• Dementia and Neurocognitive Disorders
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• v.21 no.4
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• pp.147-161
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• 2022

Background and Purpose: Subjective cognitive decline (SCD) refers to the self-perception of cognitive decline with normal performance on objective neuropsychological tests. SCD, which is the first help-seeking stage and the last stage before the clinical disease stage, can be considered to be the most appropriate time for prevention and treatment. This study aimed to compare characteristics between the amyloid positive and amyloid negative groups of SCD patients. Methods: A cohort study to identify predictors for the clinical progression to mild cognitive impairment (MCI) or dementia from subjective cognitive decline (CoSCo) study is a multicenter, prospective observational study conducted in the Republic of Korea. In total, 120 people aged 60 years or above who presented with a complaint of persistent cognitive decline were selected, and various risk factors were measured among these participants. Continuous variables were analyzed using the Wilcoxon rank-sum test, and categorical variables were analyzed using the χ² test or Fisher's exact test. Logistic regression models were used to assess the predictors of amyloid positivity. Results: The multivariate logistic regression model indicated that amyloid positivity on PET was related to a lack of hypertension, atrophy of the left temporal lateral and entorhinal cortex, low body mass index, low waist circumference, less body and visceral fat, fast gait speed, and the presence of the apolipoprotein E ε4 allele in amnestic SCD patients. Conclusions: The CoSCo study is still in progress, and the authors aim to identify the risk factors that are related to the progression of MCI or dementia in amnestic SCD patients through a two-year follow-up longitudinal study.

• Journal of Korea Port Economic Association
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• v.40 no.2
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• pp.191-204
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• 2024

In this study, AHP-based production management job training was developed for MPE companies in the aviation logistics industry. The AHP model was designed with upper and lower classes. Purchase management competency, material management competency, process management competency, and SCM competency were selected as factors of the upper class of production management job training. Lower class evaluation factors were selected for each upper class. As a result of AHP analysis, the relative importance of the upper class evaluation factors was found in the order of SCM competency (0.322), process management competency (0.314), material management competency (0.201), and purchase management competency (0.163). Among the upper classes, it was analyzed that the importance of SCM competency and process management competency was high. The final priority of evaluation factors for the development of the production management curriculum of MPE companies in the aviation logistics industry was analyzed as follows. First, supply chain performance management, which is the lower layer of SCM competency, was analyzed as the top priority factor, and the priorities of evaluation factors were derived such as facility preservation management, which is the lower layer of SCM competency, supply chain production operation, which is the lower layer of SCM competency, process quality management, which is the lower layer of SCM competency, supply chain transportation management, and supply chain supply plan, which are the lower layers of SCM competency

• Journal of the Korea Institute of Building Construction
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• v.24 no.4
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• pp.447-458
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• 2024

This study investigates the effectiveness of Building Information Modeling(BIM) software, specifically SketchUp and Revit, in reducing errors during quantity take-off(QTO) for complex building elements. While 3D modeling offers advantages, existing software may not fully account for manufacturing discrepancies, such as variations in concrete cover thickness and reinforcing bar radius. To address this limitation, this research proposes a BIM-based QTO method for high-insulation wall panels with intricate details. The method utilizes a BIM family library, focusing on key parameters like concrete cover thickness and inner radius of shear reinforcement. A case study compared the cross-sectional details of a wall panel modeled in Revit with the actual manufactured specimen. The analysis revealed a 12% reduction in modeled concrete cover thickness and a 1.27 times larger modeled inner radius of the shear bar compared to the real-world values. The proposed method incorporates these manufacturing variations into the Revit model of the high-insulation wall panel. Software like Navisworks facilitates the identification and correction of any material interferences arising from these adjustments. Furthermore, the method employs a unit wall concept(1m²) to account for the volume of various materials, including insulation and splice sleeves at joints. This allows for the identification of a similar existing family within the BIM library(e.g., "Double RC wall with embedded insulation") that reflects the actual material quantities used in the wall panel. By incorporating these manufacturing-induced variations, the proposed method offers a more accurate QTO process for complex high-insulation wall panels. The "Double RC wall with embedded insulation" family within the Revit program serves as a valuable tool for material quantity estimation in such scenarios.

• Journal of Aerospace System Engineering
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• v.18 no.4
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• pp.81-88
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• 2024

The payload BioCabinet of CAS500-3 is designed for 3D stem cell differentiation, culture, and analysis utilizing bio 3D printing techniques in space. The 3D printing technique was initially developed for orbital use; however, it lacks separate validation for extreme launch vibration environments, necessitating a design that mitigates the launch load on the payload. This paper proposes a passive vibration isolator with a low-stiffness elastic support structure and high damping characteristics to reduce the launch loads affecting the BioCabinet. We explore the high-damping characteristics through the superelastic effects of SMA (Shape Memory Alloys) and a multi-layered structure incorporating viscoelastic tape. The effectiveness of the proposed vibration isolation system was confirmed via launch vibration tests on a qualification model.

• Information Systems Review
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• v.26 no.1
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• pp.73-91
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• 2024

Recently, e-learning platforms are rapidly growing by innovating the education industry by applying various IT technologies. Because student participation in the online environment is considered a prerequisite for learning, low participation rates are considered one of the most important issues determining the performance of e-learning platforms. Gamification has grown rapidly over the past decades and is highly valued for its applicability in education because it is expected to enhance learning motivation. However, despite the interest of researchers, previous studies have reported conflicting results on the effect of gamification on participation rates in the context of e-learning platforms, and have mainly studied structural gamification, but have not sufficiently addressed the effects of content gamification. In this context, this study aims to analyze the effect of content gamification on e-learning platform engagement and to explore the boundary conditions moderating this effect. For empirical analysis, 5,017 data registered from February 11, 2022 to May 31, 2022 were analyzed for the education platform entry (https://playentry.org). The propensity score matching method and Poisson multilevel regression model were applied as analysis methods. As a result of the analysis, content gamification had a statistically significant effect on engagement, and the interaction effects of interaction and content difficulty were statistically significant.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.287-297
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• 2024

The purpose of this study is to develop a design thinking-based program to enhance the core competencies of creative problem-solving, collaboration, and communication for college students and to verify its effectiveness. To this end, a design thinking-based program was developed according to the instructional systems design (ISD) model consisting of learning content analysis, class activity design, evaluation tool development, implementation, evaluation and revision. After applying to the target (88 college students), competencies in creative problem-solving, collaboration, and communication were tested to verify quantitative effectiveness and the collected data was analyzed by t-test. In order to verify the qualitative effectiveness, the reflective logs submitted by each group as a final project report were analyzed. The results of the t-test conducted to verify the change in students' means in the pre-post competency test, showed that there were statistically significant increase in creative problem solving skill (t=-4.955, p<.01), collaboration skill (t=-3.179, p<.01), and communication skills(t=- 4.293, p<.01). And the design thinking-based program enabled students to have optimal learning experiences. Especially, learners in the program positively appreciated the experience of sharing various ideas with other members, strengthening cognitive flexibility, and acquiring performance.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.119-138
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• 2016

Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.

• The Journal of Korean Society for School & Community Health Education
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• v.13 no.3
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• pp.57-71
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• 2012

Objectives: This study examines the situation regarding smoking among high school students in Seoul Province and identifies smoking-related factors. Methods: The study sample consisted of 1,000 high school second-grade students from 6 high schools in Seoul. The PRECEDE model was used to assess the students' needs. We carried out an educational diagnosis on attitudes, outcome expectations and social norms. Date were collected from June. 7 to 21, 2011, and were analyzed using SPSS-15.0 according to the study objectives. Results: Of 906 respondents, 9.4% had experiences to smoking: 12.7% were male and 5.7% were female. Smoking-related factors from among general characteristics were statistically significant depending on the degree of gender($x^2$=14.515, p=.001), school performance($x^2$=40.289, p=.001) and friends 'smoking status($x^2$=88.615, p=.001). Factors concerning attitudes toward smoking were statistically significant depending on the students' perceptions as follows: 'Smoking is fun(t=-14.801, p=.000)', 'Smoking looks cool(t=-10.349, p=.000)', 'People who smoke have more friends(t=-11.295, p=.000)', 'Smoking helps me manage stress(t=-15.059, p=.000)' and 'Smoking is not harmful to the body if you exercise(t=-6.388, p=.000)'. Factors concerning outcome expectations were statistically significant depending on their perceptions as follows: 'Tobacco smells good(t=-8.939, p=.000)' and 'Smoking helps in weight management (t=-7.304, p=.000)'. Factors concerning social norms were statistically significant depending on the following perception: 'My friends will not like it if I smoke(t=4.605, p=.000)'. The following influence high school students attitudes toward smoking: School performance (OR=11.66, 95%CI=1.67~81.37; OR=18.27, 95%CI=2.58~129.24; OR=26.74, 95%CI=3.06~233.79), Friends smoking status(OR=80.05, 95%CI=6.94~922.77), 'Smoking is fun(OR=12.90, 95%CI=3.87~43.04; OR=63.41, 95%CI=10.66~377.09)', 'Smoking looks cool(OR=0.15, 95%CI=0.03~0.64)', 'Smoking is not harmful to the body if you exercise(OR=1.44, 95%CI=0.03~0.62)', 'When there is no work to do, smoking is a good way to pass the time(OR=21.68, 95%CI=4.27~109.90)', 'When you are angry, smoking calms you down.(OR=13.39, 95%CI=3.92~45.65; OR=8.69, 95%CI=1.67~45.13)' and 'My parents consider it important that I do not smoke(OR=10.05, 95%CI=1.00~100.43)'. Conclusions: The study suggests that effective ways to discourage of high school students from smoking are changing their attitudes toward smoking, reducing the motivation to smoke, and controlling the number of cigarettes. Therefore, aiming at preventive education. Schools must provide accurate information about the effects of smoking. Thus, health education should actively involve preventive education not only in schools but also at home, the societal and national levels. Cooperation between various sectors of society is required for this.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.59-68
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• 1998

Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.