• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.37-64
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• 2022

As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.317-323
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• 2008

Mass transit information can contribute many benefits to users. Especially, transportation information technology is developing highly with information technology in Korea recently. Hereafter, it is expected to give customized transportation information to users individually with the advent of ubiquitous age in earnest. This public transportation information service can be realized by path finding algorithm in public transportation networks including travel and transfer attributes. In this research, constraints are constructed with the primary facts influencing users. Moreover, the method reducing user's path finding condition arbitrarily is proposed by making the maximum value as variables. In this study, transfer frequency, total travel time, seat confirmation, transfer time and travel time become constraint condition based on k path finding algorithm considering service time constraint condition. Moreover, case study about user customized transfer information is performed in Seoul and metropolitan subway networks.

• Korean Journal of Social Welfare Studies
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• v.41 no.1
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• pp.307-343
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• 2010

This study, based on grounded theory, explores the child-rearing process of defecting North Korea women in South Korea. Interviews were conducted with five defecting North Korea women who had children. With the permission of the participants, the interviews were recorded with the digital recorder and transcribed by the researchers. Data were collected with in-depth interviews and observations until they were saturated. The interviews were analysed according to the constant comparative method used in grounded theory. The study derived 86 concepts, 31 subcategories and 11 categories in open coding. A core category was 'enduring hardships with hopes for children's success ' in selective coding. And The child-rearing process of the defecting North Korea women takes 'stage of entry', 'stage of confrontation', 'stage of struggle', 'stage of adjustment' and 'stage of hope for children's success'. The findings of the study will be useful in seeking an effective social welfare intervention plan for successful child-rearing of defecting North Korea women in South Korea.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.865-872
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• 2023

The purpose of this study was to analyze fabrics suitable for use as examination gowns to determine whether examination gowns affect imaging during anterior to posterior chest examinations(Chest AP) on a digital X-ray system. Examination gowns in use at five medical centers in Seoul were collected and included modal, tencel, cotton, and rayon fabrics. The selection of fabrics was based on studies that reported fabrics with good tactile, absorbent, stretchable, and wrinkle resistance. Phantoms of five hospital gowns and four fabrics, arranged in overlapping layers from one to eight, were created and examined on a digital X-ray system in both Chest AP examination. The images examined were subjected to a first-step profile analysis, a second-step signal intensity averaging analysis, and a third-step microscopic analysis. The results showed that all nine materials had an increasing impact on the image as the number of layers of fabric increased, with the modal fabric having the least impact on the image in the first, second, and third analyses. In conclusion, as the resolution of digital x-ray systems increases, the impact of examination clothing on the image will increase, and research to find suitable materials for examination clothing will continue to be necessary.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Korean Journal of Environmental Biology
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• v.41 no.3
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• pp.247-255
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• 2023

The occurrence of sudden strike pest events in urban areas is increasing as global warming intensifies, consequently, re causing harmful impacts. Studies on these incidents are fewer in number and insufficient compared to research on other nuisances such as mosquitoes and flies. Therefore, we conducted a study on the development of a selective collection method, using a filter layer to establish a monitoring system for Ephemera orientalis (Ephemeroptera: Ephemeridae), a species frequently identified as a sudden strike pest. Three sampling points were selected along the Hangang River in Namyangju, where E. orientalis outbreaks occur. Prototypes, consisting of four layers and with a light source attached to attract insects, were installed at each sampling point. Sampling was performed every 30 minutes between 19:00 and 22:30 in the month of June. The filter interval of each layer was adjusted so that the collected mayflies were distributed into specific layers. To evaluate the collection efficiency in line with the materials and the filter intervals, the optimal collection efficiency was investigated by combining two types of layer materials (stainless and acrylic) and filter intervals (1-5 mm). The optimal conditions were as follows: The selective collection efficiency was found to be highest at 96.5% when the interval of the selective target filter was 2.0 mm and there was one upper filter.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.229-238
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• 2009

This paper describes a sound engine of Korean traditional instruments, which are the Gayageum and Taepyeongso, by using a TMS320F2812. The Gayageum and Taepyeongso models based on commuted waveguide synthesis (CWS) are required to synthesize each sound. There is an instrument selection button to choose one of instruments in the proposed sound engine, and thus a corresponding sound is produced by the relative model at every certain time. Every synthesized sound sample is transmitted to a DAC (TLV5638) using SPI communication, and it is played through a speaker via an audio interface. The length of the delay line determines a fundamental frequency of a desired sound. In order to determine the length of the delay line, it is needed that the time for synthesizing a sound sample should be checked by using a GPIO. It takes $28.6{\mu}s$ for the Gayageum and $21{\mu}s$ for the Taepyeongso, respectively. It happens that each sound sample is synthesized and transferred to the DAC in an interrupt service routine (ISR) of the proposed sound engine. A timer of the TMS320F2812 has four events for generating interrupts. In this paper, the interrupt is happened by using the period matching event of it, and the ISR is called whenever the interrupt happens, $60{\mu}s$. Compared to original sounds with their spectra, the results are good enough to represent timbres of instruments except 'Mu, Hwang, Tae, Joong' of the Taepyeongso. Moreover, only one sound is produced when playing the Taepyeongso and it takes $21{\mu}s$ for the real-time playing. In the case of the Gayageum, players usually use their two fingers (thumb and middle finger or thumb and index finger), so it takes $57.2{\mu}s$ for the real-time playing.

• Journal of the Korean Society of Earth Science Education
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• v.17 no.1
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• pp.34-48
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• 2024

With the global rise in interest in competency-based education, the Ministry of Education of the Republic of Korea outlined six core competencies in the 2015 revised curriculum, essential for future society's 'creative and convergent talent'. This study introduces an HTE-STEAM constellation education program designed to develop the core competencies outlined in the 2015 revised curriculum and address the limitations of hands-on astronomy education. The program's effectiveness was assessed through a pilot test. The program was implemented at G Library, an out-of-school education site in Cheongju-si, Chungcheongbuk-do, targeting students from 3rd to 6th grade. The study's results include: First, the HTE-STEAM program significantly impacted all aspects of the STEAM attitude test except for 'self-concept', particularly influencing 'science and engineering career choice', 'consideration', and 'communication'. Thus, it has led to positive outcomes in the cultivation of future society's core competencies, including 'creative thinking skills', 'communication skills', and 'community skills'. Secondly, the HTE-STEAM constellation education program, despite covering the challenging concept of spacetime, was deemed easy by many students. Observations of students applying the spatial concepts they learned by using teaching aids suggest that the program was effective in enhancing students' understanding of the spatial structure of the sky and the universe. Additionally, this program aligns with the 2022 curriculum's updated standards for understanding the sky's spatial structure. Consequently, the HTE-STEAM constellation education program positively cultivates future society's core competencies and serves as a valuable complement to night observation practices in schools.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.149-158
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• 2024

Photo booths have traditionally provided a fun and easy way to capture and print photos to cherish memories. These booths allow individuals to capture their desired poses and props, sharing memories with friends and family. To enable diverse expressions, generative AI-powered photo booths have emerged. However, existing AI photo booths face challenges such as difficulty in taking group photos, inability to accurately reflect user's poses, and the challenge of applying different concepts to individual subjects. To tackle these issues, we present CINEMAPIC, a photo booth system that allows users to freely choose poses, positions, and concepts for their photos. The system workflow includes three main steps: pre-processing, generation, and post-processing to apply individualized concepts. To produce high-quality group photos, the system generates a transparent image for each character and enhances the backdrop-composited image through a small number of denoising steps. The workflow is accelerated by applying an optimized diffusion model and GPU parallelization. The system was implemented as a prototype, and its effectiveness was validated through a user study and a large-scale pilot operation involving approximately 400 users. The results showed a significant preference for the proposed system over existing methods, confirming its potential for real-world photo booth applications. The proposed CINEMAPIC photo booth is expected to lead the way in a more creative and differentiated market, with potential for widespread application in various fields.