• Journal of the Korea Society of Computer and Information
• /
• v.27 no.7
• /
• pp.177-185
• /
• 2022

In this paper, we attempt to explore consumers' willingness to continuously watch stage performances on virtual reality technology platforms and the mediating role of the psychological contract in it through the integration of service quality theory, thus constructing a continuous viewing model and conducting an empirical analysis through SPSS and AMOS. Through the analysis, we came to the following conclusions: 1. Interaction quality, physical environment quality, and outcome quality have a positive impact on psychological contract; 2. The psychological contract has a positive impact on the willingness to continuously watch; 3. Interaction quality, physical environment quality, and outcome quality positively influence the willingness to continuously watch through psychological contract. Therefore, this model can be used by companies to grasp consumers' perceptions of their own service quality and to formulate specific strategies, and it provides new directions and insights for stage performance companies.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.5
• /
• pp.221-228
• /
• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.5
• /
• pp.161-168
• /
• 2021

Cracks affect the robustness of infrastructures such as buildings, bridge, pavement, and pipelines. This paper presents an automated crack detection system which detect cracks in diverse surfaces. We first constructed the combined crack dataset, consists of multiple crack datasets in diverse domains presented in prior studies. Then, state-of-the-art deep learning models in computer vision tasks including VGG, ResNet, WideResNet, ResNeXt, DenseNet, and EfficientNet, were used to validate the performance of crack detection. We divided the combined dataset into train (80%) and test set (20%) to evaluate the employed models. DenseNet121 showed the highest accuracy at 96.20% with relatively low number of parameters compared to other models. Based on the validation procedures of the advanced deep learning models in crack detection task, we shed light on the cost-effective automated crack detection system which can be applied to different surfaces and structures with low computing resources.

• Advanced Industrial SCIence
• /
• v.2 no.3
• /
• pp.8-14
• /
• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• Journal of Industrial Convergence
• /
• v.21 no.3
• /
• pp.49-56
• /
• 2023

The purpose of this study is to verify the mediating effect of career adaptability in the relationship between growth mindset and occupational engagement. A total of 203 data were collected through an online survey targeting university students. For data analysis, frequency analysis and descriptive statistics analysis were used via SPSS 25.0 and AMOS 25.0 software. As a result of the study, growth mindset had a direct effect on occupational engagement (𝛽=.254, p<.01) and the mediating effect of growth mindset on occupational engagement through career adaptability was also statistically significant. (𝛽=.137, p<.01). This study suggests that it is important to promote occupational engagement for students' correct career guidance, and to this end a practical strategy for cultivating a growth mindset and career adaptability is needed.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.123-129
• /
• 2021

Recently, various platforms and contents for artificial intelligence education have been developed, but artificial intelligence education programs for the lower grades of elementary school are insufficient. Therefore, the purpose of this study is to develop an artificial intelligence education program for learners in the lower grades of elementary school. It was designed using the Novel Engineering, and its validity was verified by expert validation. It was necessary to construct a program based on spoken language rather than written language in consideration of the level of learners in the lower grades in the process of acquiring Hangeul, and to secure the number of educational hours through integration between subjects. There have been various research cases of software education with Novel Engineering, and its effectiveness has been verified. Artificial intelligence education is also expected to be applied in the school field through Novel Engineering.

• Convergence Security Journal
• /
• v.24 no.2
• /
• pp.79-87
• /
• 2024

This paper addresses the increasing cyber attacks exploiting security vulnerabilities in software due to the rise in web applications. CSRF (Cross-Site Request Forgery) attacks pose a serious threat to web users and developers and must be prevented in advance. CSRF involves performing malicious requests without the user's consent, making protection methods crucial for web applications. This study compares and verifies the CSRF defense performance of two frameworks, Spring Security and Apache Shiro, to propose an effectively applicable framework. The results show that both frameworks successfully defend against CSRF attacks; however, Spring Security processes requests faster, averaging 2.55 seconds compared to Apache Shiro's 5.1 seconds. This performance difference stems from variations in internal processing methods and optimization levels. Both frameworks showed no significant differences in resource usage. Therefore, Spring Security is more suitable for environments requiring high performance and efficient request processing, while Apache Shiro needs improvement. These findings are expected to serve as valuable references for designing web application security architectures

• Journal of KIISE:Software and Applications
• /
• v.29 no.8
• /
• pp.573-583
• /
• 2002

Pattern recognition process is made up of the feature extraction in the pre-processing, the pattern clustering by training and the recognition process. This paper presents the F-LVQ (Fuzzy Learning Vector Quantization) pattern classification model which is optimized by the fuzzy membership function for the OCR(Optical Character Recognition) system. We trained 220 numeric patterns of 22 Hangul and English fonts and tested 4840 patterns whose forms are changed variously. As a result of this experiment, it is proved that the proposed model is more effective and robust than other typical LVQ models.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.6
• /
• pp.403-412
• /
• 2013

This study figures out the concepts of container transport, logistical cost and the distribution of a company through studying documents, and to suggest logistical cost reduction approach, focused on the efficiency of transport which occupied the considerable portion of the total logistical cost of the company. We analyze and discuss the container loading of multiple items for multiple places of departure and arrival through a case study on S company in South Korea. We suggest a direction to reduce the logistical cost of the companies, analyzing the conditions of multiple items loading, and rule-based systems including an algorithm which determines container-loading for minimum freight expenses. We use data mining and OLAP tools of MS Analysis Services to produce loading rules for multiple items loading and generate OLAP cube and decision trees to validate the rules.

• Aerospace Engineering and Technology
• /
• v.13 no.2
• /
• pp.73-79
• /
• 2014

During developing cubesat flight software, Communication test between cubesat and ground station is needed. For this, we have constructed indoor ground station without outdoor antenna for decreasing total cost and time. In this time, if output power of ground station is high, it will affect for cubesat transceiver to be fail. For solving this problem, ground station must be designed for output power of it to be lower than input power of cubesat satellite, and it must be verified. In this paper, first, we describe cubesat indoor ground station using UHF and VHF. Second, we describe output power decreasing test for indoor operation of ground station by attaching attenuators in the end of the output connector.