• Anatomy and Cell Biology
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• v.56 no.1
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• pp.86-93
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• 2023

Age at death estimation has always been a crucial yet challenging part of identification process in forensic field. The use of human skeletons have long been explored using the principle of macro and micro-architecture change in correlation with increasing age. The clavicle is recommended as the best candidate for accurate age estimation because of its accessibility, time to maturation and minimal effect from weight. Our study applies pre-trained convolutional neural network in order to achieve the most accurate and cost effective age estimation model using clavicular bone. The total of 988 clavicles of Thai population with known age and sex were radiographed using Kodak 9000 Extra-oral Imaging System. The radiographs then went through preprocessing protocol which include region of interest selection and quality assessment. Additional samples were generated using generative adversarial network. The total clavicular images used in this study were 3,999 which were then separated into training and test set, and the test set were subsequently categorized into 7 age groups. GoogLeNet was modified at two layers and fine tuned the parameters. The highest validation accuracy was 89.02% but the test set achieved only 30% accuracy. Our results show that the use of medial clavicular radiographs has a potential in the field of age at death estimation, thus, further study is recommended.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.83-88
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• 2024

In this research, we propose a Semi-Supervised learning based railroad surface defect detection method. The Resnet50 model, pretrained on ImageNet, was employed for the training. Data without labels are randomly selected, and then labeled to train the ResNet50 model. The trained model is used to predict the results of the remaining unlabeled training data. The predicted values exceeding a certain threshold are selected, sorted in descending order, and added to the training data. Pseudo-labeling is performed based on the class with the highest probability during this process. An experiment was conducted to assess the overall class classification performance based on the initial number of labeled data. The results showed an accuracy of 98% at best with less than 10% labeled training data compared to the overall training data.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.10-20
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• 2024

As the online commerce market continues to expand with an increase of diverse products and content, users find it challenging in navigating and in the selection process. Thereafter both platforms and shopping malls are actively working in conducting continuous research on recommendations system to select and present products that align with user preferences. Most existing recommendation studies have relied on user data which is relatively easy to obtain. However, these studies only use a single type of event and their reliance on time dependent data results in issues with reliability and complexity. To address these challenges, this paper proposes a recommendation system that analysis user preferences in consideration of the relationship between various types of event data. The proposed recommendation system analyzes the correlation of multiple events, extracts weights, learns the recommendation model, and provides recommendation services through it. Through extensive experiments the performance of our system was compared with the previously studied algorithms. The results confirmed an improvement in both complexity and performance.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.4
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• pp.59-76
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• 2023

The COVID-19 pandemic has brought about environmental severity and new social, economic, and cultural changes. Conscious fashion, which is oriented to sustainable and valuable consumption, has become a trend to consume products produced using eco-friendly and ethical processes, from the selection of the product materials to the manufacturing process. The purpose of this study is to identify the concepts and characteristics of conscious fashion and zero waste, and to explore design trends of zero wastein the new normal era of conscious fashion through the analysis of various cases. The research method is a literature review on conscious fashion based on relevant professional and academic books and articles, designer collections, and campaigns from 2010 to the present, when conscious fashion as eco-friendliness and sustainable fashion became a trend. The concept and characteristics of conscious fashion were examined them in terms of environmental, ethical, social, and cultural aspects and the concept and characteristics of zero waste through previous studies and case analysis. Through this, the trends of zero-waste design in conscious fashion were categorized into: first, an eco-friendly design orientation that utilizes reuse and reduce methods of clothing and fabric; second, a variable design orientation that practices zero waste designs by using diversity of patterns through deconstruction, disassembly, and various cutting methods. Third, long-term circulation of design through the recycling of resources by second-hand trade, the utilization of stock clothing, resale, and availability of eco-friendly materials through the development of new technologies. As an active practice for the sustainable fashion industry expands, it is expected that continuous research will be conducted as a future core value to realize the possibility of long-term circular zero-waste design through social responsibility and conscious recycling, reuse, and reproduction.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.77-93
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• 2024

Purpose: The purpose of this study is to examine machine learning use cases in manufacturing companies from a digital quality management (DQM) perspective and to analyze and present machine learning research patterns from a quality management perspective. Methods: This study was conducted based on systematic literature review methodology. A comprehensive and systematic review was conducted on manufacturing papers covering the overall quality management process from 2015 to 2022. A total of 3 research questions were established according to the goal of the study, and a total of 5 literature selection criteria were set, based on which approximately 110 research papers were selected. Based on the selected papers, machine learning research patterns according to quality management were analyzed. Results: The results of this study are as follows. Among quality management activities, it can be seen that research on the use of machine learning technology is being most actively conducted in relation to quality defect analysis. It suggests that research on the use of NN-based algorithms is taking place most actively compared to other machine learning methods across quality management activities. Lastly, this study suggests that the unique characteristics of each machine learning algorithm should be considered for efficient and effective quality management in the manufacturing industry. Conclusion: This study is significant in that it presents machine learning research trends from an industrial perspective from a digital quality management perspective and lays the foundation for presenting optimal machine learning algorithms in future quality management activities.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.155-164
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• 2024

This study examines whether startup firms start with the resources they already have and expand the resources they can mobilize in the process of business management (Effectuation Model) using public data provided by the government. The results of the study show that the Effectuation Model can partially explain the behavior of early-stage startup firms. Therefore, in terms of policy implications based on these findings, government policies for entrepreneurship should not be based on the selection of companies based on sophisticated business models and hypothetical profit models, but rather on a system that actively supports entrepreneurship in areas that are challenging, even if they seem somewhat reckless at the moment, or that best match the entrepreneur's knowledge. Next, in order to actively spread entrepreneurship, it is necessary to spread business history or entrepreneurial experience. To this end, it is necessary to drastically change the current financial system for startups, where the founder bears all the financial risk, and to more actively consider ways to reduce the risk of startups by allowing society and the financial system to share some of the risk of startups.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.359-370
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• 2024

Special judicial police officer are exercising their right to investigate areas that require expertise that is difficult for ordinary police to investigate. The fire special judicial policer are also like this, and since they investigate the specialized field of fire offenders, they require not only expertise in the firefighting field but also professional capabilities in the investigation. To achieve this, there must be improvements in the selection process for fire and special judicial police officers to secure excellent investigative personnel. There is a lack of educational facilities and training content that can systematically educate selected investigative personnel and strengthen their expertise, so improvements are needed. must also be done. Laws on controversial areas surrounding the fire and special judicial police must be reorganized and poor investigative conditions must be improved so that the fire and special judicial policer can properly perform their role.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.123-134
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• 2006

In this study ship collision risk analysis is performed to determine the design vessel for collision impact analysis of the maritime bridge. Method II which is a probability based analysis procedure is used to select the design vessel for collision impact from the risk analysis results. The analysis procedure, an iterative process in which a computed annual frequency of collapse(AF) is compared to the acceptance criterion, includes allocation method of acceptance criterion of annual frequency of bridge component collapse. The AF allocation by weights seems to be more reasonable than the pylon concentration allocation method because this AF allocation takes the design parameter characteristics quantitatively into consideration although the pylon concentration allocation method brings more economical results when the overestimated design collision strength of piers compared to the strength of pylon is moderately modified. From the assessment of ship collision risk for each bridge pier exposed to ship collision, a representative design vessel for all bridge components is selected. The design vessel size varies much from each other in the same bridge structure depending upon the vessel traffic characteristics.

• Korean Journal of Veterinary Research
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• v.64 no.3
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• pp.24.1-24.8
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• 2024

A university's admission policy is established to select applicants who can successfully complete the curriculum. Thus, it is important to develop optimal admissions processes for applicant selection. This study was conducted to infer the most suitable admission processes for veterinary school applicants by examining academic achievement, graduation competency and academic sustainability. It was conducted on students admitted from 2009 to 2018 at one of the veterinary colleges in Korea. The admission methods were divided into, first the regular admission (RA) process, primarily reflecting the results of the College Scholastic Ability Test, and second, the rolling admission processes. The rolling processes were further divided into admission officer-based (AO), high school grade point average-based (GA), essay test-based (ET), admission for the underprivileged (UP) and admission for overseas Koreans and foreigners (OKF). The final grade point average was observed to be higher in the order of the GA, AO and RA groups. The survey on the veterinary graduation competency did not reveal any difference between the regular and rolling admission processes. However, among the latter, AO-based admission showed a higher ratio of outstanding competency levels. In terms of academic sustainability, OKF admission demonstrated a higher rate of failure while RA showed a higher rate of expulsion and dropout. Summarizing the above results, the most successful veterinary applicants were selected through AO-based admission. These results are meaningful in providing the basic information required to establish admission policies for veterinary colleges in Korea.