case approach, seven students participated in interviews and all student blog interactions were analyzed. Thematic analysis was applied to analyze the interview data and identify salient themes of students' blogging experiences overall under the study strategy. The findings indicated that students took the most direct and efficient path they experienced to complete the blog task. Their peer interaction patterns varied, but several shifted from random to targeted relationships as the semester progressed. Although all students perceived the strategy as a positive approach to peer awareness, there was no clear evidence of its effect on student interactions.