• Fashion & Textile Research Journal
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• v.25 no.6
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• pp.673-689
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• 2023

To realize the traceability of sustainable textile products, this study presents a low-carbon process through energy savings in the textile material manufacturing process. Traceability is becoming an important element of Life Cycle Assessment (LCA), which confirms the eco-friendliness of textile products as well as supply chain information. Textile products with complex manufacturing processes require traceability of each step of the process to calculate carbon emissions and power usage. Additionally, an understanding of the characteristics of the product planning-manufacturing-distribution process and an overall understanding of carbon emissions sources are required. Energy use in the textile material manufacturing stage produces the largest amount of carbon dioxide, and the amount of carbon emitted from processes such as dyeing, weaving and knitting can be calculated. Energy saving methods include efficiency improvement and energy recycling, and carbon dioxide emissions can be reduced through waste heat recovery, sensor-based smart systems, and replacement of old facilities. In the dyeing process, which uses a considerable amount of heat energy, LNG, steam can be saved by using "heat exchangers," "condensate management traps," and "tenter exhaust fan controllers." In weaving and knitting processes, which use a considerable amount of electrical energy, about 10- 20% of energy can be saved by using old compressors and motors.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.4
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• pp.155-162
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• 2023

PURPOSE: The primary objective of this study was to develop a virtual reality-based vestibular rehabilitation system to enhance balance perception, target rehabilitation specialists, and evaluate its usability. A key goal was establishing a system refinement strategy based on the collected data. METHODS: We conducted a study involving ten adults aged 10 to 29 in Gwangju Metropolitan City to evaluate the usability of a virtual reality-based vestibular rehabilitation system to enhance balance perception. After introducing the product and explaining its use to the participants, balance assessments and training were conducted using computerized dynamic posturography (CDP) (also called the test of balance [TOB]). Subsequently, participants were given a questionnaire to evaluate subjective stability, operability, and satisfaction. Frequency analysis was utilized to determine the frequency of the variable values of the measurement items in the survey for descriptive statistics. RESULTS: We found that the average usability score was 2.587. When broken down by category, stability received an average rating of 2.725, operability scored an average of 2.783, and satisfaction averaged 2.454. These findings suggest that most participants experienced positive sentiments and considerable satisfaction. CONCLUSION: The study successfully developed a virtual reality-based vestibular rehabilitation system, which was an improvement over the previous model and addressed its shortcomings. The results show that users with vestibular impairments are satisfied and more engaged with this system, indicating that additional studies are warranted.

• Journal of Digital Policy
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• v.2 no.4
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• pp.17-23
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• 2023

In this paper, in order to improve production processing for small and medium-sized precision processing companies, we apply a manufacturing execution system to existing process methods and integrate precision processing data to strengthen process management within the company, increase facility operation efficiency, and realize a reduction in defect rates. The differences in productivity improvement and cost reduction rates were compared and analyzed. As a result, production productivity improved by 7.0% and product defect rate improved by 0.1% point due to the introduction of the manufacturing execution system. It was confirmed that manufacturing cost reduction improved by 10.0% and delivery compliance rate improved by 1.1%. If additional smart factory technology is applied based on the manufacturing execution system proposed in this study in the future, sales and profits in the processing industry are expected to increase due to an increase in the PQCD index.

• Composites Research
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• v.36 no.6
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• pp.388-394
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• 2023

In composites manufacturing, increasing resin impregnation is a key way to speed up the manufacturing process and improve product quality. While resin improvement is important, simple fiber surface treatments can also improve resin flowability. In this study, different plasma treatment times were applied to carbon fiber fabrics to improve the impregnation between resin and fiber. Electrical resistivity measurements were used to evaluate the dispersion of resin in the fibers, which changed with plasma treatment. The effect of fiber surface treatment on resin spreadability could be observed in real time. When inserting a carbon fiber tow into the resin, the amount of resin that soaked into the tow was measured to objectively compare resin impregnation. Five minutes of plasma treatment improved the tensile and compressive strength of the composite by more than 50%, while reducing the void content and increasing the fire point impregnation flow rate. Finally, a dynamic flexural fatigue test was conducted using a portion of the composite used as an architectural composite part, and the composite part did not fail after one million cycles of a 3 kN load.

• Journal of fish pathology
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• v.37 no.1
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• pp.147-153
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• 2024

The World Organization for Animal Health (WOAH) recommends two protocols (ITS and COI) for conventional PCR of G. salaris diagnosis. However, ITS PCR protocol may yield false-positive results, leading to unnecessary countermeasures. It's difficult to distinguish between G. salaris and false-positive by similar amplicon size of PCR, since the amplicon size of ITS PCR in G. salaris and false-positive was 1,300 and 1,187 bp, respectively. The nucleotide sequences of ITS false-positive in rainbow trout is 99.7% identical to previously reported host genome sequences of rainbow trout (Oncorhynchus mykiss) and 95.3 to 89.1% identical to those of other salmonid fish species. To reduce false-positive PCR band, PCR was performed by the different annealing temperature, but PCR bands were still detected. In RFLP analysis by HaeIII, the PCR product of G. salaris was digested into four bands of 512, 399, 234 and 154 bp, while the false-positive was digested into seven bands of 297, 263, 242, 144, 93, 80 and 68 bp. In the RFLP patterns digested by HindIII, G. salaris showed two bands of 659 and 640 bp, while false-positive had one fragment of 1,187 bp without any digestion. Therefore, the RFLP method of ITS PCR with HaeIII and HindIII can be used for differentiation between G. salaris and false-positive. These results might provide important information on the improvement of PCR diagnostic method of G. salaris.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.85-96
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• 2024

As users of paid media readers' satisfaction with usage directly affects the promotion and development of paid media in China. Based on relevant research literature on user sustained use behavior, using the Expectation Confirmation Model as the framework, China paid media Caixin is used as a content product to construct a sustained use model for paid media. At the same time, the operational definition and theoretical assumptions of the variables in the model were provided, laying the foundation for subsequent empirical research on the effectiveness of the model.The research results show that paid media's social influence and performance expectations have a positive impact on Caixin App readers' adoption behavior,perceived usefulness and expection confirmation has a positive impact on Caixin App readers' satisfaction . Adoption behavior and satisfaction has a positive effect on continue using intention, what's more,the perceived usefulness also has a positive effect on continue using intention.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.107-116
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• 2024

Copper Filter Dryer (CFD) are responsible for removing impurities from the circulation of refrigerant in refrigeration and cooling systems to maintain clean refrigerant, and defects in CFD can lead to product defects such as leakage and reduced lifespan in refrigeration and cooling systems, making quality assurance essential. In the quality inspection stage, human inspection and defect judgment methods are traditionally used, but these methods are subjective and inaccurate. In this paper, YOLOv7 object detection algorithm was used to detect defects occurring during the CFD Shaft pipe and welding process to replace the existing quality inspection, and the detection performance of F1-Score 0.954 and 0.895 was confirmed. In addition, the cause of defects occurring during the welding process was analyzed by analyzing the sensor data corresponding to the Timestamp of the defect image. This paper proposes a method for manufacturing quality assurance and improvement by detecting defects that occur during CFD process and analyzing their causes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• Journal of Technology Innovation
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• v.31 no.3
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• pp.171-199
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• 2023

The purpose of this study was to develop an evaluation tool for selecting new projects for R&D project planning level of K Research Institute. For this purpose, items and questions for R&D project selection evaluation were developed based on the CIPP model and previous studies on selection evaluation and evaluation indicators for research project evaluation, and then two Delphi surveys were conducted. The developed evaluation tool was surveyed by 13 experts to verify contents validity ratio, convergence and consensus. The finally selected evaluation tool for R&D project planning consisted of 21 questions in 8 items, including 5 questions for context evaluation, 2 questions for input evaluation, 8 questions for process evaluation, and 6 questions for product evaluation. The evaluation tool developed will contribute to the solution of problems in the bottom-up planning process and to the improvement of the planning competence of the researchers. It will also contribute to improve the consistency and efficiency of evaluation during the selection process.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.663-675
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• 2023

Purpose: Skewness is an indicator used to measure the asymmetry of data distribution. In the past, product quality was judged only by mean and variance, but in modern management and manufacturing environments, various factors and volatility must be considered. Therefore, skewness helps accurately understand the shape of data distribution and identify outliers or problems, and skewness can be utilized from this new perspective. Therefore, we would like to propose a statistical quality control method using skewness. Methods: In order to generate data with the same mean and variance but different skewness, data was generated using normal distribution and gamma distribution. Using Minitab 18, we created 20 sets of 1,000 random data of normal distribution and gamma distribution. Using this data, it was proven that the process state can be sensitively identified by using skewness. Results: As a result of the analysis of this study, if the skewness is within ± 0.2, there is no difference in judgment from management based on the probability of errors that can be made in the management state as discussed in quality control. However, if the skewness exceeds ±0.2, the control chart considering only the standard deviation determines that it is in control, but it can be seen that the data is out of control. Conclusion: By using skewness in process management, the ability to evaluate data quality is improved and the ability to detect abnormal signals is excellent. By using this, process improvement and process non-sub-stitutability issues can be quickly identified and improved.