• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.119-130
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• 2022

Crime is a common social problem that affects the quality of life. As the number of crimes increases, it is necessary to build a model to predict the number of crimes that may occur in a given period, identify the characteristics of a person who may commit a particular crime, and identify places where a particular crime may occur. Data privacy is the main challenge that organizations face when building this type of predictive models. Federated learning (FL) is a promising approach that overcomes data security and privacy challenges, as it enables organizations to build a machine learning model based on distributed datasets without sharing raw data or violating data privacy. In this paper, a federated long short- term memory (LSTM) model is proposed and compared with a traditional LSTM model. Proposed model is developed using TensorFlow Federated (TFF) and the Keras API to predict the number of crimes. The proposed model is applied on the Boston crime dataset. The proposed model's parameters are fine tuned to obtain minimum loss and maximum accuracy. The proposed federated LSTM model is compared with the traditional LSTM model and found that the federated LSTM model achieved lower loss, better accuracy, and higher training time than the traditional LSTM model.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.105-117
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• 2022

This study tested SVM(support vector machine), RF(random forest), and ANN(artificial neural network) machine-learning models that can predict net irrigation water requirements in paddy fields. For the Jeonju and Jeongeup meteorological stations, the net irrigation water requirement was calculated using K-HAS from 1981 to 2021 and set as the label. For each algorithm, twelve models were constructed based on cumulative precipitation, precipitation, crop evapotranspiration, and month. Compared to the CE model, the R² of the CEP model was higher, and MAE, RMSE, and MSE were lower. Comprehensively considering learning performance and learning time, it is judged that the RF algorithm has the best usability and predictive power of five-days is better than three-days. The results of this study are expected to provide the scientific information necessary for the decision-making of on-site water managers is expected to be possible through the connection with weather forecast data. In the future, if the actual amount of irrigation and supply are measured, it is necessary to develop a learning model that reflects this.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.31-42
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• 2024

Different industries mostly rely on quality certification for promoting their products or brands. Although getting quality certification, specifically by human experts is a tough job to do. But the field of machine learning play a vital role in every aspect of life, if we talk about quality certification, machine learning is having a lot of applications concerning, assigning and assessing quality certifications to different products on a macro level. Like other brands, wine is also having different brands. In order to ensure the quality of wine, machine learning plays an important role. In this research, we use two datasets that are publicly available on the "UC Irvine machine learning repository", for predicting the wine quality. Datasets that we have opted for our experimental research study were comprised of white wine and red wine datasets, there are 1599 records for red wine and 4898 records for white wine datasets. The research study was twofold. First, we have used a technique called backward elimination in order to find out the dependency of the dependent variable on the independent variable and predict the dependent variable, the technique is useful for predicting which independent variable has maximum probability for improving the wine quality. Second, we used a robust machine learning algorithm known as "XGBoost" for efficient prediction of wine quality. We evaluate our model on the basis of error measures, root mean square error, mean absolute error, R2 error and mean square error. We have compared the results generated by "XGBoost" with the other state-of-the-art machine learning techniques, experimental results have showed, "XGBoost" outperform as compared to other state of the art machine learning techniques.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.2
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• pp.202-211
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• 2021

The purpose of this study is to find out the Learning elements in 'Curriculum Reconstruction' of Elementary Pre-service Teachers in Connection with 'The weather and our daily life'. The pre-service teachers who participated in the study formed a research group of 29 students in 2nd grade who are attending the first semester of A university of education and taking courses in 'teaching research 1'. Participants described the learning topics and contents they would like to add to curriculum 'The weather and our daily life'. Each response was analyzed and classified based on scientific terms related to weather or climate. The results of the study were as follows. First, there were three learning topics related to weather, such as water phenomena in the atmosphere, fine dust and yellow dust phenomena, and light or electricity phenomena, and two topics related to climate such as abnormal climate and global warming. Second, interest in the problem of fine dust and yellow dust in the atmosphere was relatively high. Third, the interest in learning in the knowledge area was relatively higher than in the learning in the function or attitude area. Through these research results, it can be confirmed that it is necessary to develop a climate change or climate crisis education program.

• 한국약용작물학회:학술대회논문집
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• 2007.05a
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• pp.49-50
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• 2007

• Journal of the Korean Society of Earth Science Education
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• v.3 no.1
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• pp.65-75
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• 2010

The purpose of this study is to present a Freedom Inquiry Method by Revised Science Curriculum in 2007. This study introduced IIM(Independent Inquiry Method), PBL(Problem Based Learning), Small Inquiry Method, Science Notebooks, Project Learning Method about Freedom Inquiry Method. The results of this study are as follows: First, IIM(Independent Inquiry Method) is studying method in the inquiry process center. The inquiry process is composed of total 9 phases, inquiry subject really it is, detailed aim deciding, information searching, it searches, quest result it arranges, aim evaluation, the report making, it announces, it evaluates, it is become accomplished. Second, It is a studying method which it starts with the problem which is Problem Based Learning, study atmosphere creation phase, problematic presentation phase and sleep static problem solving the phase which it attempts, it is become accomplished with autonomous studying phase, coordinated studying and discussion studying phase, discussion resultant announcement studying phase, arrangement and evaluation. Third, Small Inquiry Method, Call it accomplishes the call grade of the students among ourselves 4~8 people degree where only the quest learning capability is similar within class. Also interaction and coordinated function of the members between it leads and the subject which is given in the group it cooperates and it solves with it is a quest method which arrives to aim of commonness. This method divides on a large scale in three parts, it becomes accomplished in programming phase, quest accomplishment and resultant announcement. Fourth, Science Notebooks learns a scientific contents and a scientific quest function and the possibility of decreasing in order to be, from the fact that the help which it understands. This planing, data searching, it searches, becomes accomplished with resultant arrangement, announcement and evaluation. Fifth, The Project Learning Method the studying person oneself studying contents, it establishes a plan and it collects it accomplishes process of etc. it evaluates it leads and a subject and information and with real life it is a method which it studies naturally from the learning environment inside which is similar. This is preliminary phase, project start, project activity and project arrangement.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.89-94
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• 2024

The main purpose of the study is to determine the main elements of the use of digital technologies for learning a foreign language in educational institutions. The era of digital technologies is a transition from the traditional format of working with information to a digital format. This is the era of the total domination of digital technologies. Digital technologies have gained an unprecedented rapid and general distribution. In recent years, all spheres of human life have already undergone the intervention of digital technologies. Therefore, it is precisely the educational industry that faces a difficult task - to move to a new level of education, where digital technologies will be actively used, allowing you to conveniently and quickly work in the information field for more effective learning and development. The study has limitations and they relate to the fact that the practical activities of the process of using digital technologies in the system of preparing the study of a foreign language were not taken into account.

• BMB Reports
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• v.42 no.1
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• pp.6-15
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• 2009

The most common genetic disorder Down syndrome (DS) displays various developmental defects including mental retardation, learning and memory deficit, the early onset of Alzheimer's disease (AD), congenital heart disease, and craniofacial abnormalities. Those characteristics result from the extra-genes located in the specific region called 'Down syndrome critical region (DSCR)' in human chromosome 21. In this review, we summarized the recent findings of the DYRK1A and RCAN1 genes, which are located on DSCR and thought to be closely associated with the typical features of DS patients, and their implication to the pathogenesis of neural defects in DS. DYRK1A phosphorylates several transcriptional factors, such as CREB and NFAT, endocytic complex proteins, and AD-linked gene products. Meanwhile, RCAN1 is an endogenous inhibitor of calcineurin A, and its unbalanced activity is thought to cause major neuronal and/or non-neuronal malfunction in DS and AD. Interestingly, they both contribute to the learning and memory deficit, altered synaptic plasticity, impaired cell cycle regulation, and AD-like neuropathology in DS. By understanding their biochemical, functional and physiological roles, we hope to get important molecular basis of DS pathology, which would consequently lead to the basis to develop the possible therapeutic tools for the neural defects in DS.

• Biomolecules & Therapeutics
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• v.15 no.2
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• pp.83-88
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• 2007

The roots of Liriope platyphylla (Liliaceae) are widely used in traditional Chinese medicine. In the present study, we investigated the effects of ethanol (70%) extract of the roots of Liriope platyphylla (ELP70) on learning and memory using behavioral and immunohistochemical methods in mice. Control animals were treated with vehicle (10% Tween 80). With sub-chronic treatments of ELP70 (p.o.) for 14 days, the latency time was significantly increased compared with that of the vehicle-treated control group (50, 100 and 200 mg/kg; P<0.05). Moreover, immunopositive cells for brain derived neurotrophic factor (BDNF) were significantly increased in the hippocapmpal dentate gyrus and CA1 regions after ELP70 treatments for 14 days (50, 100 and 200 mg/kg; P < 0.05). In addition, those cells for nerve growth factor (NGF) were also increased in the hippocapmpal dentate gyrus region (50, 100 and 200 mg/kg; P<0.05). These results suggest that the sub-chronic administration of ELP70 improves learning and memory, and that their beneficial effects are mediated, in part, by the enhancement of BDNF or NGF expression.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.24 no.1
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• pp.39-50
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• 2017

Purpose: The purpose of this study was to identify the effects simulation-based education combined team-based learning (SBE combined TBL) compared to simulation-based education (SBE) on undergraduate nursing students. Methods: A non-equivalent control group design with pre-and posttest measures was used. The participants in the study were 181 students. The SBE combined TBL group consisted of 84 senior students in 2013, and the SBE group consisted of 97 seniors in 2014. Collected data were analyzed using chi-square, independent t-test and ANCOVA with the statistical package SPSS 22.0 for Windows. Results: There was a significant improvement in communication skills, nursing performance confidence, team efficacy, and team performance scores in the SBE combined TBL group compared to the SBE group (t=2.45, p=.015; F=4.30, p=.040; t=3.06, p=.003; t=8.77, p<.001). However, there was no statistically significant difference in self-directed learning between the groups. Conclusion: SBE combined TBL compared to SBE is an effective teaching and learning method to enhance various positive educational outcomes for nursing students. Therefore, we suggest that future studies investigate the development of an integrated course in which team-based learning is applied to theoretical sessions and simulation-based training.