• The Journal of Bigdata
• /
• v.5 no.1
• /
• pp.181-188
• /
• 2020

As the size of the airport terminal grows in line with the rapid growth of aviation passengers, the advanced baggage handling system that combines various data technologies has become an essential element in order to handle the baggage carried by passengers swiftly and accurately. Therefore, this study introduces the method of analyzing the baggage handling capacity of domestic airports through the latest data analysis methodology from the process point of view to advance the operation of the airport BHS and the main points based on event log data. By presenting an accurate load prediction method, it can lead to advanced BHS operation strategies in the future, such as the preemptive arrangement of resources and optimization of flight-carrousel scheduling. The data used in the analysis utilized the APIs that can be obtained by searching for "Korea Airports Corporation" in the public data portal. As a result of applying the method to the domestic airport BHS simulation model, it was possible to confirm a high level of predictive performance.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.5
• /
• pp.359-368
• /
• 2013

Mashup is a web application that combines several different sources to create new services using Open APIs(Application Program Interfaces). Although the mashup has become very popular over the last few years, there are several challenging issues when combining a large number of APIs into the mashup, especially when composite APIs are manually integrated by mashup developers. This paper proposes a novel algorithm for automatic Open API composition. The proposed algorithm consists of constructing an operation connecting graph and searching composition candidates. We construct an operation connecting graph which is based on the semantic similarity between the inputs and the outputs of Open APIs. We generate directed acyclic graphs (DAGs) that can produce the output satisfying the desired goal. In order to produce the DAGs efficiently, we rapidly filter out APIs that are not useful for the composition. The algorithm is evaluated using a collection of REST and SOAP APIs extracted from ProgrammableWeb.com.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.48 no.1
• /
• pp.13-21
• /
• 2020

Surrogate models have been used for the rapid estimation of six-DOF aerodynamic coefficients in the context of the design and control of a missile. For this end, we may generate highly accurate surrogate models with a multitude of aerodynamic data obtained from wind tunnel tests (WTTs); however, this approach is time-consuming and expensive. Thus, we aim to swiftly predict aerodynamic coefficients via co-Kriging using a few WTT data along with plenty of computational fluid dynamics (CFD) data. To demonstrate the excellence of co-Kriging models based on both WTT and CFD data, we first generated two surrogate models: co-Kriging models with CFD data and Kriging models without the CFD data. Afterwards, we carried out numerical validation and examined predictive trends to compare the two different surrogate models. As a result, we found that the co-Kriging models produced more accurate aerodynamic coefficients than the Kriging models thanks to the assistance of CFD data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2006.05a
• /
• pp.581-584
• /
• 2006

Cellular phones have been popularized and some of them even have access to the Internet. But the utilization of mobile phones has not been for education but only focused on particular services due to the text-based low capacity. This thesis proposes a multimedia education system using cell phones with SMIL. We can decrease the size of the parser and refute the resources of CPU by designing SMIL tag only, which is needed for multimedia education. In addition, the macro method for producing information for lectures will make possible decreased transmission quantity of multimedia contents and increased transmission efficiency. This will lead to overcoming the matter of insufficient CPU and memory, which is common to most mobile phone terminals.

• Journal of KIISE:Information Networking
• /
• v.33 no.1
• /
• pp.103-112
• /
• 2006

Priority-based network service has been widely adopted for the Internet traffic management in the context of IETF differentiated services, and computing optimal prices for such priority-based service is the key topic in many pricing literature. While the equilibrium analysis has been commonly used to this end, many have criticized the validity of the underlying assumption of equilibrium analysis that user utility functions are precisely known. In this paper, we propose a solution for bridging the gap between the existing theoretical work on optimal pricing and the unavailability of precise user utility information in real networks. In the proposed method, the service provider obtains more and more accurate estimates of user utility functions from the initial imprecise knowledge by iteratively changing the price of service levels and observing the users' decisions under the changed price. Our contribution is two-fold. First, we have developed a general principle for estimating the user utility functions. Second, we have developed a novel method for setting the prices that can optimize the extraction of the knowledge about user utility functions. The extensive simulation results demonstrate the effectiveness of our method.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.2
• /
• pp.81-86
• /
• 2014

In this paper, we present an effective sound classification system for recognizing the real-time context of a smartphone user. Our system avoids unnecessary consumption of limited computational resource by filtering both silence and white noise out of input sound data in the pre-processing step. It also improves the classification performance on low energy-level sounds by amplifying them as pre-processing. Moreover, for efficient learning and application of HMM classification models, our system executes the dimension reduction and discretization on the feature vectors through k-means clustering. We collected a large amount of 8 different type sound data from daily life in a university research building and then conducted experiments using them. Through these experiments, our system showed high classification performance.

• Journal of Korea Society of Industrial Information Systems
• /
• v.24 no.4
• /
• pp.1-8
• /
• 2019

Plant phenomics is a technique for observing and analyzing morphological features in order to select plant varieties of excellent traits. The conventional methods is difficult to apply to the phenomics system. because the color threshold value must be manually changed according to the detection target. In this paper, we propose the convolution neural network (CNN) structure that can automatically segment plants from the background for the phenomics system. The LeafNet consists of nine convolution layers and a sigmoid activation function for determining the presence of plants. As a result of the learning using the LeafNet, we obtained a precision of 98.0% and a recall rate of 90.3% for the plant seedlings images. This confirms the applicability of the phenomics system.

• Journal of the Korean Society of Earth Science Education
• /
• v.12 no.2
• /
• pp.151-164
• /
• 2019

The purpose of this study is to find out the effects of reconstructing unit 'Seasonal Change' using step-by-step questioning for concepts changes to adjusting misconceptions of elementary school students. Most students have pre-conceptions at describing seasonal changes based on their experiences. Therefore, in newly developed unit, we reconstructed unit to include core teaching and learning contents by finding out common pre-conceptions of students and specifying purpose of teaching at misconceptions found in pre-conceptions as 'constituent of class for conceptual change'. After the scientific concept test, the result of 24 students in experimental group is statistically significant. Also, according to the result of qualitative analysis, the number of activated conceptional resources and degree of specificity in explaining seasonal changes are higher than that of control group.

• The Journal of the Convergence on Culture Technology
• /
• v.5 no.1
• /
• pp.77-82
• /
• 2019

AI is applied increasingly to overall industries such as living, medical, financial service, autonomous car, etc. thanks to rapid technology development. AI-leading countries are strengthening their competency to secure competitiveness since AI is positioned as the core technology in $4^{th}$ Industrial Revolution. Although Korea has the competitive IT infra and human resources, it lags behind traditional AI-leaders like United States, Canada, Japan and, even China which devotes all its might to develop intelligent technology-intentive industry. AI is the critical technology influencing on the national industry in the near future according to advancement of intelligent information society so that concentration of capability is required with national interest. Also, joint development with global AI-leading companies as well as development of own technology are crucial to prevent technology subordination. Additionally, regulatory reform and preparation of related law are very urgent.

• Journal of the Korea Convergence Society
• /
• v.12 no.4
• /
• pp.125-133
• /
• 2021

With the advent of experience era, the user experience has attracted much attention in all walks of life. And the importance of user experience emphasize began to be emphasized. It analyzed the interfering factors of user experience of smart phone medical APP, and evaluated their relative importance. Then it made suggestions on the priority of medical APP development and provided reference for medical APP design optimization and service quality improvement. First of all, based on the related research about user experience theory, smartphone APP user experience and mobile medical APP, it summarized the user experience elements of smartphone medical APP. Secondly, 200 subjects in the 20-40 age group who chose smartphone download experience and used medical APP were surveyed to rate the effect of 18 factors. The results show that the factors such as product resources, medical advertising recommendations, doctor-patient interaction, emotional pleasure, easy to learn, and other factors have a significant impact on users' good experience when using app.