• Title/Summary/Keyword: program performance

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Underwater Target Localization Using the Interference Pattern of Broadband Spectrogram Estimated by Three Sensors (3개 센서의 광대역 신호 스펙트로그램에 나타나는 간섭패턴을 이용한 수중 표적의 위치 추정)

  • Kim, Se-Young;Chun, Seung-Yong;Kim, Ki-Man
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.4
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    • pp.173-181
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    • 2007
  • In this paper, we propose a moving target localization algorithm using acoustic spectrograms. A time-versus-frequency spectrogram provide a information of trajectory of the moving target in underwater. For a source at sufficiently long range from a receiver, broadband striation patterns seen in spectrogram represents the mutual interference between modes which reflected by surface and bottom. The slope of the maximum intensity striation is influenced by waveguide invariant parameter ${\beta}$ and distance between target and sensor. When more than two sensors are applied to measure the moving ship-radited noise, the slope and frequency of the maximum intensity striation are depend on distance between target and receiver. We assumed two sensors to fixed point then form a circle of apollonios which set of all points whose distances from two fixed points are in a constant ratio. In case of three sensors are applied, two circle form an intersection point so coordinates of this point can be estimated as a position of target. To evaluates a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program.

Analysis of grout injection distance in single rock joint (단일절리 암반에서 그라우팅 주입거리 분석)

  • Ji-Yeong Kim;Jo-Hyun Weon;Jong-Won Lee;Tae-Min Oh
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.6
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    • pp.541-554
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    • 2023
  • The utilization of underground spaces in relation to tunnels and energy/waste storage is on the rise. To ensure the stability of underground spaces, it is crucial to reinforce rock fractures and discontinuities. Discontinuities, such as joints, can weaken the strength of the rock and lead to groundwater inflow into underground spaces. In order to enhance the strength and stability of the area around these discontinuities, rock grouting techniques are employed. However, during rock grouting, it is impossible to visually confirm whether the grouting material is being smoothly injected as intended. Without proper injection, the expected increases in strength, durability, and degree of consolidation may not be achieved. Therefore, it is necessary to predict in advance whether the grouting material is being injected as designed. In this study, we aimed to assess the injection performance based on injection variables such as the water/cement mixture ratio, injection pressure, and injection flow using UDEC (Universal Distinct Element Code) numerical program. Additionally, numerical results were validated by the lab experiment. The results of this study are expected to help optimize variables such as injection material properties, injection time, and pump pressure in the grouting design in the field.

Leveraging LLMs for Corporate Data Analysis: Employee Turnover Prediction with ChatGPT (대형 언어 모델을 활용한 기업데이터 분석: ChatGPT를 활용한 직원 이직 예측)

  • Sungmin Kim;Jee Yong Chung
    • Knowledge Management Research
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    • v.25 no.2
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    • pp.19-47
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    • 2024
  • Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.

Deriving Criteria Weights for Acute Care Hospital Accreditation in South Korea: Using Analytic Hierarchy Process (급성기병원 인증기준의 가중치 도출: 계층적 분석법을 활용하여)

  • Hwa Yeong Oh;Hyeon-Jeong Lee;Minsu Ock;In Ho Kim;Ho Yeol Jang;Ji-Eun Choi
    • Quality Improvement in Health Care
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    • v.30 no.1
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    • pp.33-43
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    • 2024
  • Purpose:The acute hospital accreditation program launched in South Korea has shown positive effects on safety culture and quality of care. However, relative weights have not yet been investigated for accreditation criteria with a hierarchical structure. This study aimed to derive the relative weights of acute-care hospital accreditation criteria. Methods: We conducted an online survey using the analytic hierarchy process (AHP) technique to assess the validity, importance, and urgency of acute hospital accreditation criteria. The AHP online survey link was distributed in November 2022 after obtaining informed consent from 10 experts in hospital accreditation. Results: 'Basic value system' ranked highest, while 'patient care system' ranked second in terms of validity, importance, and urgency. 'Performance management system' had the lowest validity and urgency, while 'organizational management system' carried the lowest importance. Within the 'patient care system' domain, 'surgery and anesthesia sedation management' scored highest in validity and importance, and 'patient care' scored highest in urgency. 'Care delivery system and evaluation' received the lowest scores for all three aspects. In the 'organizational management system' domain, infection control ranked highest in terms of validity, importance, and urgency. The lowest validity was observed for 'management and organizational operation' and the lowest importance and urgency were noted for 'human resource management'. Conclusion: The weights for validity, importance, and urgency, as shown in each domain and chapter, and the number of measurable elements included, are largely inconsistent. This study will contribute to the development of the structure and scientific improvement of accreditation standards.

Analysis of RSET According to Exit Installation Standards for the Exterior of a Food Manufacturing Plant Building (식품공장 건축물 바깥쪽으로의 출구 설치기준에 따른 RSET 분석)

  • Park, Ha-Soung;Lee, Jae-Wook;Kong, Ha-Sung
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.201-208
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    • 2024
  • In this study, we investigated whether the evacuation time according to the exit installation standards specified in the building code during a food factory fire is compatible with the evacuation time based on the performance-based design specified by the fire department, in order to determine if evacuation safety is ensured. We used the Pathfinder program to confirm the evacuation time, and experimented with three scenarios for exit installation standards towards the outside of the building: 60m, 80m, and 100m. The target building in the experiment corresponded to the building code's exit installation standard of 100m from each dwelling. The experimental results showed tt in the cases of 80m and 100m, ASET exceeded RSET, indicating tt evacuation safety was not ensured, while in the case of 60m, evacuation safety was maintained. Through this study, it was confirmed tt even when the exit installation standards towards the outside of the building are met, evacuation safety may not be guaranteed.

Enhancing Empathic Reasoning of Large Language Models Based on Psychotherapy Models for AI-assisted Social Support (인공지능 기반 사회적 지지를 위한 대형언어모형의 공감적 추론 향상: 심리치료 모형을 중심으로)

  • Yoon Kyung Lee;Inju Lee;Minjung Shin;Seoyeon Bae;Sowon Hahn
    • Korean Journal of Cognitive Science
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    • v.35 no.1
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    • pp.23-48
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    • 2024
  • Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

Quantity Estimation Method for High-Performance Insulated Wall Panels with Complex Details Using BIM Family Libraries (BIM의 패밀리 라이브러리를 이용한 복잡한 상세를 갖는 고단열 벽체 판넬의 물량 산출 방법)

  • Mun, Ju-Hyun
    • 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.

Comparison of Error Rate and Prediction of Compression Index of Clay to Machine Learning Models using Orange Mining (오렌지마이닝을 활용한 기계학습 모델별 점토 압축지수의 오차율 및 예측 비교)

  • Yoo-Jae Woong;Woo-Young Kim;Tae-Hyung Kim
    • Journal of the Korean Geosynthetics Society
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    • v.23 no.3
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    • pp.15-22
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    • 2024
  • Predicting ground settlement during the improvement of soft ground and the construction of a structure is an crucial factor. Numerous studies have been conducted, and many prediction equations have been proposed to estimate settlement. Settlement can be calculated using the compression index of clay. In this study, data on water content, void ratio, liquid limit, plastic limit, and compression index from the Busan New Port area were collected to construct a dataset. Correlation analysis was conducted among the collected data. Machine learning algorithms, including Random Forest, Neural Network, Linear Regression, Ada Boost, and Gradient Boosting, were applied using the Orange mining program to propose compression index prediction models. The models' results were evaluated by comparing RMSE and MAPE values, which indicate error rates, and R2 values, which signify the models' significance. As a result, water content showed the highest correlation, while the plastic limit showed a somewhat lower correlation than other characteristics. Among the compared models, the AdaBoost model demonstrated the best performance. As a result of comparing each model, the AdaBoost model had the lowest error rate and a large coefficient of determination.

Cyclic Seismic Performance of RBS Weak-Axis Welded Moment Connections (RBS 약축 용접모멘트접합부의 내진성능 평가)

  • Lee, Cheol Ho;Jung, Jong Hyun;Kim, Sung Yong
    • Journal of Korean Society of Steel Construction
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    • v.27 no.6
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    • pp.513-523
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    • 2015
  • In steel moment frames constructed of H-shapes, strong-axis moment connections should be used for maximum structural efficiency if possible. And most of cyclic seismic testing, domestic and international, has been conducted for strong-axis moment connections and cyclic test data for weak-axis connections is quite limited. However, when perpendicular moment frames meet, weak-axis moment connections are also needed at the intersecting locations. Especially, both strong- and weak-axis moment connections have been frequently used in domestic practice. In this study, cyclic seismic performance of RBS (reduced beam section) weak-axis welded moment connections was experimentally investigated. Test specimens, designed according to the procedure proposed by Gilton and Uang (2002), performed well and developed an excellent plastic rotation capacity of 0.03 rad or higher, although a simplified sizing procedure for attaching the beam web to the shear plate in the form of C-shaped fillet weld was used. The test results of this study showed that the sharp corner of C-shaped fillet weld tends to be the origin of crack propagation due to stress concentration there and needs to be trimmed for the better weld shape. Different from strong-axis moment connections, due to the presence of weld access hole, a kind of CJP butt joint is formed between the beam flange and the horizontal continuity plate in weak-axis moment connections. When weld access hole is large, this butt joint can experience cyclic local buckling and subsequent low cycle fatigue fracture as observed in this testing program. Thus the size of web access hole at the butt joint should be minimized if possible. The recommended seismic detailing such as stickout, trimming, and thicker continuity plate for construction tolerance should be followed for design and fabrication of weak-axis welded moment connections.

Effects of dietary supplementation with fermented spent mushroom substrates of the winter mushroom (Flammulina velutipes) on growth performance, carcass traits, and economic characteristics of Hanwoo steers (발효 팽이버섯 수확후배지의 급여 수준이 한우 거세우의 비육과 도체성적 및 경제성 분석에 미치는 영향)

  • Moon, Yea-Hwang;Cho, Woong-Ki;Kim, Hyun-Jung;Kim, Ji-Eun;Kim, Bo-Ram;Kim, Hye-Soo;Cho, Soo-Jeong
    • Journal of Mushroom
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    • v.15 no.4
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    • pp.223-228
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    • 2017
  • This study was conducted to investigate the effects of fermented spent mushroom substrates (F-SMS) of Flammulina velutipes on growth performance, carcass traits, and economic characteristics of Hanwoo steers. A yeast strain (Saccharomyces sp. UJ14) and Bacillus strain (Bacillus sp. UJ03) isolated from fresh spent mushroom substrates of Flammulina velutipes were used as probiotics to prepare F-SMS. Twenty-four Hanwoo steers (14 months old) were allocated to three dietary treatments via a randomized block design and were slaughtered at 30 months of age. These treatment groups included Control (TMR), T1 (TMR containing 10% of F-SMS) group, and T2 (TMR containing 30% of F-SMS). Body weight gain was not influenced by the experimental diets. DM and TDN intakes in the finishing period were significantly (p < 0.05) greater in group T1 than in other groups. CP intake was significantly (p < 0.05) greater in group T2 than in other groups during the whole experimental period. Among carcass traits, rib-eye area and back fat thickness tended to increase with F-SMS supplementation. The appearance rate (%) of a meat yield more than grade A was the highest in group T1. The net profits increased by 1.2% and 13.3% in groups T1 and T2, respectively. In conclusion, if a proper feeding program (including feed safety) can be ensured, spent mushroom substrates of Flammulina velutipes can prove to be a highly profitable feed source for Hanwoo steers.