• The Research Journal of the Costume Culture
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• v.31 no.3
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• pp.330-345
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• 2023

This study aimed to categorize consumers using super app functional characteristics to identify demographic differences, and analyze shopping orientations by consumer type. This data can be used by fashion and beauty companies for product planning and marketing strategies. To categorize super app consumers, data were analyzed with SPSS v.26.0 software using frequency, factor, reliability K-mean cluster, and distributed analyses, one-way-ANOVAs, and Scheffe verification. Cross-analysis was conducted to correlate super app consumer types with demographic characteristics. One-way-ANOVAs and Scheffe verification were used to analyze the differences in shopping preferences between super app consumer groups. As a result of our analyses, super app consumers were classified into four types: the ration type, the low-use type, the multifunction type, and the habit type. There were statistically significant differences between these types in age, occupation, marital status, average monthly household income, and shopping impact factors. Five super app user shopping orientations were identified: brand pursuit, pleasure pursuit, trend pursuit, risk perception, and economic orientation. The differences in the preferred orientation between super app consumer types were found to be statistically significant. The majority of respondents were multifunction type consumers. This group used the super app most frequently and effectively. They also demonstrated the highest scores for all five of the shopping orientations. The classification of consumer types in this study will allow the fashion and beauty industries to utilize super apps for more targeted product design and marketing.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.305-305
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• 2022

A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.216-218
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• 2022

Natural disasters caused by abnormal climates are continuously increasing, and the types of natural disasters that cause the most damage are flood damage caused by heavy rains and typhoons. Therefore, in order to reduce flood damage, this paper proposes a system that can predict the water level, a major parameter of flood, in real time using LSTM and GRU. The input data used for flood prediction are upstream and downstream water levels, temperature, humidity, and precipitation, and real-time prediction is performed through the pre-trained LSTM-GRU model. The input data uses data from the past 20 hours to predict the water level for the next 3 hours. Through the system proposed in this paper, if the risk determination function can be added and an evacuation order can be issued to the people exposed to the flood, it is thought that a lot of damage caused by the flood can be reduced.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.467-474
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• 2013

Construction contactors must continuously seek to improve their cash flows, which reside at the heart of their financial success. They require careful planning, analysis, and optimization to avoid the risk of bankruptcy, remain profitable, and secure long-term growth. Sources of cash include bank loans and retained earnings, which are conceptually similar in that they both incur a cost of capital. Financial management therefore requires accurate yet customizable modeling capabilities that can quantify all expenses, including said cost of capital. However, currently existing cash flow models in construction engineering and management have strongly simplified the manner in which interest is assessed, which may even lead to overstating it at a disadvantage to contractors. The variable nature of cash balances, especially in the early phases of construction projects, contribute to this challenging issue. This research therefore extends a new cash flow model with an accurate interest calculation. It utilizes singularity functions, so called because of their ability to flexibly model changes across any number of different ranges. The interest function is continuous for activity costs of any duration and allows the realistic case that activities may begin between integer time periods, which are often calendar months. Such fractional interest calculation has hitherto been lacking from the literature. It also provides insights into the self-referential behavior of compound interest for variable cash balances. The contribution of this study is twofold; augmenting the corpus of financial analysis theory with a new interest formula, whose strengths include its generic nature and that it can be evaluated at any fractional value of time, and providing construction managers with a tool to help improve and fine-tune the financial performance of their projects.

• Journal of Digestive Cancer Research
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• v.4 no.1
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• pp.21-28
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• 2016

Hepatocellular carcinoma (HCC) is rather unique. Most of HCC patients have underlying chronic liver diseases with or without cirrhosis and the prognosis of HCC depends on the liver function, as well as the tumor extent. Non-invasive diagnosis of HCC can be made with certain risk factors and specific imaging findings (e.g. hypervascularity). Patients with HCC can receive surgical resection, radiotherapy, and systemic chemotherapy as other solid malignancies. HCC has more treatment options such as liver transplantation, transarterial chemoembolization (TACE) and radiofrequency ablation (RFA). A variety of practice guidelines for HCC has been published by many academic societies. Different healthcare systems and availability of resources also affect the practice guidelines; therefore, practice guidelines have similarities and dissimilarities. Herein, we review the current status of practice guidelines for HCC and future perspectives for the improvement of guidelines are also discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.1-14
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• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.55-55
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• 2023

With the COVID-19 pandemic, there is increasing interest in anti-obesity strategies. According to the National Statistical Office, the obesity rate in Korea was 38.3% in 2020 and 37.1% in 2021. Obesity is a risk factor for several severe diseases, including stroke, heart disease, type 2 diabetes, and certain types of cancer. Pinus rigida × Pinus taeda is a hybrid of Pinus rigida Mill and Pinus taeda Linn, and its cones are considered a by-product. Although previous studies have investigated their pharmacological effects on antioxidant activity and protection against oxidative DNA damage, few researchers have explored their potential as functional natural materials. Therefore, we evaluated the anti-obesity effects of the cone of ethyl acetate fraction of P. rigida × P. taeda (ERT), specifically its ability to inhibit lipid accumulation. Our analysis showed that ERT contains phytochemicals (catechin and caffeic acid) which are known to improve immune function and inhibit cell damage. ERT inhibited lipid droplet accumulation at the cellular levels through Oil Red O staining. Furthermore, ERT suppressed the expression of adipogenic transcription factors (PPARγ and CEBP/α) as well as downstream lipogenic target genes (FAS and SREBP-1) thereby inhibiting adipogenesis. ERT also down-regulated key adipogenic markers, including aP2α, while inducing the phosphorylation of AMPK. It has been reported that PPARγ and CEBP/α are expressed in the early stages of adipose differentiation, while SREBP-1 is expressed in the late stage. Therefore, our findings suggest that ERT activates AMPK signaling pathways, which inhibits adipogenic transcription factors (PPARγ, C/EBPα, and SREBP1) and lipogenic genes (FAS and aP2α), thereby blocking lipid accumulation and preventing obesity and related disorders. ERT showed potential as a new resource for developing a functional material for anti-obesity agents.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.4
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• pp.109-119
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• 2023

PURPOSE: The definition and scope of biofeedback are broad and lack a clear framework. Therefore, efforts are needed to clearly understand the exact range and definition of biofeedback based on the research and development conducted to date. Thus, the purpose of this study was to arrive at the definition and scope of biofeedback through a literature review and analysis of its application methods. METHODS: This study is a systematic literature review conducted to understand the various types and effects of biofeedback. International databases such as Google Scholar and PubMed were used. Domestic databases utilized for keyword searches included the Research Information Sharing Service (RISS) and the National Digital Science Library (NDSL). Quality assessment of the selected studies in the selection process was done using the Cochrane risk of bias, and the research was analyzed according to the population, intervention, control, and outcomes (PICO) format. RESULTS: Studies conducted between 2019 and 2021 were selected, with 4 papers falling under physiological classifications and 7 under biomechanical classifications. The quality assessment results showed that random sequence generation, allocation concealment, performance bias, and reporting bias were unclear. Detection bias was moderate, and attrition bias and other biases were low. Out of the 11 papers, 9 dealt with physical function outcomes, 5 with daily life activities, and 3 with mental functions. CONCLUSION: Physiological biofeedback tended to influence psychological factors more than physical functions, while biomechanical biofeedback tended to have a positive impact on physical functions.

• The Journal of Internal Korean Medicine
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• v.44 no.6
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• pp.1118-1138
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• 2023

Objectives: Sarcopenia is an age-associated skeletal muscle disorder that can profoundly impact the health of elderly people. However, the efficacy of herbal medicine in sarcopenia is uncertain. This review aims to investigate evidence of the effect of herbal medicine on sarcopenia. Methods: We systematically searched 12 electronic databases for relevant randomized controlled trials (RCTs). Only trials that met the inclusion criteria were selected, and the characteristics of the included studies were extracted and synthesized in a narrative manner. The quality of the included studies was assessed using Cochrane's Risk of Bias (RoB) 2.0 tool. Results: 7 RCTs involving 672 participants with sarcopenia met the inclusion criteria. The intervention combining herbal medicine and conventional treatment (i.e., exercise, nutritional support) had a significant therapeutic effect compared with the conventional treatment, showing improvement in muscle strength (i.e., grip strength), muscle mass (i.e., appendicular skeletal muscle mass index), and physical function (i.e., gait speed, short physical performance battery, and timed up and go test). However, the methodological quality of the included RCTs was relatively low due to their high RoB, making it difficult to evaluate the efficacy of herbal medicine in sarcopenia. In terms of safety, several adverse events were reported. Conclusion: This review suggests that herbal medicine has a positive effect on muscle strength, muscle mass, and physical performance in elderly patients with sarcopenia, but there is a clear need for further research in this area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.348-369
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• 2024

With the advancement of Industry 4.0 and Industrial Internet of Things (IIoT), manufacturing increasingly seeks automation and intelligence. Temperature and vibration monitoring are essential for machinery health. Traditional abnormal state detection methodologies often overlook the intricate frequency characteristics inherent in vibration time series and are susceptible to erroneously reconstructing temperature abnormalities due to the highly similar waveforms. To address these limitations, we introduce synergistic, end-to-end, unsupervised Frequency-Time Domain Memory-Enhanced Autoencoders (FTD-MAE) capable of identifying abnormalities in both temperature and vibration datasets. This model is adept at accommodating time series with variable frequency complexities and mitigates the risk of overgeneralization. Initially, the frequency domain encoder processes the spectrogram generated through Short-Time Fourier Transform (STFT), while the time domain encoder interprets the raw time series. This results in two disparate sets of latent representations. Subsequently, these are subjected to a memory mechanism and a limiting function, which numerically constrain each memory term. These processed terms are then amalgamated to create two unified, novel representations that the decoder leverages to produce reconstructed samples. Furthermore, the model employs Spectral Entropy to dynamically assess the frequency complexity of the time series, which, in turn, calibrates the weightage attributed to the loss functions of the individual branches, thereby generating definitive abnormal scores. Through extensive experiments, FTD-MAE achieved an average ACC and F1 of 0.9826 and 0.9808 on the CMHS and CWRU datasets, respectively. Compared to the best representative model, the ACC increased by 0.2114 and the F1 by 0.1876.