• Journal of the Korea Society of Computer and Information
• /
• v.15 no.9
• /
• pp.145-153
• /
• 2010

E-learning is cyber-education that gives open education to everyone by providing various contents through Internet and IT technologies, and it has been spreading rapidly. In this paper, we describes an effective prototype design scheme for establishing e-Learning center, centered on the case of A University, in order to overcome a lot of shortcomings related to cyber-education and to settle down efficient and systematic on-line realtime cyber education. For this purpose, we first analyzed the current status concerning e-Learning at A University. Learners and lecturers then participated in a survey so that we could find some problems on current e-Learning and prepare their solutions. We finally designed e-Learning center prototypes, and selected the prototype 2 as a best one and designed it in more details. The prototype made in this paper would be very useful to other institutes who want to establish a new e-Learning center.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.10
• /
• pp.9-17
• /
• 2021

Humans are social animals that have gained information or social interaction through dialogue. In conversation, the mood of the word can change depending on the sensibility of one person to another. Relationships between characters in films are essential for understanding stories and lines between characters, but methods to extract this information from films have not been investigated. Therefore, we need a model that automatically analyzes the relationship aspects in the movie. In this paper, we propose a method to analyze the relationship between characters in the movie by utilizing deep learning techniques to measure the emotion of each character pair. The proposed method first extracts main characters from the movie script and finds the dialogue between the main characters. Then, to analyze the relationship between the main characters, it performs a sentiment analysis, weights them according to the positions of the metabolites in the entire time intervals and gathers their scores. Experimental results with real data sets demonstrate that the proposed scheme is able to effectively measure the emotional relationship between the main characters.

• Journal of the Korea Convergence Society
• /
• v.12 no.9
• /
• pp.1-10
• /
• 2021

In the past, designers relied primarily on past experience and reference to industry standard thresholds to design spaces. Such design often results in spaces that do not meet the needs of users. The purpose of this paper is to investigate the process and way of generating design parameters by constructing a BP neural network algorithm for spatial design. From the perspective. This paper adopts an experimental research method to take a kindergarten with a large number of complex needs in space as the object of study, and through the BP neural network algorithm in machine learning, the correlation between environmental behavior parameters and spatial design parameters is imprinted. The way of generating spatial design parameters is studied. In the future, the corresponding spatial design parameters can be derived by replacing specific environmental behavior influence factors, which can be applied to a wider range of scenarios and improve the efficiency of designers.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.9
• /
• pp.27-35
• /
• 2021

Artificial life is used in various fields of applied science by evaluating natural life-related systems, their processes, and evolution. Research has been actively conducted to evolve physical body design and behavioral control strategies for the dynamic activities of these artificial life forms. However, since co-evolution of shapes and neural networks is difficult, artificial life with optimized movements has only one movement in one form and most do not consider the environmental conditions around it. In this paper, artificial life that co-evolve bodies and neural networks using predator-prey models have environmental adaptive movements. The predator-prey hierarchy is then extended to the top-level predator, medium predator, prey three stages to determine the stability of the simulation according to initial population density and correlate between body evolution and population dynamics.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.251-256
• /
• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.6
• /
• pp.105-109
• /
• 2021

In this paper, we evaluate Boosted 3-D PCA as a Dataset and evaluate its performance. After that, we will analyze the network features and performance. In this paper, the learning was performed using the 300W-LP data set using the same learning method as Boosted 3-D PCA, and the evaluation was evaluated using the AFLW2000 data set. The results show that the performance is similar to that of the Boosted 3-D PCA paper. This performance result can be learned using the data set of face images freely than the existing Landmark-to-Pose method, so that the poses can be accurately predicted in real-world situations. Since the optimization of the set of key points is not independent, we confirmed the manual that can reduce the computation time. This analysis is expected to be a very important resource for improving the performance of network boosted 3-D PCA or applying it to various application domains.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.7
• /
• pp.251-256
• /
• 2021

Software Product Line Engineering (SPLE) has been known as an efficient and effective software reuse methodology. One of the key activities of SPLE is scoping analysis, which determines the range of the features to be developed as reusable assets. Although several scoping methods has been reported, they are not sufficient to apply them to the defense domain. In this paper, we present a scoping method applicable to the defense domain, and present a case study for applying SPLE to inertial navigation weapon system. At first, the proposed method determines the range of candidate features to be applied for the platform. The range is then adjusted from the perspective of product benefit. The final range of features is decided through considering the total cost of a product line. We will demonstrate and evaluate the applicability of the proposed method by showing how we can decide the scope of features to be engineered for the navigation software product line.

• The Journal of the Korea Contents Association
• /
• v.21 no.7
• /
• pp.619-628
• /
• 2021

This study identified the relationship between adolescents' alienation and stress responses, and examined the mediating model of smart media addiction moderated by behavioral activation system (BAS) on alienation and stress responses. Participants were 361 male and female students in middle and high schools located at Seoul metropolitan area. PROCESS Macro 3.5 Model 7 was used for analysis of the moderating mediating effect. Results revealed that adolescents' alienation and BAS were positively correlated with smart media addiction and stress responses, while smart media addiction was positively correlated with stress responses. In a moderated mediating model for stress responses, there was significant interaction effect of alienation and BAS; conditionally indirect effect of alienation was not significant in groups with very low BAS. These findings suggest that adolescents who feel alienation are more likely to experience stress responses by overindulging themselves in using smart media. The moderating effect suggests that this effect is stronger with higher levels of BAS.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.43-49
• /
• 2019

The wired and wireless Internet is a useful window to easily acquire various types of media data. On the other hand, the public can easily get the media data including the object to which the personal information is exposed, which is a social problem. In this paper, we propose a method to robustly detect a target object that has exposed personal information using a learning algorithm and effectively block the detected target object area. In the proposed method, only the target object containing the personal information is detected using a neural network-based learning algorithm. Then, a grid-like mosaic is created and overlapped on the target object area detected in the previous step, thereby effectively blocking the object area containing the personal information. Experimental results show that the proposed algorithm robustly detects the object area in which personal information is exposed and effectively blocks the detected area through mosaic processing. The object blocking method presented in this paper is expected to be useful in many applications related to computer vision.

• Journal of Internet Computing and Services
• /
• v.20 no.4
• /
• pp.39-46
• /
• 2019

In recently years, it has become important to detect underground objects of various marterials including metals, such as detecting the location of sink holes and pipe. For this reason, ground penetrating radar(GPR) technology is attracting attention in the field of underground detection. GPR irradiates the radar wave to find the position of the object buried underground and express the reflected wave from the object as image. However, it is not easy to interpret GPR images because the features reflected from various objects underground are similar to each other in GPR images. Therefore, in order to solve this problem, in this paper, to estimate the piping position in the GRP image according to the threshold value using the CNN (Convolutional Neural Network) model based on deep running, which is widely used in the field of image recognition, As a result of the experiment, it is proved that the pipe position is most reliably detected when the threshold value is 7 or 8.