• Analytical Science and Technology
• /
• v.32 no.4
• /
• pp.131-138
• /
• 2019

This paper reports results on the physical properties of a powder type of $Al_2O_3:C$ commonly used as a luminescence dosimeter using the LM-OSL technique. On the analysis with the general order kinetics model, the LM-OSL signal measured appeared to be composed of three components (fast, medium, slow) showing the largest area in the medium component. The photoionization cross sections of three components were distributed between $10^{-19}{\sim}10^{-21}cm^2$. The values of the thermal assistance energy were evaluated the largest in slow component and the smallest in fast component, which indicates the electrons trapped in defects attributed to slow component should be the most sensitive to thermal vibration among three components. In illumination to blue light, the fast component showed a rapid linear decay and completely disappeared after light exposure time of about 5 s. The medium component decayed with two exponential elements but the slow component did not observed any noticeable change until light exposure time of 40 s. In a dose response study, all components exhibited a linear behaviour up to approximately 10 Gy.

• Structural Engineering and Mechanics
• /
• v.72 no.3
• /
• pp.313-327
• /
• 2019

Damage evolution in the form of void nucleation, propagation and coalescence is the primary cause that is responsible for the ductile failure of microalloyed steels. The Gurson-Tvergaard-Needleman (GTN) damage model has proven to be extremely robust for characterizing the microscopic damage behavior of ductile metals. Nonetheless, successful applications of the model on a given metal type are limited by the correct identification of damage parameters as well as the validation of the calculated void growth rate. The purpose of this study is two-fold. First, we aim to identify the damage parameters of the GTN model for Q345 steel (Chinese code), due to its extensive application in mechanical and civil industries in China. The identification of damage parameters is facilitated by the well-suited response surface methodology, followed by a complete analysis of variance for evaluating the statistical significance of the identified model. Second, taking notched Q345 cylinders as an example, finite element simulations implemented with the identified GTN model are performed in order to analyze their microscopic damage behavior. In particular, the void growth rate predicted from the simulations is successfully correlated with experimentally measured acoustic emissions. The quantitative correlation suggests that during the yielding stage the void growth rate increases linearly with the acoustic emissions, while in the strain-hardening and softening period the dependence becomes an exponential function. The combined experimental and finite element approach provides a means for validating simulated void growth rate against experimental measurements of acoustic emissions in microalloyed steels.

• Steel and Composite Structures
• /
• v.43 no.5
• /
• pp.603-623
• /
• 2022

This article is dedicated to predict the natural frequencies of joined conical shell structures made of Functionally Graded Material (FGM). The structure includes two conical segments. The equivalent material properties are found by using the rule of mixture based on Voigt model. In addition, three well-known patterns are employed for distribution of material properties throughout the thickness of the structure. The main objective of the present research is to propose a novel exponential pattern and obtain the related equivalent material properties. Furthermore, the Donnell type shell theory is used to obtain the governing equations of motion. Note that these equations are obtained by employing First-order Shear Deformation Theory (FSDT). In order to discretize the governing system of differential equations, well-known and efficient semi-analytical scheme, namely Generalized Differential Quadrature Method (GDQM), is utilized. Different boundary conditions are considered for various types of single and joined conical shell structures. Moreover, an applicable modification is considered for the continuity conditions at intersection position. In the first step, the proposed formulation is verified by solving some well-known benchmark problems. Besides, some new numerical examples are analyzed to show the accuracy and high capability of the suggested technique. Additionally, several geometric and material parameters are studied numerically.

• Smart Structures and Systems
• /
• v.29 no.3
• /
• pp.395-420
• /
• 2022

A new hybrid quasi-3D and 2D high-order shear deformation theory is studied in this mathematical formulation, for an investigation of the bending, free vibrations and buckling influences on a functionally graded material plate. The theoretical formulation has been begun by a displacement field of five unknowns, governing the transverse displacement across the thickness of the plate by bending, shearing and stretching. The transverse shear deformation effect has been taken into consideration, satisfying the stress-free boundary conditions, especially on plate free surfaces as parabolic variation through its thickness. Thus, the mechanical properties of the functionally graded plate vary across the plate thickness, following three distributions forms: the power law, exponential form and the Mori-Tanaka scheme. The mechanical properties are used to develop the equations of motion, obtained from the Hamilton principle, and solved by applying the Navier-type solution for simply supported boundary conditions. The results obtained are compared with other solutions of 2D, 3D and quasi-3D plate theories have been found in the literature.

• Bulletin of the Korean Mathematical Society
• /
• v.59 no.5
• /
• pp.1145-1166
• /
• 2022

In this paper, for a transcendental meromorphic function f and α ∈ ℂ, we have exhaustively studied the nature and form of solutions of a new type of non-linear differential equation of the following form which has never been investigated earlier: $$f^n+{\alpha}f^{n-2}f^{\prime}+P_d(z,f)={\sum\limits_{i=1}^{k}}{p_i(z)e^{{\alpha}_i(z)},$$ where P_d(z, f) is a differential polynomial of f, p_i's and α_i's are non-vanishing rational functions and non-constant polynomials, respectively. When α = 0, we have pointed out a major lacuna in a recent result of Xue [17] and rectifying the result, presented the corrected form of the same equation at a large extent. In addition, our main result is also an improvement of a recent result of Chen-Lian [2] by rectifying a gap in the proof of the theorem of the same paper. The case α ≠ 0 has also been manipulated to determine the form of the solutions. We also illustrate a handful number of examples for showing the accuracy of our results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.108-111
• /
• 2022

Applying deep learning to machine vision systems for defect detection of products requires vast amounts of training data about various defect cases. However, since data imbalance occurs according to the type of defect in the actual manufacturing industry, it takes a lot of time to collect product images enough to generalize defect cases. In this paper, we apply a Siamese neural network that can be learned with even a small amount of data to product defect detection, and modify the image pairing method and contrastive loss function by properties the situation of product defect image data. We indirectly evaluated the embedding performance of Siamese neural networks using AUC-ROC, and it showed good performance when the images only paired among same products, not paired among defective products, and learned with exponential contrastive loss.

• Geomechanics and Engineering
• /
• v.34 no.1
• /
• pp.51-67
• /
• 2023

In this research, the degradation rate of physical properties of the Angouran pit bedrock (calc-schist) is first investigated under the specific numbers of freeze-thaw (F-T) cycles. Then, the durability of calc-schist specimens against the F-T cycle number (N) is examined considering the mechanical parameters, and using the decay function and half-time techniques. For this purpose, point load strength (I_S(50)), second durability index (I_d2), Brazilian tensile strength (BTS), and compressive (V_P) and shear (V_S) wave velocities of calc-schist specimens are measured after 0, 7, 15, 40, and 75 N. For comparing the degradation rate of mechanical properties of available rock types on the Angouran mine walls, these tests are also carried out on the limestone and amphibolite schist specimens beside the calc-schist. According to test results, the exponential regression models are developed between the mechanical parameters of rock specimen's and N variable. Also, the long-term durability of each rock type versus N is studied using the decay function and half-time techniques. Results indicated that the degradation rate differs for the above rock types in which amphibolite schist and calc-schist specimens have the highest and least resistance against the N, respectively. The obtained results from this study can play a key role in the optimal design of the mine's final walls.

• Korean Journal of Artificial Intelligence
• /
• v.11 no.2
• /
• pp.19-27
• /
• 2023

In recent times, an exponential increase in Internet traffic has been observed as a result of advancing development of the Internet of Things, mobile networks with sensors, and communication functions within various devices. Further, the COVID-19 pandemic has inevitably led to an explosion of social network traffic. Within this context, considerable attention has been drawn to research on network traffic analysis based on machine learning. In this paper, we design and develop a new machine learning framework for network traffic analysis whereby normal and abnormal traffic is distinguished from one another. To achieve this, we combine together well-known machine learning algorithms and network traffic analysis techniques. Using one of the most widely used datasets KDD CUP'99 in the Weka and Apache Spark environments, we compare and investigate results obtained from time series type analysis of various aspects including malicious codes, feature extraction, data formalization, network traffic measurement tool implementation. Experimental analysis showed that while both the logistic regression and the support vector machine algorithm were excellent for performance evaluation, among these, the logistic regression algorithm performs better. The quantitative analysis results of our proposed machine learning framework show that this approach is reliable and practical, and the performance of the proposed system and another paper is compared and analyzed. In addition, we determined that the framework developed in the Apache Spark environment exhibits a much faster processing speed in the Spark environment than in Weka as there are more datasets used to create and classify machine learning models.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.36 no.6
• /
• pp.547-555
• /
• 2023

High-density crossbar arrays based on storage class memory (SCM) are ideally suited to handle an exponential increase in data storage and processing as a central hardware unit in the era of AI-based technologies. To achieve this, selector devices are required to be co-integrated with SCM to address the sneak-path current issue that indispensably arises in such crossbar-type architecture. In this perspective, we first summarize the current state of tellurium-based threshold-switching devices and recent advances in the material, processing, and device aspects. We thoroughly review the physicochemical properties of elemental tellurium (Te) and representative binary tellurides, their tailored deposition techniques, and operating mechanisms when implemented in two-terminal threshold switching devices. Lastly, we discuss the promising research direction of Te-based selectors and possible issues that need to be considered in advance.

• Journal of Korean Institute of Industrial Engineers
• /
• v.33 no.1
• /
• pp.76-85
• /
• 2007

A reliability acceptance sampling plan (RASP) consists of a set of life test procedures and rules for eitheraccepting or rejecting a collection of items based on the sampled lifetime data. Most of the existing RASPs areconcerned with the case where test items are available at the same time. However, as in the early stage ofproduct development, it may be difficult to secure test items at the same time. In such a case, it is inevitable toconduct a life test using sequentially supplied samples.In this paper, it is assumed that test items are sequentially supplied, the lifetimes of test items follow anexponential disthbution, failures are monitored continuously, arrival times of test items are known, and thenumber of test items at each arrival time is given. Under these assumptions, RASPs are developed by deter-mining the test completion time and the critical value for the maximum likelihood estimator of the mean lifetimesuch that the producer and consumer risks are satisfied. Then, the developed plans are compared to thetraditional Type-I censored RASPs in terms of the test completion time. Computational results indicate that thetest completion time of the developed RASP is shorter than that of the traditional Type-I censored plan in mostcases considered. It is also found that the superiority of the developed RASP becomes more prominent as theinter-arrival times of test items increase and/or the total number of test items gets larger.