• Knowledge Management Research
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• v.23 no.1
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• pp.187-201
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• 2022

Online reviews written by tourists provide important information for the management and operation of the tourism industry. The star rating of online reviews is a simple quantitative evaluation of a product or service, but it is difficult to reflect the sincere attitude of tourists. There is also an issue; the star rating and review content are not matched. In this study, a star rating prediction model based on online review content was proposed to solve the discrepancy problem. We compared the differences in star ratings and sentiment by continent through sentiment analysis on tourist attractions and hotels written by foreign tourists who visited Korea. Variables were selected through TF-IDF vectorization and sentiment analysis results. Logit, artificial neural network, and SVM(Support Vector Machine) were used for the classification model, and artificial neural network and SVR(Support Vector regression) were applied for the rating prediction model. The online review rating prediction model proposed in this study could solve inconsistency problems and also could be applied even if when there is no star rating.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.85-94
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• 2022

Recently, consumers who prefer contactless consumption are increasing due to pandemic trends such as Corona 19. This is the driving force for developing the last mile-based logistics ecosystem centered on the online e-commerce market. Lastmile led to the continued development of the logistics industry, but increased the amount of cargo in urban area, and caused social problems such as overcrowding of logistics. The courier service in the logistics base area utilizes the process of visiting the delivery site directly because the courier must precede the loading work of the cargo in the truck for the delivery of the ordered product. Currently, it's carried out as automated logistics equipment such as conveyor belt in unloading or classification stage, but the automation system isn't applied, so the work efficiency is decreasing and the intensity of the courier worker's labor is increased. In particular, small-scale courier workers belonging to the sub-terminal unload at night at underdeveloped facilities outside the city center. Therefore, the productivity of the work is lowered and the risk of safety accidents is exposed, so robot-based loading technology is needed. In this paper, we have derived the top-level concept and requirements of robot-based loading system to increase the flexibility of logistics processing and to ensure the safety of courier drivers. We defined algorithms and motion concepts to increase the cargo loading efficiency of logistics sub-terminals through the requirements of end effector technology, which is important among concepts. Finally, the control technique was proposed to determine and position the load for design input development of the automatic conveyor system.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.579-590
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• 2022

In this study, we aimed to develop a Python-based outer-ring galaxy analysis algorithm according to the data science process. We assumed that the potential users are citizen scientists, including students and teachers. In the actual classification studies using real data of galaxies, a specialized software called IRAF is used, thereby limiting the general public's access to the software. Therefore, an image analysis algorithm was developed for the outer-ring galaxies as targets, which were compared with those of the previous research. The results of this study were compared with those of studies conducted using IRAF to verify the performance of the newly developed image analysis algorithm. Among the 69 outer-ring galaxies in the first test, 50 cases (72.5%) showed high agreement with the previous research. The remaining 19 cases (27.5%) showed differences that were caused by the presence of bright stars overlapped in the line of sight or weak brightness in the inner galaxy. To increase the usability of the finished product that has undergone a supplementary process, all used data, algorithms, Python code files, and user manuals were loaded in GitHub and made available as shared educational materials.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.199-206
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• 2022

A malfunction or breakdown of a manufacturing facility leads to product defects and the suspension of production lines, resulting in huge financial losses for manufacturers. Due to the spread of smart factory services, a large amount of data is being collected in factories, and AI-based research is being conducted to predict and diagnose manufacturing facility breakdowns or manufacturing site efficiency. However, because of the characteristics of manufacturing data, such as a severe class imbalance about abnormalities and ambiguous label information that distinguishes abnormalities, developing classification or anomaly detection models is highly difficult. In this paper, we present an deep learning algorithm for anomaly detection of a manufacturing facility using reconstruction loss of CNN-based model and ananlyze its performance. The algorithm detects anomalies by relying solely on normal data from the facility's manufacturing data in the exclusion of abnormal data.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.158-158
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• 2023

Characterizing the performance of precipitation (hereafter PRE) products in estimating the uncertainties in daily PRE in the era of global warming is of great value to the ecosystem's sustainability and human survival. This study intercompares the performance of different PRE products (gauge-based, satellite and reanalysis) sourced from the Frequent Rainfall Observations on GridS (FROGS) database over diverse climate zones in Africa and identifies regions where they depict minimal uncertainties in order to build optimal maps as a guide for different climate users. This is achieved by utilizing various techniques, including the triple collection (TC) approach, to assess the capabilities and limitations of different PRE products over nine climatic zones over the continent. For daily scale analysis, the uncertainties in light PRE (0.1 5mm/day) are prevalent over most regions in Africa during the study duration (2001-2016). Estimating the occurrence of extreme PRE events based on daily PRE 90th percentile suggests that extreme PRE is mainly detected over central Africa (CAF) region and some coastal regions of west Africa (WAF) where the majority of uncorrected satellite products show good agreement. The detection of PRE days and non-PRE days based on categorical statistics suggests that a perfect POD/FAR score is unattainable irrespective of the product type. Daily PRE uncertainties determined based on quantitative metrics show that consistent, satisfactory performance is demonstrated by the IMERG products (uncorrected), ARCv2, CHIRPSv2, 3B42v7.0 and PERSIANN_CDRv1r1 (corrected), and GPCC, CPC_v1.0, and REGEN_ALL (gauge) during the study period. The optimal maps that show the classification of products in regions where they depict reliable performance can be recommended for various usage for different stakeholders.

• Fashion & Textile Research Journal
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• v.25 no.4
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• pp.460-471
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• 2023

This study aimed to analyze the consumption value and clothing pursuit benefits of genderless fashion based on gender identity. The study questionnaire was distributed to and collected from men and women in their 20s and 30s living in Seoul City and the Gyeonggi province. The collected data were analyzed by using Cronbachs α, factor analysis, K-means group classification analysis, and ANOVA. The study results were as follows. First, gender identity was categorized into three groups: the genderless group, the traditional gender rejection group, and the traditional gender acceptance group. Therefore, it is necessary to subdivide gender identity rather than acceptance and rejection of traditional gender roles. Second, an analysis of consumption value based on gender identity showed significant differences in terms of fashion value and expressive value. Therefore, it is important to establish a differentiated strategy based on the relevant gender identity group when establishing genderless fashion design or marketing strategy. Finally, the study results showed that clothing pursuit benefits based on gender identity, there was a significant difference in terms of individuality pursuit, deviation from the norm, and fashion pursuit. In particular, since the genderless phenomenon agrees with the characteristics of the MZ generation, it will be necessary to share brand information or product information through digital media or to utilize a sharing culture-that is, 'meaning out' tendency and 'flex culture' (i.e., conspicuous consumption).

• International Journal of Industrial Entomology and Biomaterials
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• v.47 no.1
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• pp.51-62
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• 2023

The advantages of silkworms as functional foods are well known and various products are being developed. In general, silkworms sold in the market include silkworm powder (3 days of fifth instars) and SukJam (7 days or more of fifth instars), In other words, product classification is made according to the maturity of the fifth instar silkworms. In this study, we analyzed the gene expression changes in the fifth instar silkworms and attempted to validate the use of deregulated genes in maturity analysis. After rearing BaekokJam, transcriptome analysis was performed on days 1, 3, 5, and 8 days of the fifth instar, and differentially expressed genes showing differences at each period were selected. Of the 31,841 contigs analyzed, 4012 contigs were identified with a log2 fold change of two or more between 5 and 8 days of the fifth instar. RT-PCR was performed for 18 contigs, which showed increased or decreased expression, but in c127159, c97909, c96974, c119920, c42251, and c80216 showed clear differences. To identify SukJam, a combination of the contigs c127159 (180 bp), c97909 (143 bp), and c80216 (120 bp) was amplified. Taken together, these results suggest that the harvest time of silkworms can be determined using gene expression pattern analysis.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1279-1288
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• 2023

Recently, domestic leisure boats have been actively researching eco-friendly product development to enter the global market. Since the hulls of existing leisure boats are mainly made of fiber reinforced plastic (FRP) or aluminum, design techniques for securing structural safety by applying related materials have been mainly studied. In this study, an initial structural design safety assessment of a trimaran pontoon leisure boat with a modular hull structure and eco-friendly high-density polyethylene (HDPE) material was conducted, and sensitivity evaluation and optimization analysis for lightweight design were performed. The initial structural design safety assessment was carried out by creating a finite element analysis model and applying the loading conditions specified in the ship classification regulation to check whether the specified allowable stresses are satisfied. For the sensitivity evaluation, the influence of stress and weight of each hull structural member was evaluated using the orthogonal array design of experiments method, and an approximate model based on the response surface method was generated using the results of the design of experiments. The optimization analysis set the thickness of the hull structural members as the design variable and considered the optimal design formulation to minimize the weight while satisfying the allowable stress. The algorithm of the optimization analysis applied the Gradient-population Based Optimizer (GBO) to improve the accuracy of the optimal solution convergence while reducing the numerical cost. Through this study, the optimal design of a newly developed eco-friendly trimaran pontoon leisure boat with a weight reduction of 10% was presented.

• Food Science of Animal Resources
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• v.44 no.1
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• pp.1-18
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• 2024

This study reviewed the current data presented in the literature on developing meat analogs using plant-, insect-, and protein-derived materials and presents a conclusion on future perspectives. As a result of this study, it was found that the current products developed using plant-, insect-, and mycoprotein-derived materials still did not provide the quality of traditional meat products. Plant-derived meat analogs have been shown to use soybean-derived materials and beta-glucan or gluten, while insect-derived materials have been studied by mixing them with plant-derived materials. It is reported that the development of meat analogs using mycoprotein is somewhat insufficient compared to other materials, and safety issues should also be considered. Growth in the meat analog market, which includes products made using plant-, insect-, and mycoprotein-derived materials is reliant upon further research being conducted, as well as increased efforts for it to coexist alongside the traditional livestock industry. Additionally, it will become necessary to clearly define legal standards for meat analogs, such as their classification, characteristics, and product-labeling methods.

• Environmental and Resource Economics Review
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• v.33 no.1
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• pp.87-112
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• 2024

This study estimates the regional input-output table and GHG emissions in 2019 and then analyzes the economic effects of carbon taxes by region and industry in Korea. The GHG emission, emission coefficient, and emission induction coefficient are estimated to be higher in manufacturing-oriented metropolitan provinces. The GHG emission coefficient in the same industry varies from region to region, which might reflect the standard of product classification, characteristics of production technology, and the regional differences in input structure. If a carbon tax is imposed, production costs are expected to increase and demand and production will decrease, especially in the manufacturing industry, which emits more GFG. On the other hand, the impact of carbon taxes on each region is not expected to vary significantly from region to region, which might be due to the fact that those differences are mitigated by industry-related effects. Since the impact of carbon taxes is expected to spread to the entire region, close cooperation between local governments is necessary in the process of implementing carbon neutrality in the future.