• Journal of Digital Convergence
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• v.20 no.1
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• pp.265-275
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• 2022

This study analyzes and categorizes the cases of military look's transitional design ideas in recent women's fashion collections, and derives characteristics. The research method is a theoretical review of military look and an analysis of fashion collection cases. The research results were classified into a total of six transformational design ideas. As a structural change in design, it is a decentralized type, a type of expansion and reduction, a change in the entire material, or a transition of some materials, and finally a type according to heterogeneous harmony and organic combination corresponding to styling. Finally, a total of three characteristics are the reconstruction of structural elements, the expansion of the metric of the second mix match, and the emotional fusion of styling. I hope that the study of the transformative type of idea of the new military look will be the driving force for creative design development and will be a basic study that can read the current status and changes of the times throughout fashion design.

• Animal Bioscience
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• v.36 no.1
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• pp.63-74
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• 2023

Objective: The objective of this study was to investigate the effects of feeding active dry yeast (ADY) and yeast culture (YC) on fecal bacterial community in finishing bulls fed high-concentrate diets in the same experimental environment. Methods: Forty-five healthy finishing cattle (Simmental×Chinese Luxi yellow bulls; 24 months; 505±29 kg) were randomly divided into three groups: i) CON group (control group, only fed basal diet), ii) ADY group (fed basal diet + active dry yeast), and iii) YC group (fed basal diet + yeast culture). At the end of the trial, nine rectum fecal samples were randomly selected from each group for bacterial DNA sequencing. Results: There was no difference among groups about alpha diversity indices (all p>0.05), including ACE, Chao 1, Shannon, and Simpson indices. Principal component analysis and non-metric multidimensional scaling analysis showed a high similarity among three groups. Compared with CON group, ADY and YC groups had greater relative abundance of c_Clostridia, o_Oscillospirales, and f_Oscillospiraceae, but lesser relative abundance of g_Megasphaera, and s_Megasphaera_elsdenii (all p<0.01). And, the relative abundances of p_Firmicutes (p = 0.03), s_Prevotella_sp (p = 0.03), o_Clostridiales (p<0.01), g_Clostridium (p<0.01), f_Caloramatoraceae (p<0.01), and f_Ruminococcaceae (p = 0.04) were increased in the ADY group. The PICRUSt2 prediction results showed that the metabolic pathways had no significant differences among groups (p>0.05). Besides, the relative abundance of c_Clostridia (r = 0.42), and f_Oscillospiraceae (r = 0.40) were positively correlated to average daily gain of finishing bulls (p<0.05). Conclusion: Both of ADY and YC had no effect on diversity of fecal bacteria in finishing bulls, but the supplementation of ADY and YC can improve the large intestinal function in finishing bulls by increasing the abundance of cellulolytic bacteria and altering the abundance of lactic acid-utilizing bacteria.

• Smart Structures and Systems
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• v.32 no.1
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• pp.1-7
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• 2023

In modal analysis, the mode shape reflects the vibration characteristics of the structure, and thus it is widely performed for finite element model updating and structural health monitoring. Generally, the acceleration-based mode shape is suitable to express the characteristics of structures for the translational vibration; however, it is difficult to represent the rotational mode at boundary conditions. A tilt sensor and gyroscope capable of measuring rotational mode are used to analyze the overall behavior of the structure, but extracting its mode shape is the major challenge under the small vibration always. Herein, we conducted a feasibility study on a multi-mode shape estimating approach utilizing a single physical quantity signal. The basic concept of the proposed method is to receive multi-metric dynamic responses from two sensors and obtain mode shapes through bridge loading test with relatively large deformation. In addition, the linear transformation matrix for estimating two mode shapes is derived, and the mode shape based on the gyro sensor data is obtained by acceleration response using ambient vibration. Because the structure's behavior with respect to translational and rotational mode can be confirmed, the proposed method can obtain the total response of the structure considering boundary conditions. To verify the feasibility of the proposed method, we pre-measured dynamic data acquired from five accelerometers and five gyro sensors in a lab-scale test considering bridge structures, and obtained a linear transformation matrix for estimating the multi-mode shapes. In addition, the mode shapes for two physical quantities could be extracted by using only the acceleration data. Finally, the mode shapes estimated by the proposed method were compared with the mode shapes obtained from the two sensors. This study confirmed the applicability of the multi-mode shape estimation approach for accurate damage assessment using multi-dimensional mode shapes of bridge structures, and can be used to evaluate the behavior of structures under ambient vibration.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.315-327
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• 2023

Purpose: Recently, research has continued to predict the time of failure of the facility through measurement data obtained by attaching a sensor to the facility. However, depending on the facility, it may be difficult to attach a sensor. The purpose of this study is to propose a power generation maintenance plan system based on failure record data obtained from Continuous Ship Unloader, one of the facilities that is difficult to attach sensors. Methods: This study uses data collected from 2012 to 2022 from the 'CSU-1B' model among Continuous Ship Unloader operated by Korea Midland Power Co., LTD. By fitting fault record data to the Weibull distribution, appropriate maintenance cycles and ranges for each target facility subsystem are derived. In addition, maintenance group between subsystems is selected through Euclidean distance, a metric often used for time series data similarity. Through this, a system for establishing an maintenance plan for power generation facilities is proposed. Results: The results of this study are as follows. For the 17 subsystems of the Continuous Ship Unloader, proper maintenance cycles and ranges were determined, and a total of four maintenance groups were chosen. This resulted in the creation of an power generation maintenance plan system and the establishment of an maintenance plan. Conclusion: This study is a case study of power generation facilities. We proposed a maintenance plan system for Continuous Ship Unloader among power generation facilities.

• Smart Media Journal
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• v.12 no.5
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• pp.28-35
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• 2023

In this study, we propose a new light-weight model RoutingConvNet with fewer parameters to improve the applicability and practicality of speech emotion recognition. To reduce the number of learnable parameters, the proposed model connects bidirectional MFCCs on a channel-by-channel basis to learn long-term emotion dependence and extract contextual features. A light-weight deep CNN is constructed for low-level feature extraction, and self-attention is used to obtain information about channel and spatial signals in speech signals. In addition, we apply dynamic routing to improve the accuracy and construct a model that is robust to feature variations. The proposed model shows parameter reduction and accuracy improvement in the overall experiments of speech emotion datasets (EMO-DB, RAVDESS, and IEMOCAP), achieving 87.86%, 83.44%, and 66.06% accuracy respectively with about 156,000 parameters. In this study, we proposed a metric to calculate the trade-off between the number of parameters and accuracy for performance evaluation against light-weight.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.545-553
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• 2009

This paper describes the result of study on measurement of displacement of structure by means of non-contacting method, close-range digital photogrammetry using digital camera. To apply close-range digital photogrammetry to displacement measurement of structure, correction of lens distortion that interferes geometrical analysis has been carried out and then measuring displacement was performed on load regulated-rahmen. For enhanced applicability of displacement measurement, MIDAS which is a structural analysis program was used for modeling and the result was taken from comparative analysis. As a result of the study, it is showed that close-range digital photogrammetry could supplement several weaknesses of LVDT and cable displacement meter and, especially, economy in the perspective of measuring time could be realized. Close-range digital photogrammetry using digital camera can be applied to the area where requires visual analysis such as 3D modeling of structure, profile replication of measurement of structure as well as measurement of displacement of structure.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.541-544
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• 2023

LLM(Largescale Language Model)의 성능 향상을 위한 비용 효율적인 방법으로 ChatGPT, GPT-4와 같은 초거대 모델의 output에 대해 SLM(Small Language Model)을 finetune하는 방법이 주목받고 있다. 그러나, 이러한 접근법은 주로 범용적인 지시사항 모델을 위한 학습 방법으로 사용되며, 제한된 특정 도메인에서는 추가적인 성능 개선의 여지가 있다. 본 연구는 특정 도메인(Writing Assistant)에서의 성능 향상을 위한 새로운 방법인 Self-Guided Approach를 제안한다. Self-Guided Approach는 (1) LLM을 활용해 시드 데이터에 대해 도메인 특화된 metric(유용성, 관련성, 정확성, 세부사항의 수준별) 점수를 매기고, (2) 점수가 매겨진 데이터와 점수가 매겨지지 않은 데이터를 모두 활용하여 supervised 방식으로 SLM을 미세 조정한다. Vicuna에서 제안된 평가 방법인, GPT-4를 활용한 자동평가 프레임워크를 사용하여 Self-Guided Approach로 학습된 SLM의 성능을 평가하였다. 평가 결과 Self-Guided Approach가 Self-instruct, alpaca와 같이, 생성된 instruction 데이터에 튜닝하는 기존의 훈련 방법에 비해 성능이 향상됨을 확인했다. 다양한 스케일의 한국어 오픈 소스 LLM(Polyglot1.3B, PolyGlot3.8B, PolyGlot5.8B)에 대해서 Self-Guided Approach를 활용한 성능 개선을 확인했다. 평가는 GPT-4를 활용한 자동 평가를 진행했으며, Korean Novel Generation 도메인의 경우, 테스트 셋에서 4.547점에서 6.286점의 성능 향상이 발생했으며, Korean scenario Genration 도메인의 경우, 테스트 셋에서 4.038점에서 5.795 점의 성능 향상이 발생했으며, 다른 유사 도메인들에서도 비슷한 점수 향상을 확인했다. Self-Guided Approach의 활용을 통해 특정 도메인(Writing Assistant)에서의 SLM의 성능 개선 가능성을 확인했으며 이는 LLM에 비용부담을 크게 줄이면서도 제한된 도메인에서 성능을 유지하며, LLM을 활용한 응용 서비스에 있어 실질적인 도움을 제공할 수 있을 것으로 기대된다.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.197-226
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• 2023

Generative Text Summarization is one of the Natural Language Processing tasks. It generates a short abbreviated summary while preserving the content of the long text. ROUGE is a widely used lexical-overlap based metric for text summarization models in generative summarization benchmarks. Although it shows very high performance, the studies report that 30% of the generated summary and the text are still inconsistent. This paper proposes a methodology for evaluating the performance of the summary model without using the correct summary. AggreFACT is a human-annotated dataset that classifies the types of errors in neural text summarization models. Among all the test candidates, the two cases, generation summary, and when errors occurred throughout the summary showed the highest correlation results. We observed that the proposed evaluation score showed a high correlation with models finetuned with BART and PEGASUS, which is pretrained with a large-scale Transformer structure.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.3
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• pp.308-316
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• 2023

Objectives: The aim of this study is to measure and assess the occupational noise exposure levels among construction workers at apartment building construction sites in South Korea. Methods: Noise exposure assessments were conducted for 139 construction workers across 10 different trades at 53 apartment building construction sites in the northern part of Gyeonggi-do. Assessments were carried out using a noise dosimeter set with a 90 dB criterion, an 80 dB threshold, and a 5 dB exchange rate over a period of more than 6 hours(L_MOEL) Results: The mean L_MOEL (equivalent continuous noise level over 8 hours) for the 139 dosimeter samples was 87.8 ± 4.3 dBA. The mean noise exposure level for each construction trade, referred to as the trade mean, was also calculated. Significant differences in noise exposure levels were observed between construction trades (ANOVA, p < 0.001). The highest L_MOEL values were recorded for concrete chippers (93.2 ± 2.6 dBA), followed by ironworkers (88.4 ± 0.7 dBA), concrete finishers (88.3 ± 2.7 dBA), masonry workers (87.7 ± 1.9 dBA), pile driver operators (85.6 ± 1.7 dBA), concrete carpenters (84.9 ± 2.4 dBA), interior carpenters (83.5 ± 2.1 dBA), and other groups (81.4 ± 2.2 dBA). Conclusions: The findings suggest that nearly all construction workers in this study are at risk of Noise-Induced Hearing Loss (NIHL). Moreover, the study establishes that construction trades can serve as a useful metric for assessing noise exposure levels at apartment construction sites.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.163-170
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• 2023

The user-based collaborative filtering technique, one of the implementation methods of the recommendation system, recommends the preferred items of neighboring users based on the calculations of neighboring users with similar rating histories. However, it fundamentally has a data scarcity problem in which the quality of recommendations is significantly reduced when there is little common rating history. To solve this problem, many existing studies have proposed various methods of combining Jaccard index with a similarity measure. In this study, we introduce a time-aware concept to Jaccard index and propose a method of weighting common items with different weights depending on the rating time. As a result of conducting experiments using various performance metrics and time intervals, it is confirmed that the proposed method showed the best performance compared to the original Jaccard index at most metrics, and that the optimal time interval differs depending on the type of performance metric.