• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.388-394
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• 2021

The conventional microelectromechanical system (MEMS) process has been used to fabricate sensors with high costs and high-volume productions. Emerging 3D printing can utilize various materials and quickly fabricate a product using low-cost equipment rather than traditional manufacturing processes. 3D printing also can produce the sensor using various materials and design its sensing structure with freely optimized shapes. Hence, 3D printing is expected to be a new technology that can produce sensors on-site and respond to on-demand demand by combining it with open platform technology. Therefore, this paper reviews three standard 3D printing technologies, such as Fused Deposition Modeling (FDM), Direct Ink Writing (DIW), and Digital Light Processing (DLP), which can apply to the sensor fabrication process. The review focuses on strain/load sensors having both sensing material features and structural features as well. NCPC (Nano Carbon Piezoresistive Composite) is also introduced as a promising 3D material due to its favorable sensing characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1483-1489
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• 2022

Recently, due to the influence of the 4th industrial revolution and the development of communication media, various digital video equipment are being used in industrial fields. Image data is easily damaged by noise in the process of acquiring and transmitting and receiving from the camera and sensor, and since the damaged image has a great effect on the processing of the system, noise removal is essential. In this paper, a weight filter algorithm using a weight graph is proposed to restoration images damaged by high-density impulse noise. The proposed algorithm obtains a weight graph using pixel values inside the filtering mask of the image, and restores the image by applying the final weight to the filtering mask. Simulation was conducted to analyze the noise removal performance of the proposed algorithm, and the magnified image and PSNR were used to compare with the existing method. The resulting image of the proposed algorithm showed excellent performance by removing high-density impulse noise.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.353-357
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• 2022

This article identifies the problems and substantiates the directions for the development of distance learning technologies in the training of personnel. An example of using digital media to create a remote access laboratory is given. The article is devoted to the definition of the main aspects of the organization of distance education. Rapid digitization, economic, political and social changes taking place in Ukraine necessitate the reform of the education system. First of all, it concerns meeting the educational needs of citizens throughout their lives, providing access to educational and professional training for all who have the necessary abilities and adequate training. The most effective solution to the above-mentioned problems is facilitated by distance learning. The article analyzes the essence and methods of distance learning organization, reveals the features of the use of electronic platforms for the organization of this form of education in different countries of the world. The positive characteristics of distance learning are identified, namely: extraterritoriality; savings on transport costs; the interest of modern youth in the use of information tools in everyday life; increase in the number of students; simplicity and accessibility of training; convenient consultation system; democratic relations between the student and the teacher; convenience for organizations in training their employees without interrupting their regular work; low level of payment for distance education compared to traditional education; individual learning pace; new teacher status. Among the negative features of online education, the author refers to the following problems: authentication of users during knowledge verification, calculation of the teacher's methodological load and copyright of educational materials; the high labor intensity of developing high-quality educational content and the high cost of distance learning equipment; the need to provide users with a personal computer and access to the Internet; the need to find and use effective motivation mechanisms for education seekers.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.23-32
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• 2010

U-healthcare provides people with many conveniences and keeps their health. As facility centered medical environment is being changed to patient centered one, however, various problems are emerging. These problems range from institutional problems to technological, producer related, and user related ones. The researcher took interested in problems originating from users, in particular, elderly patients and guardians taking care of an elderly patient. The main focus of this study is the direction of serious contents design for training skills in HMI of U-healthcare equipment and developing emergency coping abilities. In this study, I started from research on elderly cognitive psychology and elders' motor reactions and interconnected the characteristics of various digital content forms. The results of this study are expected to be useful for the rapidly expanding elderly population and in the U-healthcare industry.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.27-38
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• 2023

How the port, shipping, shipbuilding, and vender industries in Korea can have a seamless value chain through their digitally smooth cooperation by applying the latest information and communications technology through the "4th industrial revolution" was examined. Also considered was the proposition that the value chain should be a smart, seamless value chain among industries with successful hyperconnection. Their cooperative relationships were defined, and the crucial elements for the sustainable development of these industries were considered. As a result, the direction for achieving environmental, social, and governance management by realizing decarbonization through today's digitalization could be studied. In particular, the importance of digitization as a way to respond to the future market from the perspective of small and medium-sized enterprises and the role of digitization realized by small and medium-sized equipment companies in the overall industry were examined. The results simultaneously show the state of linkage between industries and the reason why the value chain must maintain a smooth relationship. In addition, using the lessons learned from recent failure cases from the Korean shipbuilding industry as a cornerstone, the direction for creating a strategic pathway for intelligent connection was investigated.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.184-191
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• 2022

This study aims to provide basic information necessary to find an efficient management plan for patients using auto insurance. The analysis was conducted on the five-year auto insurance medical expenses review data registered in the health care bigdata Hub from 2016 to 2020. As a result of the analysis, the number one composition ratio of auto insurance inpatient treatment expenses was treatment and surgery fees for Certified tertiary hospitals, hospitalization fees for general hospitals, hospitals and clinics, and treatment and surgery fees for oriental medical institutions and dental hospitals. outpatient treatment expenses was doctor's fee for medical institution, treatment and surgery fees for oriental medical institutions and dental hospitals. The ratio of medication, anesthesia, and special equipment significantly affected the cost of inpatient. And the ratio of physical therapy significantly affected the cost of outpatient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.210-212
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• 2021

In modern society, various digital equipment are being distributed due to the influence of the 4th industrial revolution, and they are used in a wide range of fields such as automated processes, intelligent CCTV, medical industry, robots, and drones. Accordingly, the importance of the preprocessing process in a system operating based on an image is increasing, and an algorithm for effectively reconstructing an image is drawing attention. In this paper, we propose a filter algorithm based on a combined weight value to reconstruct an image in a complex noise environment. The proposed algorithm calculates the weight according to the spatial distance and the weight according to the difference between the pixel values for the input image and the pixel values inside the filtering mask, respectively. The final output was filtered by applying the join weights calculated based on the two weights to the mask. In order to verify the performance of the proposed algorithm, we simulated it by comparing it with the existing filter algorithm.

• Steel and Composite Structures
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• v.44 no.5
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• pp.707-720
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• 2022

In the present work, bending and free vibration analyses of multilayered functionally graded (FG) graphene platelet (GPL) and fiber-reinforced hybrid composite beams are carried out using the parabolic function based shear deformation theory. Parabolic variation of transverse shear stress across the thickness of beam and transverse shear stress-free conditions at top and bottom surfaces of the beam are considered, and the proposed formulation incorporates a transverse displacement field. The present theory works only with four unknowns and is computationally efficient. Hamilton's principle has been employed for deriving the governing equations. Analytical solutions are obtained for both the bending and free vibration problems in the present work considering different variations of GPLs and fibers distribution, namely, FG-X, FG-U, FG-Λ, and FG-O for beams having simply-supported boundary condition. First, the matrix is assumed to be strengthened using GPLs, and then the fibers are embedded. Multiscale modeling for material properties of functionally graded graphene platelet/fiber hybrid composites (FG-GPL/FHRC) is performed using Halpin-Tsai micromechanical model. The study reveals that the distributions of GPLs and fibers have significant impacts on the stresses, deflections, and natural frequencies of the beam. The number of layers and shape factors widely affect the behavior of FG-GPL-FHRC beams. The multilayered FG-GPL-FHRC beams turn out to be a good approximation to the FG beams without exhibiting the stress-channeling effects.

• Structural Engineering and Mechanics
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• v.89 no.1
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• pp.1-11
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• 2024

This article introduces a novel analytical model for examining the impact of porosity on shear correction factors (SCFs) in functionally graded porous beams (FGPB). The study employs uneven and logarithmic-uneven modified porosity-dependent power-law functions, which are distributed throughout the thickness of the FGP beams. Additionally, a modified exponential-power law function is used to estimate the effective mechanical properties of functionally graded porous beams. The correction factor plays a crucial role in this analysis as it appears as a coefficient in the expression for the transverse shear stress resultant. It compensatesfor the assumption that the shear strain is uniform across the depth of the cross-section. By applying the energy equivalence principle, a general expression for static SCFs in FGPBs is derived. The resulting expression aligns with the findings obtained from Reissner's analysis, particularly when transitioning from the two-dimensional case (plate) to the one-dimensional case (beam). The article presents a convenient algebraic form of the solution and provides new case studies to demonstrate the practicality of the proposed formulation. Numerical results are also presented to illustrate the influence of porosity distribution on SCFs for different types of FGPBs. Furthermore, the article validates the numerical consistency of the mechanical property changesin FG beams without porosity and the SCF by comparing them with available results.