• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.183-192
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• 2023

This study analyzes the performance of flipped learning, an offline class method conducted in a degree-linked work-learning parallel system. Training in the work-study parallel system, which is conducted as part of job competency improvement, has thoroughly adhered to the offline method, but in line with COVID-19, unlike before, it is changing in the direction of using the online method more actively. However, educational methods such as flipped learning are not new because the degree-linked operation is applied to the academic system and education method of universities and is practically the same form as general university education. Therefore, it is necessary to analyze the educational performance and complementary points of flipped learning, which has recently been expanded in the degree-linked work-study parallel system, considering the characteristics of this system, in which classes are held only on weekends. As a result of statistical analysis based on the survey, some of the outcomes of flipped learning have been confirmed, and in order to increase the performances, it is necessary to continuously seek out specific measures to encourage learning and expand communication between instructors and students.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• Computers and Concrete
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• v.32 no.3
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• pp.263-286
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• 2023

Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.39-48
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• 2023

Breast cancer screening makes extensive utilization of mammography. Even so, there has been a lot of debate with regards to this application's starting age as well as screening interval. The deep learning technique of transfer learning is employed for transferring the knowledge learnt from the source tasks to the target tasks. For the resolution of real-world problems, deep neural networks have demonstrated superior performance in comparison with the standard machine learning algorithms. The architecture of the deep neural networks has to be defined by taking into account the problem domain knowledge. Normally, this technique will consume a lot of time as well as computational resources. This work evaluated the efficacy of the deep learning neural network like Visual Geometry Group Network (VGG Net) Residual Network (Res Net), as well as inception network for classifying the mammograms. This work proposed optimization of ResNet with Teaching Learning Based Optimization (TLBO) algorithm's in order to predict breast cancers by means of mammogram images. The proposed TLBO-ResNet, an optimized ResNet with faster convergence ability when compared with other evolutionary methods for mammogram classification.

• Journal of Engineering Education Research
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• v.19 no.6
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• pp.57-62
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• 2016

In this work, we present a case study of using the assessments for the enhancement of students' learning motivation in engineering education. The assessments, given in between summative assessments such as midterms and finals, may have a component of formative evaluation, which are reported as very effective tools as the sources of feedback to improve teaching and learning. We studied how the students' performance is improved by additional tests in engineering education. Also, we examined the factors of successful results of the cooperative learning model, Student Teams-Achievement Division, which is based on imposing a number of tests, achieved in our previous work.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.1-8
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• 2019

This study examined the constructivist perspective and the characteristics of informal learning in relation to work place learning of sports center leaders through a theoretical approach. For this reason, informal learning has important learning meaning because sports center leaders based on informal learning enable them to develop their professionalism through workplace learning in terms of experience and practice in promoting the process of growth and learning. Can be. In addition, the leaders in the sports center coaching sites lack formal learning opportunities in workplace learning compared to office workers in general companies. Therefore, the type of informal learning and the way to improve learning should be presented. This part is considered to be an educational element as an important factor for the professionalism of sports center leaders. In addition, the establishment of a workplace learning environment in personal, environmental, institutional and organizational aspects will help sports center leaders to increase their professionalism.

• The Journal of Bigdata
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• v.7 no.1
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• pp.1-14
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• 2022

The proof-of-work consensus algorithm used by most blockchains is causing a massive waste of computing resources in the form of mining. A useful proof-of-work consensus algorithm has been studied to reduce the waste of computing resources in proof-of-work, but there are still resource waste and mining centralization problems when creating blocks. In this paper, the problem of resource waste in block generation was solved by replacing the relatively inefficient computation process for block generation with distributed artificial intelligence model learning. In addition, by providing fair rewards to nodes participating in the learning process, nodes with weak computing power were motivated to participate, and performance similar to the existing centralized AI learning method was maintained. To show the validity of the proposed methodology, we implemented a blockchain network capable of distributed AI learning and experimented with reward distribution through resource verification, and compared the results of the existing centralized learning method and the blockchain distributed AI learning method. In addition, as a future study, the thesis was concluded by suggesting problems and development directions that may occur when expanding the blockchain main network and artificial intelligence model.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.3-11
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• 2023

To address the high accident rate in the construction industry, there is a growing interest in implementing virtual reality (VR)-based construction safety training. However, existing training approaches often failed to consider learners' individual characteristics, resulting in inadequate training for some individuals. This study aimed to investigate the impact of personal characteristics on learning performance in VR-based construction safety training using machine learning and SHAP (SHAPley Additional exPlanations). This study revealed that age exerted the greatest influence on learning performance, while work experience had the least impact. Furthermore, age exhibited a negative relationship with learning performance, indicating that the introduction of VR-based construction safety training can be effective for younger individuals. On the other hand, academic degree, qualifications, and work experience exhibited a positive relationship. To enhance learning performance for individuals with lower academic degree, it is necessary to provide content that is easier to understand. The lower qualifications and work experience have minimal impact on learning performance, so it is important to consider other learners' characteristics so as to provide appropriate educational content. This study confirmed that personal characteristics can significantly affect learning performance in VR-based construction safety training, highlighting the potential for leveraging these findings to provide effective safety training for construction workers.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.359-366
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• 2013

Although many research efforts have been conducted to address the effect of crew members' work skills (e.g., technical and planning skills) on work performance (e.g., work duration and quality) in construction projects, the relationship between skill and performance has generated a great deal of controversy in the field of management (Inkpen and Crossan 1995). This controversy can lead to under- or over-estimations of the overall project schedule, and can make it difficult for project managers to implement appropriate managerial policies for enhancing project performance. To address this issue, the following aspects need to be considered: (a) work performances are determined not only by individual-level work skill but also by the group-level work skill affected by work team members, each member's role, and any working behavior pattern; (b) work planning has significant effects on to what extent work skill enhances performance; and (c) different types of activities in construction require different types of work, skill, and team composition. This research, therefore, develops a system dynamics (SD) model to analyze the effects of both individual-and group-level (i.e., multi-level) skill on performances by utilizing the advantages of SD in capturing a feedback process and state changes, especially in human factors (e.g., attitude, ability, and behavior). The model incorporates: (a) a multi-level skill evolution and relevant behavior development mechanism within a work group; (b) the interaction among work planning, a crew's skill-learning, skill manifestation, and performances; and (c) the different work characteristics of each activity. This model can be utilized to implement appropriate work planning (e.g., work scope and work schedule) and crew management policies (e.g., work team composition and decision of each worker's role) with an awareness of crew's skill and work performance. Understanding the different characteristics of each activity can also support project managers in applying strategic work planning and crew management for a corresponding activity, which may enhance each activity's performance, as well as the overall project performance.

• Journal of Korean Elementary Science Education
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• v.21 no.1
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• pp.111-125
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• 2002

The aim of this study is to make it sure how pupils' science inquiry skills and attitude are influenced when they are taught by using the work-sheets for the differentiated learning according to their ability. In order to accomplish this aim, two classes of the fourth grade in the elementary school were distinguished into two groups: one was the experimental class and the other, the comparative class. The experimental class was given 52 hours of science lessons using the above sheets, and the comparative class, the general method of teaching. In order to compare their scientific interest and learning ability of the two groups each other, pupils were tested the standardized achievement in advance. The two groups were also given "ex post facto test" to measure the variation of their inquiry skills and attitude after the lessons. In addition, the experimental class was tested to measure their learning attitude after they are teamed the science with the sheets. The results of this study are as follows: 1. According to the percentile statistics of the science inquiry skills test between the two groups, the work-sheets for the differentiated teaming helped pupils develope their inquiry skills remarkably. 2. The work-sheets did not lead to significant difference between the learning ability of boys and girls. 3. The science lesson using the work-sheets showed positive influences in increasing pupils' scientific attitude. 4. About 77.2 percent of pupils accepted the excellent records of the evaluation in the science lesson using the sheets. It can be, therefore, concluded that the science lesson using the work-sheets for differentiated teaming is one of effective science lessons to increasing pupils' science inquiry skills, compared with the general teaching method.