• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2904-2926
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• 2022

Currently, diabetes is the most common chronic disease in the world, affecting 23.7% of the population in the Kingdom of Saudi Arabia. Diabetes may be the cause of lower-limb amputations, kidney failure and blindness among adults. Therefore, diagnosing the disease in its early stages is essential in order to save human lives. With the revolution in technology, Artificial Intelligence (AI) could play a central role in the early prediction of diabetes by employing Machine Learning (ML) technology. In this paper, we developed a diagnosis system using machine learning models for the detection of type 2 diabetes among adults, through the adoption of two different diabetes datasets: one for training and the other for the testing, to analyze and enhance the prediction accuracy. This work offers an enhanced classification accuracy as a result of employing several pre-processing methods before applying the ML models. According to the obtained results, the implemented Random Forest (RF) classifier offers the best classification accuracy with a classification score of 98.95%.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.307-312
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• 2004

In our fast-moving information and knowledge society, skills and know-how rapidly become outdated. Virtual learning environments play a key role in meeting today's growing demand for customized educational and vocational training and lift-long teaming. The scope of multimedia-based and web-supported education is illustrated by means of an interdisciplinary multimedia project 'New Statistics' funded by the German government. The project output contains more than 70 learning modules covering the complete curriculum of an introductory statistics course. All modules are based on a statistical laboratory and on a multitude of Java applets, animations and case studies. The paper focuses on presenting the statistical laboratory and the applets. These components present the main project pillars and are particularly suitable for international use, independently from the original project framework. This article also demonstrates the application of Java applets and other multimedia developments from the educational world to official statistics for interactive presentation of statistical information.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.1001-1007
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• 2024

Recent deep learning algorithms for object detection in real-time play a crucial role in various applications such as autonomous driving, traffic monitoring, health care, and water quality monitoring. The size of small objects, in particular, significantly impacts the accuracy of detection models. However, data containing small objects can lead to underfitting issues in models. Therefore, this study developed a deep learning model capable of quickly detecting small objects to provide more accurate predictions. The RE-SOD (Residual block based Small Object Detector) developed in this research enhances the detection performance for small objects by using RGB separation preprocessing and residual blocks. The model achieved an accuracy of 1.0 in image classification and an mAP50-95 score of 0.944 in object detection. The performance of this model was validated by comparing it with real-time detection models such as YOLOv5, YOLOv7, and YOLOv8.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.161-165
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• 2023

One of the difficult works in an autonomous driving system is detecting road lanes or objects in the road boundaries. Detecting and tracking a vehicle is able to play an important role on providing important information in the framework of advanced driver assistance systems such as identifying road traffic conditions and crime situations. This paper proposes a vehicle detection scheme based on deep learning to classify and tracking vehicles in a complex and diverse environment. We use the modified YOLO as the object detector and polynomial regression as object tracker in the driving video. With the experimental results, using YOLO model as deep learning model, it is possible to quickly and accurately perform robust vehicle tracking in various environments, compared to the traditional method.

• Journal of Engineering Education Research
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• v.12 no.1
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• pp.73-81
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• 2009

This paper discusses the changing roles of tutors when engaging with e-learning of engineering basic design courses. Understanding the importance of these roles and identifying necessary tutoring skills are the two main keys to the success of e-learning solutions. Since online tutors play a critical role in e-learning, they must be equipped with an appropriate set of skills and attributes. The roles of e-tutors involve the social, organizational, intellectual, and technical tasks.

• The Mathematical Education
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• v.58 no.1
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• pp.41-54
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• 2019

The purpose of this study was to examine the effects of career identity on learning persistence and academic achievement, and mediating effect of utility value. To examine the effect of mediating role of utility value, we divided utility value into two types, utility value of daily matters and utility value of career. This study was conducted on 228 senior students in high school, to investigate relations among career identity, utility value, learning persistence and academic achievement in mathematics, by using the structural equation model. The results are as follows. First, career identity positively predicted learning persistence in mathematics. Second, career identity positively predicted the utility value of daily matters and career. Third, both type of utility value in mathematics positively predicted learning persistence in mathematics. Fourth, the utility value of daily matters and career, in mathematics subjects, showed differential predictability toward learning persistence and academic achievement. Both type of utility value in mathematics positively predicted learning persistence, but showed differential predictability toward learning academic achievement. Specifically, the utility value of daily matters in the near future did not predict the academic achievement, but the utility value of career in the distant future positively predicted the academic achievement. Fifth, the utility value was found to play a mediating role in the relationship between career identity and learning persistence. Based on the results of this study, implications for mathematics education were discussed.

• Cartoon and Animation Studies
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• s.32
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• pp.363-381
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• 2013

In this paper, on the web, offline mobile learning content to reinforce the learning of the video frame-by-frame necessary for re-learning area to capture only the important areas. The frame of the captured image and the image in the form of advanced training time saved and also a description of the notes feature to store. The area needed for the capture area re-learning the learner to learner-centered custom systems can be applied. In order to capture the learning program, regardless of the configuration of the selected frame by frame in order to capture the user-centric storytelling-based learning can be applied. Capture the full effect of the system compared to learning and learner-centered learning time-saving reconstruction of the frame according to the customized learning to play a positive role in improving effectiveness.

• Korean Parent-Child Health Journal
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• v.19 no.1
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• pp.25-32
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• 2016

Purpose: The purpose of this study was to use the social network analysis to verify the relationship between the interpersonal disposition and interactive characteristics of nursing college students. Five classes, a total of 117 nursing students were included in the study. Methods: The study interaction network centralization, density and in-degree & out-degree centrality were used as indicators for measuring students' study interaction. Also, the students' interpersonal disposition was measured using verified tool. Results: The results indicated that the ordinary type which gave and took the information generally showed the highest proportions in the study interaction network. Also, the empathic-acceptable tendency of social relation domain showed the highest proportions in the interpersonal disposition. Moreover, the students who play the isolate and the carrier role in the study interaction network had no relation with the expression tendency, and the transmitter role play students had no relation with the role tendency. Conclusion: Based on the results, the tutors should consider the students' interpersonal relationship disposition when implementing the instructional strategy in PBL curriculum.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.14-29
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• 2020

The 6G mobile communication system will become a backbone infrastructure around 2030 for the future digital world by providing distinctive services such as five-sense holograms, ultra-high reliability/low-latency, ultra-high-precision positioning, ultra-massive connectivity, and gigabit-per-second data rate for aerial and maritime terminals. The recent remarkable advances in machine learning (ML) technology have recognized its efficiency in wireless networking fields such as resource management and cell-configuration optimization. Further innovation in ML is expected to play an important role in solving new problems arising from 6G network management and service delivery. In contrast, an approach to apply ML to a physical-layer (PHY) target tackles the basic problems in radio links, such as overcoming signal distortion and interference. This paper reviews the methodologies of ML-based PHY, relevant industrial trends, and candiate technologies, including future research directions and standardization impacts.

• Journal of Korean Academy of Nursing
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• v.6 no.2
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• pp.32-38
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• 1976

The advanced knowledge is increasing day by day due to the progress of medicine and tectonics, the increase of nursing research nowadays. In parallel with these, nursing profession has a need of the nursing care with improvement of new Knowledge, tectonics and nursing procedure through the insertive education. Therefore, this study was attempted to investigate that to grasp learning need of nurses about inservice educational play a pivotal role in the progress of inservice education. This study was made from 242 clinical nurse at 4 hospitals in Seoul and through question- are consisting of 1) ideological part 2) basic sciences 3) nursing part 4) administrative part 5) the others from 10 July '75 to 7 Oct. '75. The data were treated by percentage, Licker method, arid chi- square examination. Significant difference p is 0.05. The results of this studies are as follows : A. learning needs of nurses 1) Generally the learning needs of nurses is very high. 2) Of the learning need of inservice education for nurses, the highest learning need is as follow (Table 2 ) 1 st : Charting 2 nd : The ability of grasping patient's needs and problems. 3 rd ; The contents and the methods of the advanced nursing skill. 4 th ; The importance of team work 5 th ; The general knowledge of the various disease 6 th : The decision of a propriety nursing diagnosis under the general condition. 7 th ; The introduction of the new nursing theory. 8 th : The Nurses role and the responsibility in emergency and disaster. 9 th : The improvement of nursing skill for the perfect interpersonal relationship. l0th ; Cultural education: B . Verification of hypothesis 1. Hypothesis I , learning needs of nurses and educational level of nurse will be correlated, is rejected (Table 3 ) 2. Hypothesis II, learning need of nurses and duties of post will be correlated, is rejected (Table 4) 3. Hypothesis III, learning need of nurse and clinical experience of nurses will be correlated, is rejected (Table 5).