• Advances in nano research
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• v.12 no.1
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• pp.101-115
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• 2022

Some researchers pointed out that the nonlocal cantilever models do not predict the dynamic softening behavior for nanostructures (including nanobeams) with clamped-free (CF) ends. In contrast, some indicate that the nonlocal cantilever models can capture the stiffness softening characteristics. There are substantial differences on this issue between them. The vibration analysis of porosity-dependent functionally graded nanoscale tubes with variable boundary conditions is investigated in this study. Using a modified power-law model, the tube's porosity-dependent material coefficients are graded in the radial direction. The theory of nonlocal strain gradients is used. Hamilton's principle is used to derive the size-dependent governing equations for simply-supported (S), clamped (C) and clamped-simply supported (CS). Following the solution of these equations by the extended differential quadrature technique, the effect of various factors on vibration issues was investigated further. It can be shown that these factors have a considerable effect on the vibration characteristics. It also can be found that our numerical results can capture the unexpected softening phenomena for cantilever tubes.

• Journal of Drive and Control
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• v.20 no.1
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• pp.34-40
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• 2023

The agricultural tractor ROPS test method according to OECD code 4 is a test to assess whether the driver's safety area can be secured when a tractor overturns, and reliability should be ensured. In this study, a model formula and procedure for calculating measurement uncertainty expressing reliability in the field of agricultural machinery testing were established according to the ISO/IEC Guide 98-3:2008. The characteristics of the ROPS test device were assessed and repeated tests were performed, and the were used as factors to calculate the measurement uncertainty. As a result of repeated tests, the accuracy was higher than 1.9 % in all load directions; thus, they were, applied to calculate the type A standard uncertainty. The final expanded uncertainty was calculated within the range of less than ± 7.76 kN of force and ± 6.96 mm of deformation in all load directions.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.91-94
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• 2023

According to most experts and health workers, a living creature's body heat is little understood and crucial in the identification of disorders. Doctors in ancient medicine used wet mud or slurry clay to heal patients. When either of these progressed throughout the body, the area that dried up first was called the infected part. Today, thermal cameras that generate images with electromagnetic frequencies can be used to accomplish this. Thermography can detect swelling and clot areas that predict cancer without the need for harmful radiation and irritational touch. It has a significant benefit in medical testing because it can be utilized before any observable symptoms appear. In this work, machine learning (ML) is defined as statistical approaches that enable software systems to learn from data without having to be explicitly coded. By taking note of these heat scans of breasts and pinpointing suspected places where a doctor needs to conduct additional investigation, ML can assist in this endeavor. Thermal imaging is a more cost-effective alternative to other approaches that require specialized equipment, allowing machines to deliver a more convenient and effective approach to doctors.

• Advances in nano research
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• v.14 no.2
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• pp.155-164
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• 2023

Grain size in sheet metals in one of the main parameters in determining formability. Grain size control in industry requires delicate process control and equipment. In the present study, effects of grain size on the formability of steel sheets is investigated. Experimental investigation of effect of grain size is a cumbersome method which due to existence of many other effective parameters are not conclusive in some cases. On the other hand, since the average grain size of a crystalline material is a statistical parameter, using traditional methods are not sufficient for find the optimum grain size to maximize formability. Therefore, design of experiment (DoE) and artificial intelligence (AI) methods are coupled together in this study to find the optimum conditions for formability in terms of grain size and to predict forming limits of sheet metals under bi-stretch loading conditions. In this regard, a set of experiment is conducted to provide initial data for training and testing DoE and AI. Afterwards, the using response surface method (RSM) optimum grain size is calculated. Moreover, trained neural network is used to predict formability in the calculated optimum condition and the results compared to the experimental results. The findings of the present study show that DoE and AI could be a great aid in the design, determination and prediction of optimum grain size for maximizing sheet formability.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.1
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• pp.11-22
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• 2023

Bone densitometry is a disease in which bones are easily broken due to metabolic bone disease, and DXA is used as a clinical standard test. Although DXA is a good method with good accuracy and reproducibility, it is frequently subject to test errors in testing and result analysis and analysis. Therefore, it is important to recognize the error issues that radiologists should basically be aware of when performing bone density tests, prevent erroneous diagnoses and treatments resulting from the results, and reduce the unnecessary costs associated with them. aim. The inspection must be carried out if the quality control of the equipment is basically continuously performed well before the inspection. Before starting the examination, the patient's age, sex, race, weight, pregnancy status, and any foreign objects that can be removed should be checked, and the examination should be performed in the correct posture. In addition, it is important to analyze results consistently. Radiologists, who play the most important role in ensuring accurate examinations, need to be aware of the potential for errors in advance and develop the ability to deal with the potential for errors in each examination. For that reason, regular education is considered essential.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.705-714
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• 2023

In order to establish a dynamic model test method of bridge pylons subjected to ocean waves, the similarity method of hydroelastic model test for bridge pylons were analyzed systematically, and a model design and production method was proposed. Using this method, a dynamic test model of a bridge pylon was made, and then a free vibration test on the model structure and a dynamic response test of the model structure under wave actions were conducted in a wave flume. The results of the free vibration test show that the primary natural frequencies of the structure by the model test are close to the design frequencies of the prototype structure, indicating that the dynamic characteristics of the bridge pylon are well simulated by the model structure. The results of the dynamic response test show that wave induced base shear forces and motion responses on the model structure are consistent with the numerical results of the prototype structure. The model test results confirm that the proposed model test design method is feasible and applicable. It has application and reference significances for model testing studies of such marine bridge structures.

• Genomics & Informatics
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• v.21 no.2
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• pp.24.1-24.7
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• 2023

Assays of clinical diagnosis and species identification using molecular markers are performed according to a quantitative method in consideration of sensitivity, cost, speed, convenience, and specificity. However, typical polymerase chain reaction (PCR) assay is difficult to quantify and have various limitations. In addition, to perform quantitative analysis with the quantitative real-time PCR (qRT-PCR) equipment, a standard curve or normalization using reference genes is essential. Within the last a decade, previous studies have reported that the digital PCR (dPCR) assay, a third-generation PCR, can be applied in various fields by overcoming the shortcomings of typical PCR and qRT-PCR assays. We selected Stilla Naica System (Stilla Technologies), Droplet Digital PCR Technology (Bio-Rad), and Lab on an Array Digital Real-Time PCR analyzer system (OPTOLANE) for comparative analysis among the various droplet digital PCR platforms currently in use commercially. Our previous study discovered a molecular marker that can distinguish Hanwoo species (Korean native cattle) using Hanwoo-specific genomic structural variation. Here, we report the pros and cons of the operation of each dPCR platform from various perspectives using this species identification marker. In conclusion, we hope that this study will help researchers to select suitable dPCR platforms according to their purpose and resources.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.153-158
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• 2017

Procurement system of public construction projects in Japan is changing with diversity in rapid pace. The quality assurance and risk management of construction projects should be more certain as the projects are turning into larger scale and more complexed. The clients in the public sector will want to make the relation of responsibility among the client, the designer (architects and engineers), and contractor clearer in terms of role and risk. Public-Private Partnership (PPP) is one of the methods for collaboration of the public sector and the private sector in public construction projects where the public utilizes the ability and suggestion of the private. Private Finance Initiative (PFI), Design-Build-Operate (DBO), market testing, designated manager system, outsourcing of tasks in local governments are well-known as examples of PPP in Japan. Indeed, there is an obvious trend that Design-Build (DB) is adopted in public construction projects in many countries including Japan. In this paper, the public construction projects in various procurement systems are surveyed and analyzed. They are not limited within the traditional procurement, Design-bid-Build, a separate order system of design and construction. Design-Build or PFI are adopted. In particular, contract by wide range including maintenance of equipment can be found. On the other hand, modification from originally typical PFI is taking place, such as concept design and project finance are removed from the roles and the tasks of the special purpose company (SPC) in PFI. Standard roles and tasks in a construction project are modeled in this paper.

• Journal of the Korean Geosynthetics Society
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• v.22 no.4
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• pp.83-92
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• 2023

In this study, we conducted verification of key influencing factors during cone penetration testing using the developed Mini Cone Penetration Tester (Mini-CPT), and compared the experimental results with empirical formulas to validate the equipment. The Mini-CPT was designed to measure cone penetration resistance through a Strain Gauge, and the resistance values were calibrated using a Load Cell. Moreover, the influencing factors were verified using a model ground constituted in a soil box. The primary influencing factors examined were the boundary effect of the soil box, the distance between cone penetration points, and the cone penetration speed. For the verification of these factors, the experiment was conducted with the model ground having a relative density of 63.76% in the soil box. It was observed that the sidewall effect was considerably significant, and the cone penetration resistance measured at subsequent penetration points was higher due to the influence between penetration points. However, within the speed range considered, the effect of penetration speed was almost negligible. The measured cone penetration resistance was compared with predicted values obtained from literature research, and the results were found to be similar. It is anticipated that using the developed Mini-CPT for constructing model grounds in the laboratory will lead to more accurate geotechnical property data.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.253-262
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• 2024

Dynamic properties are pivotal in soil analysis, yet their experimental determination is hampered by complex methodologies and the need for costly equipment. This study aims to predict dynamic soil properties using static properties that are relatively easier to obtain, employing machine learning techniques. The static properties considered include soil cohesion, friction angle, water content, specific gravity, and compressional strength. In contrast, the dynamic properties of interest are the velocities of compressional and shear waves. Data for this study are sourced from 26 boreholes, as detailed in a geotechnical investigation report database, comprising a total of 130 data points. An importance analysis, grounded in the random forest algorithm, is conducted to evaluate the significance of each dynamic property. This analysis informs the prediction of dynamic properties, prioritizing those static properties identified as most influential. The efficacy of these predictions is quantified using the coefficient of determination, which indicated exceptionally high reliability, with values reaching 0.99 in both training and testing phases when all input properties are considered. The conventional method is used for predicting dynamic properties through Standard Penetration Test (SPT) and compared the outcomes with this technique. The error ratio has decreased by approximately 0.95, thereby validating its reliability. This research marks a significant advancement in the indirect estimation of the relationship between static and dynamic soil properties through the application of machine learning techniques.