• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.9
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• pp.1077-1082
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• 2011

Ball joint is a rotating and swiveling element that is typically the interface between two parts. In an automobile, the ball joint is the component that connects the control arms to the steering knuckles by playing a role of bearing. The ball joint can also be installed in linkage systems for motion control applications. This paper describes the simulation strategy for a ball joint analysis, considering manufacturing process. Its manufacturing process can be divided into plugging and spinning. Then, the interested response is selected as the stress distribution generated between its ball and bearing. In this paper, a commercial code of NX DAFUL 2.0 using an implicit integration method is introduced to calculate the response. In addition, the gap analysis is performed to investigate the fitness. Also, the optimum design is suggested through case studies.

• Steel and Composite Structures
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• v.30 no.6
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• pp.535-550
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• 2019

Prestressed concrete (PC) bridges using corrugated steel webbing have emerged as one of the most promising forms of steel-concrete composite bridge. However, their long-term behavior is not well understood, especially in the case of large-span bridges. In order to study the time-dependent performance, a large three-span PC bridge with corrugated steel webbing was compared to a similar conventional PC bridge to examine their respective time-dependent characteristics. In addition, a three-dimensional finite element method with step-by-step time integration that takes into account cantilever construction procedures was used to predict long-term behaviors such as deflection, stress distribution and prestressing loss. These predictions were based upon four well-established empirical creep prediction models. PC bridges with a corrugated steel web were observed to have a better long-term performance relative to conventional PC bridges. In particular, it is noted that the pre-cambering for PC bridges with a corrugated steel web could be smaller than that of conventional PC bridges. The ratio of side-to-mid span has great influence on the long-term deformation of PC bridges with a corrugated steel web, and it is suggested that the design value should be between 0.4 and 0.6. However, the different creep prediction models still showed a weak homogeneity, thus, the further experimental research and the development of health monitoring systems are required to further progress our understanding of the long-term behavior of PC bridges with corrugated steel webbing.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.331-337
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• 2018

This paper presents dynamic algorithm of the MLS(moving least squares) difference method using first order differential Approximation. The governing equations are only discretized by the first order MLS derivative approximation. The system equation consists of an assembly of the approximate function, so the shape of system equation is similar to FEM(finite element method). The CDM(central difference method) is used for time integration of dynamic equilibrium equation. The natural frequency analyses of the MLS difference method and FEM are performed, and two analysis results are compared. Also, the accuracy of the proposed numerical method is verified by displaying the dynamic analysis results together with the results by the existing second order differential approximation. In the process of assembling the first order MLS derivative approximation, the oscillation error was suppressed and the stress distribution was interpreted as relatively uniform.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.33 no.3
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• pp.73-81
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• 2022

Since dissociative identity disorder (DID) has symptoms similar to schizophrenia, such as auditory hallucinations and delusional thoughts of being controlled, there are difficulties in its differential diagnosis. A 16-year-old adolescent male patient who was previously diagnosed with schizophrenia from a different hospital was admitted to our inpatient psychiatric unit for the evaluation of auditory hallucinations and suicide attempts. Through psychiatric evaluations, it was determined that the patient suffered from identity alternation, dissociation, and amnesia. As for the diagnostic evaluations, the following measures were implemented: a psychiatric interview regarding the diagnostic criteria, mental status examination, laboratory tests, brain imaging studies, electroencephalography, and full psychological test for adolescents, and the self-reported measure of the Adolescent Dissociative Experiences Scale. The patient was diagnosed with DID, and the following treatments were administered: pharmacotherapy, ego state therapy, psychoeducation regarding emotions, trauma-focused psychotherapy including stabilization, and family therapy. Following treatment, in the internal dimensions, the patient was able to recognize the nine alternate identities in charge of his emotions, which established a basis for the potential integration of identities. In the external dimensions, he showed improvements in the aspects of family conflicts and issue of school refusal. This is the first reported case of DID in an adolescent in Korea; it emphasizes the consideration of DID in the differential diagnosis of other mental illnesses such as schizophrenia, bipolar disorder, and posttraumatic stress disorder and expands the treatment opportunities for DID by sharing the procedures of ego state therapy.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.89-95
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• 2021

As the influence of fine dust on society spreads gradually, the public's interest in indoor air is increasingly rising. Air-purifying plants are drawing keen attention due to their natural purifying function enabled by plant physiology. However, as their fine dust reduction mechanism is limited to adsorption only, vegetation bio-filters that optimize purification effects through integration with air-conditioning systems is rising as an alternative. In accordance with the relevant standard test methods, this study looked into the fine dust reduction assessment method by air-conditioning airflow volume that can be used for the industrial spread of vegetation bio-filters. In the case of PM₁₀ at 300 ㎍/m³, it was in the order of EG-B(3,500CMH, 29 min.) < EG-A (2,500CMH, 37 min.) < CG(0CMH, 64 min.) for reaching the maintenance level (100 ㎍/m³) of publicly used facilities. For reaching the WHO Guideline(50 ㎍/m³) requirement, it was in the order of EG-B (51 min.) < EG-A (160 min.) < CG (170 min.). In the case of PM_2.5, it was in the order of EG-B (26 min.) < EG-A (33 min.) < CG (57 min.) for reaching the maintenance level (50 ㎍/m³) of publicly used facilities. It was in the order of EG-B (48 min) < EG-A (140 min) < CG (158 min) for reaching the WHO Guideline (25 ㎍/m³) requirement. The findings from the analysis showed that fine dust can be reduced most efficiently when the system is operated at 3,500CMH level. The limitation of this study is that due to the absence of a way of assessing the stress of plants in vegetation bio-filters, generating optimal air-conditioning air flow of the relevant system and economics analysis against the existing facility-type air purification system have been clarified, which should be explored further though follow-up studies.

• Computers and Concrete
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• v.31 no.5
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• pp.419-432
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• 2023

Beam-column joints are a critical component of reinforced concrete frame structures. They are responsible for transferring forces between adjoining beams and columns while limiting story drifts and maintaining structural integrity. During severe loading, beam-column joints deform significantly, affecting, and sometimes governing, the overall response of frame structures. While most failure modes for beam and column elements are commonly considered in plastic-hinge-based global frame analyses, the beam-column joint failure modes, such as concrete shear and reinforcement bond slip, are frequently omitted. One reason for this is the dearth of published guidance on what type of hinges to use, how to derive the joint hinge properties, and where to place these hinges. Many beam-column joint models are available in literature but their adoption by practicing structural engineers has been limited due to their complex nature and lack of practical application tools. The objective of this study is to provide a comparative review of the available beam-column joint models and present a practical joint modeling approach for integration into commonly used global frame analysis software. The presented modeling approach uses rotational spring models and is capable of modeling both interior and exterior joints with or without transverse reinforcement. A spreadsheet tool is also developed to execute the mathematical calculations and derive the shear stress-strain and moment-rotation curves ready for inputting into the global frame analysis. The application of the approach is presented by modeling a beam column joint specimen which was tested experimentally. Important modeling considerations are also presented to assist practitioners in properly modeling beam-column joints in frame analyses.

• Journal of dental hygiene science
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• v.23 no.4
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• pp.271-281
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• 2023

Background: This study aims to improve dental hygiene education by investigating the relationship between metacognition, learning flow, and problem-solving abilities in dental hygiene majors. Methods: A survey was conducted on 2nd to 4th-year students from dental hygiene programs, with 132 responses analyzed. Data analysis involved t-tests and ANOVA to examine the differences in metacognition, learning flow, and problem-solving abilities based on the general characteristics. Multiple regression analysis was employed to investigate the factors influencing the dependent variable, which is problem-solving abilities. The collected data were analyzed using SPSS. Results: First, when comparing metacognition, learning flow, and problem-solving abilities based on the general characteristics of the study participants, statistically significant differences were observed in common factors such as major satisfaction, subjective academic performance, GPA (grade point average), and reason for major choice (p<0.05). Second, it was found that there is a significant positive correlation between metacognition, learning flow, and problem-solving abilities in dental hygiene students (r≥0.79, p<0.05). In other words, higher levels of metacognition and learning flow were associated with better problem-solving abilities. Third, factors influencing problem-solving abilities were identified, with both metacognition and learning flow having a statistically significant positive impact. It was also noted that metacognition had a greater influence on problem-solving abilities compared to learning flow (adjusted R²=0.815, p<0.05). Conclusion: To enhance the core competency of problem-solving abilities, it is essential to improve metacognition and learning flow. To enhance metacognition and promote learning flow, strategies such as goal setting, utilizing effective learning methods, boosting self-efficacy, managing the learning environment, choosing activities that foster immersion, stress management, self-assessment and feedback integration, improving focus, and utilization a variety of learning experiences will be necessary.

• Advances in nano research
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• v.16 no.6
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• pp.623-638
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• 2024

This study investigates the thermal post-buckling behavior of concrete eccentric annular sector plates reinforced with graphene oxide powders (GOPs). Employing the minimum total potential energy principle, the plates' stability and response under thermal loads are analyzed. The Haber-Schaim foundation model is utilized to account for the support conditions, while the transform differential quadrature method (TDQM) is applied to solve the governing differential equations efficiently. The integration of GOPs significantly enhances the mechanical properties and stability of the plates, making them suitable for advanced engineering applications. Numerical results demonstrate the critical thermal loads and post-buckling paths, providing valuable insights into the design and optimization of such reinforced structures. This study presents a machine learning algorithm designed to predict complex engineering phenomena using datasets derived from presented mathematical modeling. By leveraging advanced data analytics and machine learning techniques, the algorithm effectively captures and learns intricate patterns from the mathematical models, providing accurate and efficient predictions. The methodology involves generating comprehensive datasets from mathematical simulations, which are then used to train the machine learning model. The trained model is capable of predicting various engineering outcomes, such as stress, strain, and thermal responses, with high precision. This approach significantly reduces the computational time and resources required for traditional simulations, enabling rapid and reliable analysis. This comprehensive approach offers a robust framework for predicting the thermal post-buckling behavior of reinforced concrete plates, contributing to the development of resilient and efficient structural components in civil engineering.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Journal of Society of Preventive Korean Medicine
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• v.28 no.2
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• pp.99-111
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• 2024

Objectives : Anxiety is an important mental health symptom associated with healthcare utilization. This research aims to identify the demographic, socio-economic, and health-related factors associated with the use of Korean medicine (KM) treatments in adults experiencing anxiety. Methods : We conducted a cross-sectional analysis using the Korea Health Panel Annual Data 2019. Logistic regression models were employed to examine the relationships between KM utilization and various factors such as economic activity, perceived stress levels, and presence of physical discomfort. The study sample included 552 adults experiencing anxiety. Results : Among the subjects, 19.20% were using both conventional treatment and KM treatment. The analysis revealed that individuals engaged in economic activities were more likely to use KM treatments compared to those who were not (odds ratio [OR] = 2.207, 95% confidential interval [CI] = 1.316 to 3.699). Additionally, individuals reporting high levels of pain or discomfort showed a significantly higher likelihood of using both KM and conventional medical services (OR = 2.933, 95% CI = 1.645 to 5.231). Musculoskeletal conditions were the most common reason for KM utilization among the study participants. Conclusion : The findings suggest that economic activity and the severity of physical discomfort significantly influence the use of KM treatments among adults with anxiety. These insights could inform healthcare policy and the integration of KM services into broader health management strategies for anxiety.