• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.32-48
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• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• Journal of the Korean Recycled Construction Resources Institute
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• v.12 no.1
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• pp.63-71
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• 2024

Through the development of construction technology, various construction projects such as redevelopment projects, undergrounding of roads, expansion of subways, and metro railways are being carried out. However, this has led to an increase in the number of construction projects in existing urban centers and neighborhoods, resulting in an increase in the number of damages and disputes between neighboring buildings and residents, as well as an increase in safety accidents due to the aging of existing buildings. In this study, digital data was applied to a graphics program to objectify the progress of cracks by comparing the creation of cracks and the increase in length and width through photographic images and presenting the degree of cracks numerically. Through the application of the program, the error caused by the subjective judgment of crack change, which was mentioned as a shortcoming of the existing field survey, was solved. It is expected that the program can be used universally in the building diagnosis process by improving its reliability if supplemented and improved in the process of use. As a follow-up study, it is necessary to apply the extraction algorithm of the digital graphic data program to calculate the length and width of the crack by itself without human intervention in the preprocessing work and to check the overall change of the building.

• Applied Chemistry for Engineering
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• v.35 no.3
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• pp.222-229
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• 2024

The use of low-toxic, hypoallergenic, and environmentally friendly natural pigments has increased. With growing interest in health, research on natural extracts containing beneficial substances for the human body is actively underway. In this study, natural pigments were extracted from sprout barley using a solvent extraction method and CCD-RSM was used to optimize the extraction process. The experiment's independent variables included extraction temperature, alcohol/ultra-pure volume ratio, and extraction time. The response variables were set to achieve a target chromaticity (L = 45, a = -35, b = 45), and to maximize DPPH radical scavenging activity evaluating the antioxidant capacity. The statistical significance of the main effect, interaction effect, and effect on the response value was evaluated and analyzed through the F and P values for the regression equation variables calculated using RSM optimization. Additionally, the reliability of the experiment was also confirmed through the P values of the probability plot graph. The extraction conditions for optimizing the four reaction values are 76.1 vol.% alcohol/ultra pure water volume ratio, an extraction temperature of 52.9 ℃ , and an extraction time of 49.6 min. Under these conditions, the theoretical values of the reaction values are L = 45.4, a = -36.8, and b = 45.0 DPPH radical scavenging activity = 30.9%. When the actual experiment was conducted under these optimal extraction conditions and analyzed, the measured values were L = 46.2, a = -36.1, and b = 48.2, and antioxidant capacity = 31.1% with an average error rate of 2.9%.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1295-1295
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• 2024

As extreme weather events such as heavy snowfall and typhoon become more frequent, climate change significantly impacts across various worldwide industries. With demands for dealing with this phenomenon, continuous achievements in safety diagnosis have been announced for large structures. Conversely, in agricultural infrastructures having lower risk to human life, there is lack of established safety diagnosis methods. However, considering expansion of high-value smart farm, the importance of plastic greenhouse cannot be overlooked. Therefore, this study aimed to develop on-site diagnosis technique for structural safety of steel structure greenhouse. To build an analysis model, we generated point cloud data of on-site greenhouse using a camera with LiDAR sensor. Subsequently, we extracted points corresponding to pipes using a pre-trained semantic segmentation model, achieving a pipe segmentation accuracy of 78.1%. These points were then converted into 3D frame model, with a location coordinate error of 5.4 cm for nine reference points, as measured by an on-site survey. In FEM structural analysis, nonlinearity of pipe connection was reflected. The loads were determined based on expected wind speed and snow depth in Korea. The structural safety of on-site model was diagnosed more vulnerable with 10.3% higher maximum axial stress, compared with standard model. Through this research, we expect the quantitative safety diagnosis of predicting greenhouse collapse risk. In addition, this technique will enable localized reinforcement strategies within the structure.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.4
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• pp.86-93
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• 2009

This study analyzes the systematic visual images and factors in and outside of the main courtyard in Byungsan-seowon. The results are as follows; In terms of space distribution, Ip-kyo-dang is located at an elevation of 85m and the distance to Byung-san is 365m. Byung-san with the mean gradient over $50^{\circ}$ looked so stiff, and the east side of that cliff is higher than west. In terms of the angle of elevation relationship between Man-dae-ru and Byung-san draw 10.5 degree and it suits with human scale. The D/H ratio of 1:3 makes the given place very spacious but the linear stiff shape of Byung-san may cause the feeling of closeness. The results of the visual image analysis of the main yard facing Byung-san is very positive with a score of 1.70 in openness, 1.78 in wideness, 1.96 in beauty, 1.96 in harmony for the spacious arrangement which overall, makes the seowon beautiful with many open spaces. There are 4 main implicated factors analyzed which are uniqueness, aesthetic, openness and nature. Out of the total variables, these factors' descriptive ability is 55.90% and the remaining 44.10% is error and peculiarities variables. The factor which contributed most to Byungsan-seowon's main yard's visual preference was the 'aesthetic' with B-values of 0.661 and 0.455 in the nature category.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Journal of the Korean Wood Science and Technology
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• v.34 no.4
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• pp.37-45
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• 2006

Recently, wood-framed houses has been built in the Korea for pension. Wood is good material for human healthy, while the construction lumbers are treated with preservative such as CCA (chromated copper arsenate), which contain some toxic elements for human body. However, if the waste woody biomass treated with various heavy metals, which has been collected from house construction or demolition, was fired in the field, and incinerated or landfilled after mass collection, such components will result in the toxic air pollutants in the burning or land fills, and spreaded into other areas. So the careful selection of wood and chemicals are required in advance for house construction, in particular, for environment-friendly housings. Therefore, this study was carried out to determine the content of toxic heavy metals in woody materials such as domestic hinoki and imported hemlock treated with CCA for housing materials, and the post-treated wood components such as organic fertilizer, sludge, dry-distilled charcoal and carbonized charcoal, to be returned finally into soil. The results are as follows. 1) The chemical analysis of toxic trace elements in various solid biomass required accurate control and management of laboratory environment, and reagents and water used, because of the error of data due to various foreign substances added in various processing and transporting steps. So a systematic analyzers was necessary to monitor the toxic pollutants of construction materials. 2) In particular, the biomass treated with industrial biological or thermal conditions such as sludge or charcoals was not fully dissolvable after third addition of $HNO_3$ and HF. 3) The natural woody materials such as organic fertilizer, sludge. and charcoals without any treatment of preservatives or heavy metal components were nontoxic in landfill because of the standard of organic fertilizers, even after thermal or biological treatments. 4) The CC A-treated wood for making the construction wood durable should not be landfilled, because of its higher contents of toxic metals than the criterion of organic fertilizer for agriculture or of natural environment. So the demolished waste should be treated separately from municipal wastes.

• Journal of the Korean Society of Radiology
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• v.11 no.7
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• pp.547-553
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• 2017

In the current medical field, lead is widely used as a radiation shield. However, the lead weight is very heavy, so wearing protective clothing such as apron is difficult to wear for long periods of time and there is a problem with the danger of lethal toxicity in humans. Recently, many studies have been conducted to develop substitute materials of lead to resolve these problems. As a substitute materials for lead, barium(Ba) and iodine(I) have excellent shielding ability. But, It has characteristics emitting characteristic X-rays from the energy area near 30 keV. For patients or radiation workers, shielding materials is often made into contact with the human body. Therefore, the characteristic X-rays generated by the shielding material are directly exposured in the human body, which increases the risk of increasing radiation absorbed dose. In this study, we have developed the FLUKA transport code, one of the most suitable elements of radiation transport codes, to remove the characteristic X-rays generated by barium or iodine. We have verified the reliability of the shielding fraction of the structure of the structure shielding by comparing with the MCPDX simulations conducted as a prior study. Using the MCNPX and FLUKA, the double layer shielding structures with the various thickness combination consisting of barium sulphate ($BaSO_4$) and bismuth oxide($Bi_2O_3$) are designed. The accuracy of the type shown in IEC 61331-1 was geometrically identical to the simulation. In addition, the transmission spectrum and absorbed dose of the shielding material for the successive x-rays of 120 kVp spectra were compared with lead. In results, $0.3mm-BaSO_4/0.3mm-Bi_2O_3$ and $0.1mm-BaSO_4/0.5mm-Bi_2O_3$ structures have been absorbed in both 33 keV and 37 keV characteristic X-rays. In addition, for high-energy X-rays greater than 90 keV, the shielding efficiency was shown close to lead. Also, the transport code of the FLUKA's photon transport code was showed cut-off on low-energy X-rays(below 33keV) and is limited to computerized X-rays of the low-energy X-rays. But, In high-energy areas above 40 keV, the relative error with MCNPX was found to be highly reliable within 6 %.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.59-70
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• 2018

With the breakthrough of speech recognition technology, conversational agents have become pervasive through smartphones and smart speakers. The recognition accuracy of speech recognition technology has developed to the level of human beings, but it still shows limitations on understanding the underlying meaning or intention of words, or understanding long conversation. Accordingly, the users experience various errors when interacting with the conversational agents, which may negatively affect the user experience. In addition, in the case of smart speakers with a voice as the main interface, the lack of feedback on system and transparency was reported as the main issue when the users using. Therefore, there is a strong need for research on how users can better understand the capability of the conversational agents and mitigate negative emotions in error situations. In this study, we applied social strategies, "forewarning" and "apology", to conversational agent and investigated how these strategies affect users' perceptions of the agent in breakdown situations. For the study, we created a series of demo videos of a user interacting with a conversational agent. After watching the demo videos, the participants were asked to evaluate how they liked and trusted the agent through an online survey. A total of 104 respondents were analyzed and found to be contrary to our expectation based on the literature study. The result showed that forewarning gave a negative impression to the user, especially the reliability of the agent. Also, apology in a breakdown situation did not affect the users' perceptions. In the following in-depth interviews, participants explained that they perceived the smart speaker as a machine rather than a human-like object, and for this reason, the social strategies did not work. These results show that the social strategies should be applied according to the perceptions that user has toward agents.

• Radiation Oncology Journal
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• v.16 no.3
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• pp.325-335
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• 1998

Purpose : Since the mid cranial fossa is composed of various thickness of bone, the tissue inhomogeneity caused by bone would produce dose attenuation in cobalt-60 gamma knife irradiation. The correction factor for bone attenuation of cobalt-60 which is used for gamma knife source is -3.5$\%$. More importantly, nearly all the radiosurgery treatment planning systems assume a treatment volume of unit density: any perturbation due to tissue inhomogeneity is neglected, This study was performed to confirm the bone attenuation in mid cranial fossa using gamma knife. Materials and Methods : Computed tomography was performed after Leksell stereotactic frame had been liked to the Alderson Rando Phantom (human phantom) skull area. Kodak X-omat V film was inserted into two sites of pituitary adenoma point and acoustic neurinoma point, and irradiated by gamma knife with 14mm and 18mm collimator. An automatic scanning densitometer with a 1mm aperture is used to measure the dose profile along the x and y axis. Results : Isodose curve constriction in mid cranial fossa is observed with various ranges. Pituitary tumor point is greater than acoustic neurinoma point (0.2-3.0 mm vs 0.1-1.3 mm) and generally 14 mm collimator is greater than 18mm collimator (0.4-3.0 mm vs. 0.2-2.2 mm) Even though the isodose constriction is found, constriction of 50$\%$ isodose curve which is used for treatment reference line does not exceed 1 mm. This range is too small to influence the treatment planning and treatment results. Conclusion : Radiosurgery planning system of gamma knife does not show significant error to be corrected without consideration of bone attenuation.