• Journal of Powder Materials
• /
• v.23 no.4
• /
• pp.325-330
• /
• 2016

Owing to increasing demand of rare metals present in ICT products, it is necessary to promote the rare metal recycling industry from an environmental viewpoint and to prevent climate change. Despite the fact that information for toxic substances is partly indicated, a legal basis and an international standard indicating usage of rare metals is insufficient. In order to address this issue, a newly created study group of environment and climate change at the ITU (International Telecommunication Union) is doing research to develop methodologies for recycling rare metals from ICT products in an eco-friendly way. Under this group, the Republic of Korea has established two international standards related to rare metals present in ICT products. The first is 'Release of rare metal information for ICT products (ITU-T L.1100)' and the other is 'Quantitative and qualitative analysis methods for rare metals (ITU-T L.1101)'. A new proposal for recommending the provision of rare metal information through a label by manufacturers and consumer/recycling businesses has been approved recently and is supposed to be published later in 2016. Moreover, these recommendations are also being extended to IEC, ISO and other standardization organizations and a strategy to reinforce the ability for domestic standardization is being established in accordance with industrial requirements. This will promote efficient recycling of rare metals from ICT products and will help improve the domestic supply of rare metals.

• Journal of Internet Computing and Services
• /
• v.24 no.4
• /
• pp.85-92
• /
• 2023

Deep learning applications are increasingly being leveraged for disease detection tasks in medical imaging modalities such as X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). Most data-centric deep learning challenges necessitate the use of supervised learning methodologies to attain high accuracy and to facilitate performance evaluation through comparison with the ground truth. Supervised learning mandates a substantial amount of image and label sets, however, procuring an adequate volume of medical imaging data for training is a formidable task. Various data augmentation strategies can mitigate the underfitting issue inherent in supervised learning-based models that are trained on limited medical image and label sets. This research investigates the enhancement of a deep learning-based rib fracture segmentation model and the efficacy of data augmentation techniques such as left-right flipping, rotation, and scaling. Augmented dataset with L/R flipping and rotations(30°, 60°) increased model performance, however, dataset with rotation(90°) and ⨯0.5 rescaling decreased model performance. This indicates the usage of appropriate data augmentation methods depending on datasets and tasks.

• Composites Research
• /
• v.37 no.1
• /
• pp.21-31
• /
• 2024

This review paper investigates the use of shockwave attenuating materials within composite structures to enhance personnel protection against blast-induced traumatic brain injury (bTBI). This paper also introduces experimental methodologies exploited in the generation and measurement of shockwaves to evaluate the performance of the shock dissipating composites. The generation of shockwaves is elucidated through diverse approaches such as high-energy explosives, shock tubes, lasers, and laser-flyer techniques. Evaluation of shockwave propagation and attenuation involves the utilization of cutting-edge techniques, including piezoelectric, interferometer, electromagnetic induction, and streak camera methods. This paper investigates phase-separated materials, including polyurea and ionic liquids, and provides insight into composite structures in the quest for shockwave pressure attenuation. By synthesizing and analyzing the findings from these experimental approaches, this review aims to contribute valuable insights to the advancement of protective measures against blast-induced traumatic brain injuries.

• Korean Institute of Interior Design Journal
• /
• v.22 no.3
• /
• pp.145-153
• /
• 2013

Since a government design department office was set up in 2007, active design projects have been implemented. With this opportunity, each local self-governing organization has improved its administration and institutions, and are planning intensive research on public design for efficient execution of public design projects. However, recent public design projects have caused many problems due to unspecialized design processes, a lack of cooperation with relevant organizations, and unsatisfactory management systems after projects. Therefore, to overcome such problems in the execution of public design projects, a procedure-centered model should be developed. This study aims to analyse the process structures for the strategic execution of public design projects, and the methods and content of the execution process. For this purpose, this study looked into the process structures of public design projects based on design management strategies in order to draw suggestions needed for the execution process through advanced cases. The study is summed up as follows: First, when the process of public design projects was examined in terms of management strategies and design management strategies, it included two dimensions: the management structure of general projects and the design of development projects. Secondly, through the analysis of public design cases, this study discovered useful methodologies and the main programs used and drew suggestions needed for each step in public design projects. It is expected that the results of this study will be helpful for the development of a process model appropriate for national public design projects based on the current status of the project execution and to make a contribution to systematic development in national public design.

• Journal of Industrial Convergence
• /
• v.22 no.8
• /
• pp.19-28
• /
• 2024

This study proposes a new method for predicting the wage grades of soccer players using big data and artificial intelligence. Predicting the salaries of soccer players is a crucial task that involves accurately assessing players' performance and potential, and reflecting this in their salaries to enhance the economic efficiency of the soccer industry. This research analyzes player ability data provided by FIFA 22 and employs various big data and artificial intelligence techniques to predict players' salary grades. Key methodologies used include decision trees, artificial neural networks, random forests, and boosting, which were utilized to compare the accuracy of the salary prediction models. The results show that the random forest and boosting methods exhibited the highest prediction accuracy. This study demonstrates the process and utility of using big data and artificial intelligence technologies to predict soccer players' salary grades, offering a new perspective on the soccer industry.

• Journal of Intelligence and Information Systems
• /
• v.15 no.3
• /
• pp.31-51
• /
• 2009

Research on how to develop information systems efficiently and effectively since early 1960s has resulted in many techniques, methods and methodologies. Only a few of them, however, have been successfully practiced in the field. Model-Driven Development(MDD) is an innovative approach emphasizing the central role of model for development activities, attracting many practitioners' attention as well as researchers'. As MDD matures, many researchers have been trying to establish the evidence of its effectiveness. But many of them only suggest lessons learned or report limited evidence of effectiveness based on isolated case studies. This paper reports the state of the art of Model-Driven Engineering(MDE) and its major issues. We reviewed a number of papers and collected the conceptual definitions of MDE effectiveness from the technological and organizational perspectives. A case study in which MDD technology was adopted has been performed in order to measure the effectiveness of MDD quantitatively and qualitatively. This paper also analyzes and summarizes key considerations and lessons learned for IT organizations to adopt MDE successfully from the case study.

• Korean Journal of Health Education and Promotion
• /
• v.29 no.3
• /
• pp.53-61
• /
• 2012

Objectives: Improving public capability to obtain, understand, and use health information is important for decision-making and communication. This study attempts to measure adults' literacy of the information provided by a public health institution. Factors affecting different health literacy level are also investigated. The relation between public risk perception and health literacy is examined as well. Methods: A total of 800 korean adults were surveyed. To provide the participants health literacy questions, health messages of heavy metals released by KFDA as well as literacy questions developed by NIKL were used. A total of eight questions were developed to measure health literacy. The dimensions of risk perception proposed by Brewer et al.(2008) were modified to measure risk perception. Results: The average percentage of correct answer for all literacy questions was only 65.57%. Individuals at the older age, and with lower education/ income level were more likely to be low literate. In addition, health literacy was strongly associated with risk perception. Conclusions: Public literacy of health information is influenced by socio demographic factors. This study suggested a possibility that low health literacy may affect unrealistically high risk perception. Further studies with sophisticated methodologies to measure health literacy need to be developed.

• Journal of Digital Convergence
• /
• v.19 no.8
• /
• pp.219-224
• /
• 2021

The convergence of various industries has removed the boundaries of software application fields and reduced the restrictions on convergence fields. Software requirements are diversified and they want to reconfigure software requirements in a fast cycle. Since various changes in requirements have to be accepted technically, research on methodologies and standards to increase the efficiency of software productivity and methods for standardizing and producing software are needed. In this study, we studied how the reusability and complexity of the software asset reconfiguration system appeared according to the developer's characteristics and environment to utilize the assets optimized in previous studies. At this time, we measured how the change in complexity according to the usability and asset composition method that appears according to the developer's characteristics appears, but there is a limit to the collected data, so it is necessary to secure the quality of the measured value through continuous data collection. In addition, an intelligent system application plan is needed to supplement the problem of context classification in the use stage of complex assets.

• Journal of The Korean Society of Integrative Medicine
• /
• v.11 no.4
• /
• pp.177-188
• /
• 2023

Purpose : To identify trends in studies on the intersection of neurofeedback (NF) training and rehabilitation interventions for patients with stroke, as conducted over the past decade. Methods : This review included studies published from 2012 to 2022. A comprehensive database search was conducted using keywords such as "stroke", "electroencephalogram (EEG)", "brain wave", "nerve feedback", and "upper extremity function". Results : A total of 703 studies were initially retrieved. Of these, literature predating 2012, duplicate literature, non-experimental studies, and studies that did not target patients with stroke were excluded. After this screening, we retrieved the full texts of 15 articles and re-checked whether each study met the inclusion criteria of this study. The advisory members who participated in this study consisted of people with doctoral degrees and more than 5 years of clinical experience related to the rehabilitation of patients with stroke. Disagreements were resolved through discussions. Ultimately, 8 papers met the inclusion criteria and were included in the final analysis. Despite differences in the type and duration of NF training, the combination of NF training and rehabilitation intervention was found to be effective in promoting the functional recovery of the upper extremities, eliciting positive EEG changes, and inducing neurological changes in the brain. Conclusion : A meta-analysis involving a wider search range is needed in future studies. In addition, efforts are required to generalize the clinical application of these interventions. This can be achieved by supplementing the research methodologies through extensive review studies that encompass a diverse array of study designs.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 1997.05a
• /
• pp.8-11
• /
• 1997

Current methods of evaluating soil contamination by heavy metals rely on analyzing samples for total contents of metals or quantities recovered in various chemical extracting solutions. Results from these approaches provide only an index for evaluation because these methodologies yield values not directly related to bioavailability of soil-borne metals. In addition, even though concentrations of metals may be less than those required to cause toxic effects to biota, they may cause substantial effects on soil chemical parameters that determine soil quality and sustainable productivity. The objective of this research was to characterize effects of Cu or Cd additions on soil solution chemistry of soil quality indices, such as pH, EC, nutrient cation distribution and quantity/intensity relations (buffer capacity). Metals were added at rates ranging from 0 to 400 mg/kg of soil. Soil solution was sequentially extracted from saturated pastes using vacuum. Concentrations of Cu or Cd remaining in soil solutions were very low as compared to those added to the soils, warranting that most of the added metals were recovered as nonavailable (strongly adsorbed) fractions. Adsorption of the added metals released cations into soil solution causing increases of soluble cation contents and thus ionic strength of soil solution. At metal additions of 200~400 mg/kg, EC of soil solution increased to as much as 2~4 dS/m; salinity levels considered high enough to cause detrimental effects on plant production. More divalent cations (Ca+Mg) than monovalent cations (K+Na) were exchanged by Cu or Cd adsorption. The loss of exchangeable nutrient cations decreased long-term nutrient supplying capacity or each soil. At 100 mg/kg or metal loading, the buffering capacity was decreased by 60%. pH of soil solution decreased linearly with increasing metal loading rates, with a decrement of up to 1.3 units at 400 mg Cu/kg addition. Influences of Cu on each of these soil quality parameters were consistently greater than those of Cd. These effects were of a detrimental nature and large enough in most cases to significantly impact soil productivity. It is clear that new protocols are needed for evaluating potential effects of heavy metal loading of soils.