Education is one of the priority sectors specified in Tanzania, and it has committed to provide 11 years of compulsory free basic education for all from pre-primary to lower secondary level. Despite the Government's efforts to provide free basic education to all children, there are 2.0 million (23.2 per cent) out of 8.5 million children at the primary school age of 7-13, who are out of school in Tanzania. The ICT class should be offered as a regular class in all secondary schools in Tanzania, recommended by the ministry of education. However, many schools are struggling to implement this mandate. Most of schools offer the ICT class with theory without any real hardware. Some schools were given with computers but they were not maintained for operation. There is a huge task to make ICT education universal. Main issues include: remoteness (off-grid area), lack of ICT teachers, lack of resources such as hardware, infrastructure, and lack of practical lessons or projects to be used at schools. An innovative blended ICT/STEM education program is being conducted not only for Tanzanian public and private/international schools, but also for out-of-school adolescents through institutions, NGO centers, home visits and at the E3 Empower academy center. For effective STEM education to take place and remain sustainable, more practical curriculum, and close-up teacher support need to be accompanied concurrently. Practical, project-based simple coding lessons have been developed and employed that students experience true learning. The effectiveness of the curriculum has been demonstrated in various project centers, and it showed that students are showing new interests in exploring new discovery, even though this was a totally new area for them. It has been designed for an easy replication, thus students who learned can repeat the lessons themselves to other students. The ultimate purpose of this project is to have IT education offered as universally as possible throughout the whole Tanzania. Quality education for all children is a key for better future for all. Previously it was hoped that education with discipline will improve the active learning. But now more than ever, we believe that children have the ability to learn on their own with given proper STEM education tools, guidelines and environment. This gives promising hope to all of us, including those in the developing countries.
Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.
Journal of Agricultural Extension & Community Development
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v.13
no.1
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pp.149-171
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2006
This is a pilot study on rural women's psychological trap to define some obstacles to self directed learning. During few decades, according to major crop of each farm household has shifted from rice to other crops like as vegetables, fruits, horticultures, livestock, etc., women's role or labor sharing of women in farming has been also increased. Although women are important human resources, till now, there is no a research or an approach to rural woman on the view of individual human being. Therefore this study will contribute to understand woman's behavior or attitudes based on psychological description at each person's experiences. For this study, the data was collected from 23 women leaders who participated in a training course in 2005, through the scale of Jeffrey E. Young & Janet S. Klosko which was developed to improvement of one's repetitious behavior based on cognitive psychological care. It was categorized into 11types of psychological trap of one person, named as follows; (1) trap of being deserted by someone (2) trap of disbelief and being ill-treated (3) trap of weakness (4) trap of dependence (5) trap of emotional deprivation (6) trap of feelings of alienation among society (7) trap of deficiency (8) trap of anxiety to failure (9) trap of subordination (10) trap of the merciless standard by self-estimation (11) trap of the sense of privilege. From the data, the average age of subjects was 52.8years old, and the educational back of subjects was higher than general rural women. In both of the trap of weakness and the trap of the merciless standard by self-estimation, the ratio of over and 4 point score of 6 points was 71.4% and 76.2%. It means most of subjects have experienced fear of unexpected calamity(trap of weakness), and mental press hard for efforts to meet one's ideal standard(trap of the merciless standard by self-estimation). Especially the trap of the merciless standard by self-estimation may have relation with rural women's over burden from farming and local society activities.
Social bookmarking systems are a typical web 2.0 service based on folksonomy, providing the platform for storing and sharing bookmarking information. Spammers in social bookmarking systems denote the users who abuse the system for their own interests in an improper way. They can make the entire resources in social bookmarking systems useless by posting lots of wrong information. Hence, it is important to detect spammers as early as possible and protect social bookmarking systems from their attack. In this paper, we applied a diverse set of machine learning approaches, i.e., decision tables, decision trees (ID3), $na{\ddot{i}}ve$ Bayes classifiers, TAN (tree-augment $na{\ddot{i}}ve$ Bayes) classifiers, and artificial neural networks to this task. In our experiments, $na{\ddot{i}}ve$ Bayes classifiers performed significantly better than other methods with respect to the AUC (area under the ROC curve) score as veil as the model building time. Plausible explanations for this result are as follows. First, $na{\ddot{i}}ve$> Bayes classifiers art known to usually perform better than decision trees in terms of the AUC score. Second, the spammer detection problem in our experiments is likely to be linearly separable.
This study presents the process and outcomes of developing mathematical-informatics linkage·convergence class materials, based on previous research findings that indicate a lack of such materials in high schools despite the increasing need for development of interdisciplinary linkage·convergence class materials In particular, this research provides insights into the discussions of six teachers who participated in the same professional learning community program, aiming to create materials that are suitable for linkage·convergence class materials and highly practical for classroom implementation. Following the material development process, a theme-based design model was applied to create the materials. In alignment with prior research and consensus among teacher learning community members, mathematics and informatics teachers developed instructional materials that can be utilized together during a 100-minute block lesson. The developed materials utilize societal issue contexts to establish links between the two subjects, enabling students to engage in problem-solving through mathematical modeling and coding. To increase the validity and practicality of the developed resources during their field application, CVR verification was conducted involving field teachers. Incorporating the results of the CVR verification, the finalized instructional materials were presented in the form of a teaching guide. Furthermore, we aimed to provide insights into the trial-and-error experiences and deliberations of the developers throughout the material development process, with the intention of offering valuable information that can serve as a foundation for conducting related research by field researchers. These research findings hold value as empirical evidence that can explore the applicability of teaching material development models in fields. The accumulation of such materials is expected to facilitate a cyclical relationship between theoretical teaching models and practical classroom applications.
As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.
Eunji Jo;Woojin Kim;Kwangyeom Kim;Jaeho Jung;Sanghyuk Bang
Tunnel and Underground Space
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v.33
no.4
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pp.209-227
/
2023
The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.
Journal of The Korean Association For Science Education
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v.38
no.4
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pp.467-480
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2018
This study aims to investigate how flipped learning-based socioscientific issue instruction (FL-SSI instruction) affected middle school students' key competencies and character development. Traditional classrooms are constrained in terms of time and resources for exploring the issues and making decision on SSI. To address these concerns, we designed and implemented an SSI instruction adopting flipped learning. Seventy-three 8th graders participated in an SSI program on four topics for over 12 class periods. Two questionnaires were used as a main data source to measure students' key competencies and character development before and after the SSI instruction. In addition, student responses and shared experience from focus group interviews after the instruction were collected and analyzed. The results indicate that the students significantly improved their key competencies and experienced character development after the SSI instruction. The students presented statistically significant improvement in the key competencies (i.e., collaboration, information and technology, critical thinking and problem-solving, and communication skills) and in two out of three factors in character and values as global citizens (social and moral compassion, and socio-scientific accountability). Interview data supports the quantitative results indicating that SSI instruction with a flipped learning strategy provided students in-depth and rich learning opportunities. The students responded that watching web-based videos prior to class enabled them to deeply understand the issue and actively engage in discussion and debate once class began. Furthermore, the resulting gains in available class time deriving from a flipped learning approach allowed the students to examine the issue from diverse perspectives.
Park, Byung-Yeol;Jeon, Jaedon;Lee, Hyundong;Lee, Hyonyong
Journal of The Korean Association For Science Education
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v.40
no.3
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pp.237-251
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2020
Issues on climate change we are facing, such as global warming, are very important as it affects our lives directly. To overcome this, efforts to reduce greenhouse gases emissions (e.g., carbon dioxide) are necessary and these efforts should be based on our integrated understanding of carbon cycle. The purpose of this study is to examine the research trend on carbon cycle education and to suggest the value and direction of carbon cycle education for students who will be citizens of the future. We analyzed 52 carbon cycle education related studies collected from academic research databases (RISS, KCI, ERIC, Google Scholar, and others). As a result, we conclude that resources are still limited and more researches on verification and utilization of developed program, development of accurate and comprehensive tools for students' recognition and level assessment, developing educational model or teacher professional development, providing more appropriate curriculum resources, and the use of various topics or materials for carbon cycle education are necessary. Students' comprehensive understanding of the carbon cycle is important to actively react to the changes in the global environment. Therefore, to support such learning opportunities, resources that can be connected to students' daily experiences to improve students' understanding of carbon cycle and replace misconceptions based on the verification of existing programs should be provided in the classroom as well as the curriculum. In addition, sufficient exemplary cases in carbon cycle education including various materials and topics should be provided through professional development to support teachers teaching strategies with carbon cycle.
The currently existing "Bonchojeonghwa (本草精華)" is a manuscript without the preface and the epilogue, composed of 2 books in 2 volumes. This book is a quintessence of knowledge on science of medicinal ingredients (medicinal phytology I herbal science) as well as an trial of new development in Chosun medical science. I.e. this book includes surprising change representing medical science in Chosun dynasty as a single publication on science of medicinal ingredients. It holds a value essential to clinician as a specialized book in medicinal ingredients, and Includes richer content on medicinal ingredients than any other books published before. In addition, it is away from boring list-up of superfluous knowledge as seen in "Bonchokangmok(本草綱目)" published in China, and well summarizes essential knowledge which can be used within a range of medicines available in Korea. This book has an outstanding structure that can be even used in today's textbook on science of medicinal ingredients, as it has clear theory, system and classification. Because it handles essential learning points prior to prescription to disease, it is possible to configure new prescription and adjustment of medicinal materials. Moreover, this book can play a good role for linguistic study at the time of publication, because it describes many drugs in Hangul in many parts of the book. "Bonchojeonghwa" includes a variety of animals, plants and mineral resources in Korea, like "Bonchokangmok" which was recently listed in UNESCO. As such, it has a significance in natural history as well as pharmacy in Korean Medicine. It has various academic relationships all in biologic & abiologic aspects. It has importance in sharing future biological resources, building up international potential, setting up the standard for biologic species under IMF system, and becoming a base for resource diplomacy. We should not only see it as a book on medicinal ingredients in terms of Oriental Medicine, but also make an prudent approach to it in terms of study strengthening Korea's national competitiveness. After bibliographical reviewing on the features & characteristics of the only existing copy of "Bonchojeonghwa" housed in Kyujanggak(奎章閣) of Seoul National University, the followings are noted. First, "Bonchojeonghwa" is a specialized book on medicinal ingredients voluntarily made by private hands to distribute knowledge on drugs in the desolate situation after Imjinoeran (Japanese Invasion in 1592), without waiting for governmental help. Second, it raised accessibility and practicality by new editing. Third, it classified 990 different kinds of drugs into plant, animal, and mineral at large, and dassified more in detail into 15 'Bu' and 48 'Ryu' at 258 pages. Fourth, the publication of this book is estimated to be around 1625~1633, at the time of Injo's reign in 17th century. Fifth, it contains the existing & up-to-date knowledge at the time of publication, and it is possible to see the supply-demand situation by Hangul descriptions in 149 places in the book. By the fact that there are many linguistic evidences of 17th century, explains well when the book was published.
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