Recently, due to the increase in domestic and international online e-commerce platforms and the increase in container traffic at domestic ports, the operating ratio of large trucks has increased, and the number of truck fires is continuously increasing. In particular, spontaneous combustion is the most common cause of truck fires. Various academic approaches have been attempted to prevent truck fires, but due to the lack of research on the spontaneous tire ignition phenomenon that occurs during braking, this research directly designed and manufactured an experimental device to establish an environment similar to the braking system of a truck. A non-contact temperature sensor was installed on the brake device of the experimental device to collect temperature data generated from the brake device. Based on the data collected from the temperature sensor of the brake device and the temperature sensor on the tire surface, the ARIMA model among the time series prediction models was used to Appropriate parameters were selected to suit the temperature change trend, and as a result of comparing and analyzing the measured and predicted data, an accuracy of over 90% was obtained. Based on this, a plan was proposed to reduce the rate of fires in trucks by providing real-time warnings and support for truck drivers to respond to overheating phenomena occurring in the braking system.
Objective: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model. Materials and Methods: A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance. The mean absolute error (MAE), root mean square error (RMSE), and proportions of bone age predictions within 6, 12, 18, and 24 months of the reference age (chronological age) were compared between the Korean model and a commercial model (VUNO Med-BoneAge version 1.1; VUNO) trained with Greulich-Pyle-based age as the label (GP-based model). Results: Compared with the GP-based model, the Korean model showed a lower RMSE (11.2 vs. 13.8 months; P = 0.004) and MAE (8.2 vs. 10.5 months; P = 0.002), a higher proportion of bone age predictions within 18 months of chronological age (88.3% vs. 82.2%; P = 0.031) for Institution 1, and a lower MAE (9.5 vs. 11.0 months; P = 0.022) and higher proportion of bone age predictions within 6 months (44.5% vs. 36.4%; P = 0.044) for Institution 2. Conclusion: The Korean model trained using the chronological ages of Korean children and adolescents without known bone development-affecting diseases/conditions as labels performed better in bone age assessment than the GP-based model in the Korean pediatric population. Further validation is required to confirm its accuracy.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.24
no.2
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pp.167-175
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2024
Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.
The Journal of the Convergence on Culture Technology
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v.10
no.3
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pp.421-426
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2024
The Analytic Hierarchy Process (AHP) converts people's judgment criteria into objective numerical values using pairwise comparisons. However, the need for an excessive number of pairwise comparisons poses a problem. To mitigate this issue, most existing studies have utilized the process separation approach. The method of process separation devised in this study is a "separation and integration approach," where 1) the standard AHP process is used for evaluating judgment criteria, and 2) the Multi-Attributive Utility Technique (MAUT) is applied for comparing alternatives. This AHP-MAUT Hybrid model was applied to a real analysis case, specifically analyzing the transportation choices of commuters between Bundang and Gangnam Station in Gyeonggi Province. The results showed that the computational process was reduced by 42.03% when applying the Hybrid model compared to using the AHP model alone. Furthermore, the choice results of residents using the Hybrid model were compared with those using the standard AHP. The consistency between the two models' choices was 82.1%, indicating a significant level of consistency. In conclusion, this study contributes by presenting a simpler, more convenient, yet equally effective Hybrid model as a new decision-support system alternative to AHP.
In this study, we explored the feasibility of automatically scoring descriptive assessment items using GPT-4 based ChatGPT by comparing and analyzing the scoring results between teachers and GPT-4 based ChatGPT. For this purpose, three descriptive items from the permutation and combination unit for first-year high school students were selected from the KICE (Korea Institute for Curriculum and Evaluation) website. Items 1 and 2 had only one problem-solving strategy, while Item 3 had more than two strategies. Two teachers, each with over eight years of educational experience, graded answers from 204 students and compared these with the results from GPT-4 based ChatGPT. Various techniques such as Few-Shot-CoT, SC, structured, and Iteratively prompts were utilized to construct prompts for scoring, which were then inputted into GPT-4 based ChatGPT for scoring. The scoring results for Items 1 and 2 showed a strong correlation between the teachers' and GPT-4's scoring. For Item 3, which involved multiple problem-solving strategies, the student answers were first classified according to their strategies using prompts inputted into GPT-4 based ChatGPT. Following this classification, scoring prompts tailored to each type were applied and inputted into GPT-4 based ChatGPT for scoring, and these results also showed a strong correlation with the teachers' scoring. Through this, the potential for GPT-4 models utilizing prompt engineering to assist in teachers' scoring was confirmed, and the limitations of this study and directions for future research were presented.
Research was conducted on a PA material-based composite material manufacturing method for application to engine mount brackets. Engine mount brackets must have heat resistance, impact resistance, and damping performance. PA66 resin was used as the base material for the composite material. The glass fiber was used as the reinforcement material. The composite material was manufactured using the injection molding method. The thermal, mechanical, and morphological characteristics were analyzed depending on the content of glass fiber. 3D model was created using the property evaluation database of composite materials(input data). The damping performance of the generated 3D model was extracted as out-put data. The reason for evaluating the characteristics of PA-based composite materials and conducting simulations on the damping performance of 3D models of engine brackets is because product performance can be predicted without manufacturing actual automobile parts and conducting damping performance tests. As a result of the damping simulation, damping performance tended to increase proportionally as the mass fraction of the reinforcement increased. But above a certain level, it no longer increased and slightly decreased. As a result of comparing the actual experimental values a nd the simulated values, the approximate value was within ±5%.
To observe the change in the status of stresses according to three different postural angulation of an intervertebral disc with or without nucleus pulposus, 6 specimens of a 3-dimensional photoelastic model of the s pine were made of epoxy. The nucleus pulposus portion was replaced with silicon in three models, and the three were made without silicon. Through axial application of a vertical compressive load of 8kg, the peculiar patterns of the isochromatic fringes were observed. Stresses on the intervertebral disc were analyzed according to three different postural angulations of the intervertebral disc with the nucleus pulposus and without the nucleus pulposus. The results of these study are as follow : 1. In an erect neutral posture with the nucleus pulposus, the stress concentration was much increased at the posterior portion rather than at the anterior portion. Also, the high stress was concentrated at the medial and central portion. In an erect neutral posture without the nucleus pulposus, the stress concentration was much increased at the anterior portion rather than at the posterior portion and the stress distribution seemed to be locally concentrated. 2. In a maximal flexed posture, the stress concentration was much increased at the posterior portion rather than at the anterior portion. Comparing the presence of the nucleus pulposus with the absence of the nucleus pulposus, the stress concentration was lower at the anterior portion in the presence of the nucleus pulposus than in the absence of the nucleus pulposus. However, the stress distribution at the posterior portion was nearly same in the two groups. According to the analysis of the stress distribution diagram, as a whole, the stress pattern around the disc was evenly distributed. 3. In a maximal extended posture, the higher concentration of the stress distribution at the anterior and medial portion rather than in the posterior and lateral portion was observed. The stress concentration was higher in the presence of the nucleus pulposus than in the absence of the nucleus pulposus. 4. Comparing the maximal flexed posture with the erect neutral posture, the stress concentration in the flexed posture was much decreased in the posterior portion rather than in the erect neutral posture, and an even distribution of the stress pattern in the flexed posture was observed. 5. In the presence of the nucleus pulposus, at the anterior and posterior portion, the stress concentration in the flexed posture was much decreased compared with the extended posture. In the absence of the nucleus pulposus, at the anterior and posterior portion, the stress concentration in the extended posture was much decreased compared with the flexed posture.
This study aims to evaluate the accuracy of the collapsed cone convolution (CCC) algorithm for dose calculation in a treatment planning system (TPS), CorePLAN$^{TM}$. We implemented beam models for various setup conditions in TPS and calculated radiation dose using CCC algorithm for 6 MV and 15 MV photon beam in $50{\times}50{\times}50cm^3$ water phantom. Field sizes were $4{\times}4cm^2$, $6{\times}6cm^2$, $10{\times}10cm^2$, $20{\times}20cm^2$, $30{\times}30cm^2$ and $40{\times}40cm^2$ and each case was classified as open beam cases and wedged beam cases, respectively. Generated beam models were evaluated by comparing calculated data and measured data of percent depth dose (PDD) and lateral profile. As a result, PDD showed good agreement within approximately 2% in open beam cases and 3% in wedged beam cases except for build-up region and lateral profile also correspond within approximately 1% in field and 4% in penumbra region. On the other hand, the discrepancies were found approximately 4% in wedged beam cases. This study has demonstrated the accuracy of beam model-based CCC algorithm in CorePLAN$^{TM}$ and the most of results from this study were acceptable according to international standards. Although, the area with large dose difference shown in this study was not significant region in clinical field, the result of our study would open the possibility to apply CorePLAN$^{TM}$ into clinical field.
This study is designed to find out the determinants of dual-earner wives' needs for family-supportive services. For this purpose, a hypothetical model which explains the relationships among 6 stressors, role overload, stress and needs for 4 family-supportive services is developed. Using the data collected by purposive sampling from 234 professional women and 208 blue-collar women living in Chinju and Sacheon, the hypothetical model developed in this study was tested. In order to examine occupational class differences, a model for professionals and another model for blue-collars were developed separately and compared. For data analysis, a covariance structure analysis was used. The best-fitting model for professional women (df=141, GFI=0.928, CFI=0.965) and the model for blue collar women (df=141, GFI=0.902, CFI=0.912) were found. As a result of comparing two models, 9 common relationships were found:l)Greater dissatisfaction with child care service increases role overload; 2)Longer work hours increases role overload; 3) Higher level of role overload increases stress; 4)Higher level of stress increase needs for leaves; 5)Older child increases needs for flexible work pattern; 6)Younger child increases needs for finalcial assistance for child care fee; 7)needs for financial assistance for child care increases needs for on-site child care services; 8)needs for on-site child care services increases needs for leaves; 9)needs for leaves increases needs for flexible work pattern. With the exception of these 9 common relationships, the analyses revealed substantial differences between professional and blue-collar dual-earner wives. Based on the common and differential needs between 2 groups of wives, the effective ways to provide family-supportive services according to the needs of individual dual-earner wives who are in different familial, financial, and work conditions were suggested.
The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.
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