Application Of Learning Methods Research Articles

The Application of Blending Learning Method in Teaching Chinese as a Foreign Language

The Application of Blending Learning Method in Teaching Chinese as a Foreign Language

A Survey on 3D Skeleton-Based Action Recognition Using Learning Method.

Three-dimensional skeleton-based action recognition (3D SAR) has gained important attention within the computer vision community, owing to the inherent advantages offered by skeleton data. As a result, a plethora of impressive works, including those based on conventional handcrafted features and learned feature extraction methods, have been conducted over the years. However, prior surveys on action recognition have primarily focused on video or red-green-blue (RGB) data-dominated approaches, with limited coverage of reviews related to skeleton data. Furthermore, despite the extensive application of deep learning methods in this field, there has been a notable absence of research that provides an introductory or comprehensive review from the perspective of deep learning architectures. To address these limitations, this survey first underscores the importance of action recognition and emphasizes the significance of 3-dimensional (3D) skeleton data as a valuable modality. Subsequently, we provide a comprehensive introduction to mainstream action recognition techniques based on 4 fundamental deep architectures, i.e., recurrent neural networks, convolutional neural networks, graph convolutional network, and Transformers. All methods with the corresponding architectures are then presented in a data-driven manner with detailed discussion. Finally, we offer insights into the current largest 3D skeleton dataset, NTU-RGB+D, and its new edition, NTU-RGB+D 120, along with an overview of several top-performing algorithms on these datasets. To the best of our knowledge, this research represents the first comprehensive discussion of deep learning-based action recognition using 3D skeleton data.

Robust Vascular Segmentation for Raw Complex Images of Laser Speckle Contrast Based on Weakly Supervised Learning.

Laser speckle contrast imaging (LSCI) is widely used for in vivo real-time detection and analysis of local blood flow microcirculation due to its non-invasive ability and excellent spatial and temporal resolution. However, vascular segmentation of LSCI images still faces a lot of difficulties due to numerous specific noises caused by the complexity of blood microcirculation's structure and irregular vascular aberrations in diseased regions. In addition, the difficulties of LSCI image data annotation have hindered the application of deep learning methods based on supervised learning in the field of LSCI image vascular segmentation. To tackle these difficulties, we propose a robust weakly supervised learning method, which selects the threshold combinations and processing flows instead of labor-intensive annotation work to construct the ground truth of the dataset, and design a deep neural network, FURNet, based on UNet++ and ResNeXt. The model obtained from training achieves high-quality vascular segmentation and captures multi-scene vascular features on both constructed and unknown datasets with good generalization. Furthermore, we intravital verified the availability of this method on a tumor before and after embolization treatment. This work provides a new approach for realizing LSCI vascular segmentation and also makes a new application-level advance in the field of artificial intelligence-assisted disease diagnosis.

Application of Deep Learning Methods in Prediction of Anticancer Drug Susceptibility

Application of Deep Learning Methods in Prediction of Anticancer Drug Susceptibility

Classification of coronary artery disease severity based on SPECT MPI polarmap images and deep learning: A study on multi-vessel disease prediction

Background Coronary artery disease (CAD) is a global health concern. Conventional single photon emission computed tomography myocardial perfusion imaging (SPECT MPI) is a noninvasive method for assessing the severity of CAD. However, it relies on manual classification by clinicians, which can lead to visual fatigue and potential errors. Deep learning techniques have displayed promising results in CAD diagnosis and prediction, providing efficient and accurate analysis of medical images. Methods In this study, we explore the application of deep learning methods for assessing the severity of CAD and identifying cases of multivessel disease (MVD). We utilized the EfficientNet-V2 model in combination with DeepSMOTE to evaluate CAD severity using SPECT MPI images. Results Utilizing a dataset consisting of 254 patients (176 with MVD and 78 with single-vessel disease [SVD]), our model achieved an accuracy rate of 84.31% and area under the receiver operating characteristic curve (AUC) value of 0.8714 in predicting cases of MVD. These results underline the promising potential of our approach in MVD prediction, offering valuable diagnostic insights and the prospect of reducing medical costs. Conclusion This study emphasizes the feasibility of employing deep learning techniques for predicting MVD based on SPECT MPI images. The integration of Efficient-Net-V2 and DeepSMOTE methods effectively evaluates CAD severity and distinguishes MVD from SVD. Our research presents a practical approach to the early prediction and diagnosis of MVD, ultimately leading to enhanced patient outcomes and reduced healthcare costs.

Применение методов машинного обучения к построению прогнозных моделей продуктивности многолетних трав при орошении

Purpose: to test the hypothesis on possibility of perennial grasses yield forecast model building using machine learning methods. For agricultural production planning, the yield forecasting is one of the important tasks, and when using information technologies, building forecast models requires significantly less labor while maintaining or even increasing the accuracy and adequacy of the models. Materials and methods. Such methods of scientific knowledge as analysis and synthesis of various levels, methods of data preparation for machine learning, machine learning methods implementing a linear regression model and regression using decision trees were used. The popular Python language and publicly available libraries for data analysis and preparation and building machine learning models were used as the main technology stack for implementing machine learning methods. Results. The data was prepared for training the model using machine learning methods, and the data was modified without loss in such a way that it represents exclusively numerical values. Linear regression and regression models using decision trees were trained. A metric of model quality confirmed by high values of determination coefficients (0.68 and 0.98, respectively) was calculated, using standard tools from the libraries used. Conclusions: numerical values of input of such characteristics as food regime (0.176935–0.315269), as well as the ratio of the number of irrigations and irrigation norms (0.056576–0.108139), into the model, confirm their significance for the conditions of research areas and database collection.

Metode Pembelajaran Guru Aqidah Akhlak

This study intends to find out the actual nature of the Aqidah Akhlak learning technique, find the issues associated with applying learning methods in Aqidah Akhlak subjects, and find solutions to these issues. An observation-based qualitative method of data collecting was employed in the development of this study. The results of the analysis show that the reality of the teacher uses the learning method from the learning method carried out by Dra. Wiwi Marwiyah, M.Pd.I in the subject of Aqidah Akhlak with hypocrisy and ghadab material is to use lecture, question and answer and discussion methods. In the learning process, the teacher comes in and starts it in a timely, informative, and interactive manner. As for the problems with using the learning method, there are still students chatting when the teacher explains using the lecture method, and the teacher has not succeeded in getting students to appear in front of them to re-present the material that has been delivered. Thus, hypocritical and ghadab material is not compatible with the lecture method, so CTL (contextual teaching and learning) and PBL (problem-based learning) methods must be used.

Construction and Application of Complex Student-Centered Teaching and Learning Method in a University General Chemistry Course

In this study, we constructed and applied a complex student-centered teaching and learning method (CSCTL) that can be used in a university general chemistry course, and analyzed students' satisfaction and perceptions of it. Specifically, we aimed to construct a CSCTL that enables students to actively understand chemical concepts and phenomena, recognize the importance of quantitative thinking, take an active stance to acquire concepts and knowledge, and cultivate attitudes such as thinking for themselves, expressing their opinions, listening to their peers' opinions, and persuading their peers. Based on the theoretical considerations, we designed and applied a CSCTL, including ConcepTests, quantitative problem-solving, and peer discussion to general chemistry classes, and conducted two surveys to analyze students' satisfaction and perception. The results were analyzed in combination with the students' opinions on essay questions in a course evaluation. The results showed that, first, the CSCTL induced students' learning motivation, increased their concentration and understanding of the learning content, led to longer retention of scientific knowledge, and increased their satisfaction with learning efficiency comparing with the conventional lecture-centered teaching method. Second, the CSCTL provided students with opportunities to construct knowledge and to think logically, stimulating them to think more deeply, consider conflicting viewpoints, and continuously consider their chemistry knowledge. Third, the CSCTL provided opportunities for interactive communication, allowing members to communicate with each other and share knowledge. Fourth, despite the above positive results, we found that the students felt academic pressure in the class. The results of this study are significant in that we are suggesting the CSCTL that can be applied to a university general chemistry course, which is part of a general education in university.

Using Artificial Intelligence in the Security of Cyber Physical Systems

The prominence of cyber security continues to increase on a daily basis. Following the cyber attacks in recent years, governments have implemented a range of regulations. The advancement of technology and digitalization has led to the creation of new vulnerabilities that cyber attackers can exploit. The digitalization of facilities such as energy distribution networks and water infrastructures has enhanced their efficiency, thereby benefiting states and society. The modern sensors, controllers, and networks of these new generation facilities have made them susceptible to cyber attackers. While all forms of cyber attacks are detrimental, targeting critical cyber-physical systems presents a heightened level of peril. These assaults have the potential to disrupt the social structure and pose a threat to human lives. Various techniques are employed to guarantee the security of these facilities, which is of utmost importance. This study examined the applications of machine learning and deep learning methods, which are sub-branches of artificial intelligence that have recently undergone a period of significant advancement. Intrusion detection systems are being created for the networks that facilitate communication among the hardware components of the cyber-physical system. Another potential application area involves the development of models capable of detecting anomalies and attacks in the data generated by sensors and controllers. Cyber physical systems exhibit a wide range of diversity. Due to the wide range of variations, it is necessary to utilize specific datasets for training the model. Generating a dataset through attacks on a functional cyber-physical system is unattainable. The study also analyzed the solutions to this problem. Based on the analyzed studies, it has been observed that the utilization of artificial intelligence enhances the security of cyber physical systems.

Supervisi Penerapan Metode Ummi dalam Meningkatkan Kemampuan Membaca dan Menghafal Al-Qurân

Implementing a learning method requires guidance and supervision. In many cases, teachers are often required to implement a new method without any guidance and supervision. There is one application of learning methods that provides guidance and supervision, namely the application of the Ummi learning method in improving the ability to read and memorize the Al-Qur'an. This is worth studying. For this reason, this research is aimed at revealing how to implement supervision activities by focusing on three things, namely: steps, techniques and factors inhibiting and supporting these supervision activities. The research was carried out in two locations: SMPN 1 Sampang and SDN 1 Dalpenang Sampang. This research uses a qualitative approach with data collection techniques: non-participant observation, in-depth interviews, and documentation of related sources. The research results obtained are first, the stages of implementing supervision in both institutions include daily, weekly and monthly supervision. Second, the technique for implementing Ummi method supervision in both institutions is in the form of individual and group techniques. Individual supervision techniques include class visits, individual meetings and document observation, while group techniques include school visits, evaluation meetings and teaching demonstrations. Third, the supporting factors for implementing the Ummi method of supervision in both institutions are support from school principals and parents who encourage supervisors to continue to supervise, supervisors' activeness and teacher welfare as well as adequate facilities. The inhibiting factors are the lack of supervision time and the lack of supervisors which is not commensurate with the number of existing groups. The results of the research have implications for supervisors being able to emphasize the objectives of supervision, so that supervision activities are not understood as a form of supervision but as mentoring and guidance activities.

Application of Project-based Learning Method in High School Language Teaching—The Teaching of “Xiang Ji Xuan Zhi” as an Example

Application of Project-based Learning Method in High School Language Teaching—The Teaching of “Xiang Ji Xuan Zhi” as an Example

Peningkatan Hasil Belajar IPS Siswa Kelas V SDN 164 Pacora Kabupaten Soppeng Melalui Metode Thingking Aloud Pair Problem Solving (TAPPS)

This study aims to improve student learning outcomes through the Thinking Aloud Pair Problem Solving method in class V SDN 164 Pcora Kabupaten Soppeng. . This research is classroom action research which is carried out in two cycles and through several stages, namely, planning, implementing actions, observing and reflecting. Data was collected using observation sheets, tests and documentation. The data collected were analyzed descriptively and quantitatively. The results showed that student learning outcomes in following the teaching and learning process through the application of the Thinking Aloud Pair Problem Solving learning method could improve social studies learning outcomes for grade VII students of SDN 164 Pacora Kabupaten Soppeng, which can be seen from the completeness of student learning outcomes from 64% completed with a score of 64%. an average of 66.8 in the first cycle increased to 88% completed with an average value of 82 in the second cycle

Analisis Implementasi Metode Pembelajaran Field Trip Terhadap Hasil Belajar Siswa Sekolah Dasar

Learning can be obtained by students not only within the school environment, but outside the school environment students can explore knowledge related to the material in the classroom through the field trip learning method. This study aims to determine the application of field trip learning methods to the learning outcomes of students in Elementary School (SD). This research uses a type of qualitative descriptive research with literature studies from relevant research. Data is obtained from various sources including published articles, books, and other relevant literature. The results of this research show that the field trip learning method is a learning method that can direct students to study somewhere directly according to the material they are studying. The field trip learning method can have a positive impact on student learning outcomes. So it can be concluded that in learning teachers can use a variety of learning methods that are adapted to the material, one of which is using the field trip method with their students

The implementation Project-Based Learning in lower secondary school: a critical review

The learning that is widely recommended to improve science skills is project-based learning. Several studies show that the application of project-based learning models or methods or learning strategies increases motivation, achievement, problem-solving abilities, and so on. However, in reality, in the field, teachers have difficulty adopting project-based learning in schools, because several supporting factors are inadequate. Supporting factors for the success of project-based learning include a comprehensive curriculum, learning environment, appropriate assessment, student self-efficacy and support from stakeholders, especially parents. This critical review study reviews how research on project-based learning produces learning outcomes according to Project-based learning standards. In the initial stage, the author looked for as many articles as possible regarding project-based learning, especially in the science field, provided the articles were reputable. Then, reputable articles are selected that are appropriate to the implementation of project-based learning. The results of the critical review study show three important points in implementing Project-based learning to be more successful, namely: comprehensive curriculum support; the approach widely used in Project-based learning is STEM; and the implementation of Project-based learning must be adapted to suit the characteristics of students.

FORMATION OF EMOTIONAL INTELLIGENCE IN THE PROCESS OF PREPARATION OF FUTURE SOCIAL PROFESSIONALS IN HIGHER EDUCATION INSTITUTIONS

Abstract: the article emphasizes the importance of the role of education as one of the main components of supporting the transition period of Ukraine on the way to the EU and NATO; it has been proven that the formation of a new philosophy of higher education is simultaneously connected with emotional intelligence, which is of great importance in the training of future specialists in the social sphere in institutions of higher education. It was determined that the state and development of the modern Ukrainian economy depends on the quality of personnel training provided by universities. It was found that the lack of management culture, the insufficient level of moral and ethical training of specialists in the social sphere and qualified specialists in the field of professional ethics is an obstacle to the creation of an emotional and ethical infrastructure in Ukraine. The opinion is substantiated that the wide application of active learning methods with the analysis of real and educational business situations and the regular professional practice of future specialists in the social sphere at enterprises, firms, state authorities and local governments will ensure the effectiveness of the training of specialists in the social sphere, will contribute to the formation and development of ethical norms and emotional intelligence.

Peer Teaching for Early Reading of Elementary School Students: Classroom Implementation and Challenges

The purpose of this study was to analyze and describe the application of the peer teaching learning method to students' beginning reading skills. The research method used is qualitative research with exploratory descriptive design. Sources of data in this study were students and teachers in first grade of elementary school who had implemented the peer teaching learning method. Data collection techniques using documentation, interviews, and observation. Data analysis techniques used are data reduction, data display, and data verification. Test the validity of the data using technical triangulation. The results showed that the inclusion of students' initial reading skill aspects included being able to pronounce letters very fluently with no errors, being able to compose letters into words fluently even though there were a few structuring errors, understanding the meaning of words that were read quite fluently because there were several deficiencies in understanding the meaning of words, showing appropriate reading behavior quite fluently, there was activity of repeating words in reading even though not many words were repeated, and activities in decapitation were not quite right there were few errors, so that overall the coverage of reading skills through the peer teaching method analyzed was as large as fulfilling If the criterion is sufficient, in the future it is hoped that there will be a review related to the implementation of learning plans through the peer teaching method so that learning activities that refer to the development of students' reading abilities are achieved.

Outbound Method to Improve Group B Children's Cooperation Ability

The lack of application of creative learning methods hinders children's focus in completing assignments. This research aims to determine the significant effect of using the outbound method to improve group B children's cooperative abilities, such as interpreting instructions and directing when mistakes occur. This type of research is a quasi-experiment with a non-equivalent control group design. The population in this study was 38 children. Research samples were taken using random sampling techniques. The selected models were Group B1, with 20 children as the experimental group, and Group B2, with 18 children as the control group. The data collection method used is a non-test method, namely observation with an analysis method using inferential statistics. The results of this study showed that the average post-test score for the experimental group was 95.17, while for the control group, it was 63.28. The results of data analysis obtained a count of 18.58. The data analysis shows that using the outbound method affects the cooperative abilities of group B children. It is concluded that the outbound process can improve the collective skills of group B children.

Deep learning-based image classification of MRI brain image

This article reviews the latest research on MRI brain image classification techniques based on deep learning. Firstly, MRI brain image classification and traditional machine learning methods applied to MRI image classification were briefly introduced. Then, a review was conducted on existing MRI brain image classification methods based on deep learning. The article reviews past and recent related research and provides a detailed introduction to the application of deep learning methods in MRI brain image classification. This includes some traditional machine learning methods and research achievements in deep neural networks (DNN), convolutional neural networks (CNN), and transfer learning. The most commonly used deep learning architecture for image classification is CNN. Research has shown that deep learning methods have high accuracy and performance in MRI brain image classification and can automatically extract image features for effective classification. Therefore, deep learning methods provide doctors with more comprehensive information, help them make more accurate diagnoses and formulate treatment plans, and have broad prospects for application in MRI brain image classification. In the future, the further development of deep learning technology will achieve better auxiliary effects on diagnosis, treatment, and scientific research related to the brain.

RELATIONSHIP BETWEEN LANGUAGE LEARNING STRATEGIES AND ACHIEVEMENT WITH LEARNING MOTIVATION AMONG STUDENTS OF CHINESE AS FOREIGN LANGUAGE PROGRAMME IN MALAYSIA

In Malaysia, teaching Chinese as a foreign language began in 1963 and has grown in popularity. Language Learning Strategies, or the measures students take to increase their learning, are critical to the final success of Chinese as a Foreign Language. Student achievement is determined by the application of language learning methods. Learning motivation, on the other hand, has a significant impact on academic achievement. This study's purpose is to (1) investigate the level of Language Learning Strategy, Learning motivation, and Language Learning achievement. (2) To investigate the relationship between Language Learning Strategy and Language Learning achievement; (3) To investigate the relationship between Language Learning Strategy and Learning motivation; and (4) To investigate the relationship between Learning Motivation and Language Learning Achievement among students of the Chinese as a Foreign Language programme in Malaysia. The collected data were analysed quantitatively using SPSS for descriptive analysis and the relationship between language learning strategies, learning motivation, and achievement. The Pearson correlation analysis showed the highly correlated between language learning strategies, learning motivation, and achievement.

PENGGUNAAN METODE PEMBELAJARAN INOVATIF MELALUI DEMONTRASI TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN FIQH

Nowadays there are many problems faced by students' decreased interest in learning, even though interest has a big influence on learning, Therefore, to increase interest in learning, it is very necessary to apply learning methods that attract students' interest, so that it is easier to learn and quickly understood in learning. This study aims was to increase students' understanding of the practice of worship in fiqh subjects.The application of innovative learning methods through the demontration strategy is very suitable to be applied in the learning process. The demontration strategy is a learning model that uses examples. This research was conducted at MI Mathla’ul Anwar Kota Dukuh, Pandeglang Regency. This research was conducted for 2 months, from September to October 2023. The time of this research was carried out in the odd semester of the 2023/2024 school year. This study uses experimental research methods. The type of experiment used is Quasy Experimental, that is, there is a control group However, it cannot provide overall control over external variables that influence the implementation of the experiment. The approach used in this research is a quantitative approach. In the Homogeneity Test, the results obtained were Fcount < Ftable or 1.07 < 2.215, then the data obtained was homogeneous, in the t test the results were obtained tcount=16.07 and table=2.044 so that the Coefficient of Determination obtained a value of 88.36, the contribution of variable X was obtained to the Y variable of 88.36% while the remainder is equal to 11.64% followed by other variables. The conclusion in this research is that the demonstration learning strategy can increase students' understanding in learning, especially in the material of religious practice in fiqh subjects.