• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.291-298
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• 2019

In this paper, we propose a Fresnel transform method using various wavelet functions to efficiently decompose digital holograms. After implementing the proposed wavelet function-based Fresnelet transforms, we apply it to the digital hologram and analyze the energy characteristics of the coefficients. The implemented wavelet transform-based Fresnelet transform is well suited for reconstructing and processing holograms which are optically obtained or generated by computer-generated hologram technique. After analyzing the characteristics of the spline function, we discuss wavelet multiresolution analysis method based on it. Through this process, we proposed a transform tool that can effectively decompose fringe patterns generated by optical interference phenomena. We implement Fresnelet transform based on wavelet function with various decomposition properties and show the results of decomposing fringe pattern using it. The results show that the energy distribution of the coefficients is significantly different depending on whether the random phase is included or not.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.903-909
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• 2018

In this paper, performance analysis of machine vision techniques is presented to improve the convenience and speed of automatic inspection in the industrial field when machine vision is applied to the image not taken in the stationary state, but in the moving state on a conveyer. When the length of cylindrical rods used for automobiles was measured using the edge detection method, the conveying speed increased, and the uncertainty of the boundary between the background and the part image increased, which resulted in a shorter image of the object taken. This paper proposes a linear compensation method to predict the biased errors of the length measurements after examining the pattern of biased and random errors, respectively, with 6 different types of specimens and 7 velocity stages. The length measurement corrected by the linear compensation method had the same accuracy as the stationary state within the speed range of 30 cm/s and could enhance the application capability in automatic inspections.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.1-8
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• 2019

This paper carried out a study to reduce damage from jellyfish whose population has increased due to global warming. The emergence of jellyfish on the beach could result in casualties from jellyfish stings and economic losses from closures. This paper confirmed from the preceding studies that the pattern of jellyfish's appearance is predictable through machine learning. This paper is an extension of The prediction model of emergence of Busan coastal jellyfish using SVM. In this paper, we used deep neural network to expand from the existing methods of predicting the existence of jellyfish to the classification by index. Due to the limitations of the small amount of data collected, the 84.57% prediction accuracy limit was sought to be resolved through data expansion using bootstraping. The expanded data showed about 7% higher performance than the original data, and about 6% better performance compared to the transfer learning. Finally, we used the test data to confirm the prediction performance of jellyfish appearance. As a result, although it has been confirmed that jellyfish emergence binary classification can be predicted with high accuracy, predictions through indexation have not produced meaningful results.

• The korean journal of orthodontics
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• v.52 no.3
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• pp.182-200
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• 2022

Objective: This study aims to examine the effectiveness of miniscrew assisted rapid palatal expansion (MARPE) treatment in late adolescents and adult patients using cone-beam computed tomography (CBCT). Methods: Literature search was conducted in five electronic databases (PubMed, Embase, Scopus, Web of Science, and Cochrane Library) based on the PICOS keyword design focusing on MARPE. Out of the 18 CBCT screened outcomes, only nine parameters were sufficient for the quantitative meta-analysis. The parameters were classified into three main groups: 1) skeletal changes, 2) alveolar change, and 3) dental changes. Heterogeneity test, estimation of pooled means, publication bias, sensitivity analysis and risk of bias assessment were also performed. Results: Upon database searching, only 14 full-text articles were qualified from the 364 obtained results. Heterogeneity test indicated the use of the random-effects model. The pooled mean estimate were as follows: 1) Skeletal expansion: zygomatic width, 2.39 mm; nasal width, 2.68 mm; jugular width, 3.12 mm; and midpalatal suture at the posterior nasal spine and anterior nasal spine, 3.34 mm and 4.56 mm, respectively; 2) Alveolar molar width expansion, 4.80 mm; and 3) Dental expansion: inter-canine width, 3.96 mm; inter-premolar width, 4.99 mm and inter-molar width, 5.99 mm. The percentage of expansion demonstrated a skeletal expansion (PNS) of 55.76%, alveolar molar width expansion of 24.37% and dental expansion of 19.87%. Conclusions: In the coronal view, the skeletal and dental expansion created by MARPE was of the pyramidal pattern. MARPE could successfully expand the constricted maxilla in late adolescents and adult patients.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.235-242
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• 2021

Recently, many human activity recognition(HAR) researches using smartphone sensor data have been studied. HAR can be utilized in various fields, such as life pattern analysis, exercise measurement, and dangerous situation detection. However researches have been focused on recognition of basic human behaviors or efficient battery use. In this paper, exercising activities performed indoors and outdoors were defined and recognized. Data collection and pre-processing is performed to recognize the defined activities by SVM, random forest and gradient boosting model. In addition, the recognition result is determined based on voting class approach for accuracy and stable performance. As a result, the proposed activities were recognized with high accuracy and in particular, similar types of indoor and outdoor exercising activities were correctly classified.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.293-309
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• 2022

Purpose - The purpose of this study is to explore the possibility of predicting the degree of smartphone overdependence based on mobile phone usage patterns. Design/methodology/approach - In this study, a survey conducted by Korea Internet and Security Agency(KISA) called "problematic smartphone use survey" was analyzed. The survey consists of 180 questions, and data were collected from 29,712 participants. Based on the data on the smartphone usage pattern obtained through the questionnaire, the smartphone addiction level was predicted using machine learning techniques. k-NN, gradient boosting, XGBoost, CatBoost, AdaBoost and random forest algorithms were employed. Findings - First, while various factors together influence the smartphone overdependence level, the results show that all machine learning techniques perform well to predict the smartphone overdependence level. Especially, we focus on the features which can be obtained from the smartphone log data (without psychological factors). It means that our results can be a basis for diagnostic programs to detect problematic smartphone use. Second, the results show that information on users' age, marriage and smartphone usage patterns can be used as predictors to determine whether users are addicted to smartphones. Other demographic characteristics such as sex or region did not appear to significantly affect smartphone overdependence levels. Research implications or Originality - While there are some studies that predict smartphone overdependence level using machine learning techniques, but the studies only present algorithm performance based on survey data. In this study, based on the information gain measure, questions that have more influence on the smartphone overdependence level are presented, and the performance of algorithms according to the questions is compared. Through the results of this study, it is shown that smartphone overdependence level can be predicted with less information if questions about smartphone use are given appropriately.

• Archives of Plastic Surgery
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• v.49 no.6
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• pp.773-781
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• 2022

Anatomies of the vascular and lymphatic systems have been vital research topics in reconstructive surgery. Harvey was a pioneer who provided the earliest descriptions of the cutaneous vasculature in the 17th century. The concept of vascular territories of the skin was first described by Manchot. The radiographic injection method in cadavers was developed by Salman, who defined more than 80 vascular territories. The arterial system has been thoroughly investigated with the development of regional and free flaps. The concept of axial and random pattern flaps was introduced by McGregor and Morgan. Manchot's vascular territories were refined by Taylor and Palmer as the angiosome concept. Detailed information about the venous circulation is essential for reconstructive surgeries. The concept of intrinsic and extrinsic venocutaneous vascular systems was introduced by Nakajima and led to the development of the venoadipofascial flap. The importance of venous augmentation in flap survival was emphasized by Chang. The lymphatic system was discovered much later than the arterial and venous systems. Aselli was credited for discovering the lacteal vessels in the 17th century; mercury was popularly used as a contrast agent to distinguish lymphatic vessels for the next three centuries. A radiographic method in cadavers was developed by Suami. Lymphatic imaging devices are constantly upgrading, and photoacoustic imaging was recently introduced for three-dimensional visualization of architecture of superficial layers of the lymphatic and venous systems.

• Journal of Forest and Environmental Science
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• v.26 no.3
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• pp.149-159
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• 2010

This paper analyzes data on the composition, status, diversity, and distribution pattern of invasive forest undergrowth in a protected area (Khadimnagar National Park) of Northeastern Bangladesh. Assessment was done by means of stratified random sampling to diversify the invasive forest undergrowth species. For vegetation survey, 45 plots were taken randomly in ($2m{\times}2m$) circular plot from three topographical regions namely top of the hill, middle slope and plain land (15 plots from each region) and a total of 715 individuals, 22 invasive species belonging to 17 families were recorded from the study site. Among invasive species, shrubs constitute 10 species, herbs 9 species, and vines 3 species respectively. Mass number of invasive undergrowth species was grows in plain land (45.45%) followed by middle slope (31.82%). Based on the survey, invasive undergrowth plants of study areas were also categorized into three degrees of invasiveness e.g., highly invasive, moderately invasive and potentially invasive. Herbs, shrubs, and vines constitute the highest density at Chromolaema odorata (Linn.) King. (1.09), relative density at Chromolaema odorata (Linn.) King. 6.85%; highest and lowest frequency was calculated at Cassia alata L. (64.44%) and Diplazium esculentum (24.44%); for relative frequency the highest was Cassia alata L., which occupies 6.64%. Determination of the abundance of the different species revealed that Cassia alata L., constitutes (3.36) followed by Pteris cretica Wilsonii (3.14) of the area. The presence of invasive undergrowth species always reduced the number of associated species. Therefore, an extensive in-depth long-term investigation, proper policy formulation and management interventions and further study and continuous monitoring on their impacts need to be triggered targeting the control of the invasive undergrowth species of this protected area. In this aspect, national and international organization could help to conserve its biodiversity.

• Korean Journal of Clinical Pharmacy
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• v.33 no.3
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• pp.195-201
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• 2023

Background: Hematocrit is usually measured from venous blood collected by invasive venipuncture. This study was performed to determine hematocrit accurately and precisely using minimally invasive volumetric absorptive microsampling (VAMS) technique. Such technique is to be applied to determining hematocrit in various clinical settings for the care, including therapeutic drug monitoring, of neonatal or epileptic patients, or patients with high risk of infection or bleeding. Methods: The study was performed using 31 VAMS samples obtained from 21 pancreatic cancer patients. Hematocrit was determined using the values of potassium concentrations obtained from blood in VAMS tips (Hct_VAMS). Hct_VAMS was compared with hematocrit measured from blood collected by venipuncture (Hct_VP). The accuracy and precision of Hct_VAMS in comparison to Hct_VP were evaluated using Bland-Altman plot, Deming regression and mountain plot. Results: Bland-Altman plot displayed a random scattering pattern of the differences between Hct_VAMS and Hct_VP with the mean bias of -0.010 and the 95% limit of agreement ranging from -0.063 to 0.044. Deming regression for Hct_VAMS and Hct_VP line demonstrated very small proportional and constant biases of 1.04 and -0.003, respectively. Mountain plot exhibited a narrow and symmetrical distribution of the differences with their median of -0.011 and central 95% range from -0.049 to 0.033. Conclusion: Hematocrit was accurately and precisely determined using less invasive VAMS technique. Such technique appears to be applicable to determining hematocrit in situations that venipuncture is not favorable or possible.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.1
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• pp.37-47
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• 2023

A new clamped mechanical splice system was proposed to develop structural performance and constructability for precast concrete connections. The proposed mechanical splice resists external loading immediately after the engagement. The mechanical splices applicable for both large-scale rebars for plants and small-scale rebars for buildings were developed with the same design concept. Quasi-static lateral cyclic loading tests were conducted with reinforced and precast concrete members to verify the seismic performance. Also, shaking table tests with three types of seismic wave excitation, 1) random wave with white noise, 2) the 2016 Gyeongju earthquake, and 3) the 1999 Chi-Chi earthquake, were conducted to confirm the dynamic performance. All tests were performed with real-scale concrete specimens. Sensors measured the lateral load, acceleration, displacement, crack pattern, and secant system stiffness, and energy dissipation was determined by lateral load-displacement relation. As a result, the precast specimen provided the emulative performance with RC. In the shaking table tests, PC frames' maximum acceleration and displacement response were amplified 1.57 - 2.85 and 2.20 - 2.92 times compared to the ground motions. The precast specimens utilizing clamped mechanical splice showed ductile behavior with energy dissipation capacity against strong motion earthquakes.