• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.297-303
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• 2020

This study compared the perceptions of novice teachers and expert teachers on software education in the 2015 revised curriculum. Awareness comparisons were assessed by questionnaire for priorities for field support, activities for professional development, organizational hours, achievement criteria statements, and appropriateness for textbooks introduced only in 6th grade. In all questions, there was a difference in recognition between the two groups. In particular, novice teachers were '' appropriate '' in terms of organizational hours, achievement criteria, and textbooks introduced only in 6th grade. Expert teachers, on the other hand, were inadequate. In addition, as a result of analyzing the key keywords of free-response opinions about the introduction of educational robots in the curriculum and textbooks, positive keywords were obtained for both groups. However, novice teachers showed passive and passive keywords such as 'support', 'difficulty', and 'problems', and expert teachers showed differences in their educational utilization after introducing 'utilization' and 'education'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1676-1681
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• 2020

Collecting and managing information on all-round activities of students not only helps to improve school life adjustment and satisfaction, but also serves as the basis for preventive student support for academic warnings or dropouts. Therefore, in guiding students, it is necessary to integrate various information of students and provide them to the instructor quickly and accurately. In this study, in the special environment of an organization in which student information is scattered in several systems, a system model is proposed that not only integrates and provides student information to instructors quickly, but also saves cost and effort. And we tested the effectiveness of the proposed system model by developing a simple web page. As a result, it was confirmed that the proposed model provided information necessary for student guidance in an integrated, multifaceted, and instantaneous manner, and that user satisfaction was improved through an improved UI.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.109-117
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• 2011

We can use document issuance services provided by a school, bank, hospital, company, etc. either by visiting those facilities or by simply visiting their Web sites. Services available through the Internet allow us to use the same services as we do by actually going to those facilities at home or office any time. As much as it saves us time and money, there also arises a problem of information being forged on the Internet or on a printed document. There has to be security functions to deal with the problem. This paper intends to think of the possible security threats and draw out the necessary security functions that an on-line document issuance system should have based on the CC v3.1, so that anyone can use it as reference when they evaluate or introduce the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.628-636
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• 2021

This paper contains the implementation and performance evaluation results of a system that collects environmental data at the time when the wild animal intrusion occurred at farms and then predicts future wild animal intrusions through a machine learning-based Vector Autoregression(VAR) model. To collect the data for intrusion prediction, an IoT-based hardware prototype was developed, which was installed on a small farm located near the school and simulated over a long period to generate intrusion events. The intrusion prediction service based on the implemented VAR model provides the date and time when intrusion is likely to occur over the next 30 days. In addition, the proposed system includes the function of providing real-time notifications to the farmers mobile device when wild animals intrusion occurs in the farm, and performance evaluation was conducted to confirm that the average response time was 7.89 seconds.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.134-139
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• 2022

Recently, interest in programming and artificial intelligence is continuously increasing, and software education is being implemented as a mandatory education from elementary school. For efficient programming education, it is basically necessary to build a lab environment suitable for students and teachers, but there are performance problems due to the inadequacy of old computers and network equipment. Therefore, in this paper, we propose a web page-based online practice environment and algorithm competition scoring system using React and Spring boot to solve the problem of the programming practice environment. Through this, it is thought that programming learning can be carried out using only a web browser even on low-spec computers. In addition, since various programming languages can be learned irrespective of the language to be learned, it is considered that the time cost for establishing a practice environment can be reduced.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.510-518
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• 2022

The diagnostic evaluation conducted at the national level is very important to detect underachievers in school early. This study used an artificial intelligence method to find the characteristics of underachievers that affect learning development for middle school students. In this study an artificial intelligence model was constructed and analyzed to determine whether the Busan Education Longitudinal Data in 2020 by entering data from the first year of middle school in 2019. A predictive model was developed to predict basic middle school Korean, English, and mathematics education with machine learning algorithms, and it was confirmed that the accuracy was 78%, 82%, and 83%, respectively, in the prediction for the next school year. In addition, by drawing an achievement prediction decision tree for each middle school subject we are analyzing the process of prediction. Finally, we examined what characteristics affect achievement prediction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.930-935
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• 2022

The ability to use software is an essential competency in modern society. As a result, programming education is conducted from elementary school to university. In case of programming education for non-majors conducted in the liberal arts at universities, if it is conducted online using high-quality contents, problems such as the shortage of professional professor and the limitation of practice time can be solved. Also, it has the advantage of providing students with enough time to think and solve problems. In this paper, the possibility of online lectures was investigated through a survey before and after lectures in software liberal arts courses conducted online. From the results of the survey, it is judged that the goal of software education can be achieved even if software lectures are conducted online, which is to improve computational thinking and problem-solving skills.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.91-98
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• 2022

In this study, Pukyong National University's floating population survey and analysis were conducted using Raspberry Pie, an open source hardware, and object detection algorithms based on deep learning technology. After collecting images using Raspberry Pie, the person detection of the collected images using YOLO3's IMAGEAI and YOLOv5 models was performed, and Haar-like features and HOG models were used for accuracy comparison analysis. As a result of the analysis, the smallest floating population was observed due to the school anniversary. In general, the floating population at the entrance was larger than the floating population at the exit, and both the entrance and exit were found to be greatly affected by the school's anniversary and events.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.641-648
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• 2022

In this study, the performance of the NHPP software reliability model with exponential distribution (Exponential Basic, Inverse Exponential, Lindley, Rayleigh) characteristics was comparatively analyzed, and based on this, the optimal reliability model was also presented. To analyze the software failure phenomenon, the failure time data collected during system operation was used, and the parameter estimation was solved by applying the maximum likelihood estimation method (MLE). Through various comparative analysis (mean square error analysis, true value predictive power analysis of average value function, strength function evaluation, and reliability evaluation applied with mission time), it was found that the Lindley model was an efficient model with the best performance. Through this study, the reliability performance of the distribution with the characteristic of the exponential form, which has no existing research case, was newly identified, and through this, basic design data that software developers could use in the initial stage can be presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.1-8
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• 2022

Recently, Google MedeiaPipe presents a novel approach for neural network-based hair segmentation from a single camera input specifically designed for real-time, mobile application. Though neural network related to hair segmentation is relatively small size, it produces a high-quality hair segmentation mask that is well suited for AR effects such as a realistic hair recoloring. However, it has undesirable segmentation effects according to hair styles or in case of containing noises and holes. In this study, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood function. It is further optimized according to graph cuts algorithm and initial hair region is obtained. Finally, clustering algorithm and image post-processing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. The proposed method is applied to MediaPipe hair segmentation pipeline.