• Anatomy and Cell Biology
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• v.56 no.2
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• pp.161-165
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• 2023

The depressor anguli oris (DAO) muscle is a thin, superficial muscle located below the corner of the mouth. It is the target for botulinum neurotoxin (BoNT) injection therapy, aimed at treating drooping mouth corners. Hyperactivity of the DAO muscle can lead to a sad, tired, or angry appearance in some patients. However, it is difficult to inject BoNT into the DAO muscle because its medial border overlaps with the depressor labii inferioris and its lateral border is adjacent to the risorius, zygomaticus major, and platysma muscles. Moreover, a lack of knowledge of the anatomy of the DAO muscle and the properties of BoNT can lead to side effects, such as asymmetrical smiles. Anatomical-based injection sites were provided for the DAO muscle, and the proper injection technique was reviewed. We proposed optimal injection sites based on the external anatomical landmarks of the face. The aim of these guidelines is to standardize the procedure and maximize the effects of BoNT injections while minimizing adverse events, all by reducing the dose unit and injection points.

• Information Systems Review
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• v.21 no.4
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• pp.31-45
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• 2019

Despite the expansion of the market of performing arts and culture, small and medium size theaters are still experiencing difficulties due to poor accessibility of information by consumers. This study proposes a machine learning based genre recommendation system as an alternative to enhance the marketing capability of small and medium sized theaters. We developed five recommendation systems that recommend three genres per customer using customer master DB and transaction history DB of domestic venues. We propose an optimal recommendation system by comparing performances of recommendation system. As a result, the recommendation system based on the ensemble model showed better performance than the single predictive model. This study applied the personalized recommendation technique which was scarce in the field of performing arts and culture, and suggests that it is worthy enough to use it in the field of performing arts and culture.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.3
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• pp.29-43
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• 2024

Legally protected species are one of the crucial considerations in the field of natural ecology when conducting environmental impact assessments (EIAs). The occurrence of legally protected species, especially 'Endangered Wildlife' designated by Ministry of Environment, significantly influences the progression of projects subject to EIA, necessitating clear investigations and presentations of their habitats. In perspective of statistics, a minimum of 30 occurrence coordinates is required for population prediction, but most of endangered wildlife has insufficient coordinates and it posing challenges for distribution prediction through modeling. Consequently, this study aims to propose modeling methodologies applicable when coordinate data are limited, focusing on Rodgersia podophylla, representing characteristics of endangered wildlife and northern plant species. For this methodology, 30 random sampling coordinates were used as input data, assuming little survey data, and modeling was performed using individual models included in BIOMOD2. After that, the modeling results were evaluated by using discrimination capacity and the reality reflection ability. An optimal modeling technique was proposed by ensemble the remaining models except for the MaxEnt model, which was found to be less reliable in the modeling results. Alongside discussions on discrimination capacity metrics(e.g. TSS and AUC) presented in modeling results, this study provides insights and suggestions for improvement, but it has limitations that it is difficult to use universally because it is not a study conducted on various species. By supporting survey site selection in EIA processes, this research is anticipated to contribute to minimizing situations where protected species are overlooked in survey results.

• Steel and Composite Structures
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• v.51 no.6
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• pp.679-695
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• 2024

This paper presents a novel technique that combines machine learning (ML) with moth-flame optimization (MFO) methods to predict the axial compressive strength (ACS) of concrete filled double skin steel tubes (CFDST) columns. The proposed model is trained and tested with a dataset containing 125 tests of the CFDST column subjected to compressive loading. Five ML models, including extreme gradient boosting (XGBoost), gradient tree boosting (GBT), categorical gradient boosting (CAT), support vector machines (SVM), and decision tree (DT) algorithms, are utilized in this work. The MFO algorithm is applied to find optimal hyperparameters of these ML models and to determine the most effective model in predicting the ACS of CFDST columns. Predictive results given by some performance metrics reveal that the MFO-CAT model provides superior accuracy compared to other considered models. The accuracy of the MFO-CAT model is validated by comparing its predictive results with existing design codes and formulae. Moreover, the significance and contribution of each feature in the dataset are examined by employing the SHapley Additive exPlanations (SHAP) method. A comprehensive uncertainty quantification on probabilistic characteristics of the ACS of CFDST columns is conducted for the first time to examine the models' responses to variations of input variables in the stochastic environments. Finally, a web-based application is developed to predict ACS of the CFDST column, enabling rapid practical utilization without requesting any programing or machine learning expertise.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.19-25
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• 2024

This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.

• Korean Journal of Materials Research
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• v.34 no.7
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• pp.321-329
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• 2024

In this work, a series of BaTiO₃-based ceramic materials, Ba(Al_0.5Nb_0.5)_xTi_1-xO₃ (x = 0, 0.04, 0.06, 0.08), were synthesized using a standard solid-state reaction technique. X-ray diffraction profiles indicated that the Al+Nb co-doping into BaTiO₃ does not change the crystal structure significantly with a doping concentration up to 8 %. The doping ions exist in Al³⁺ and Nb⁵⁺ chemical states, as revealed by X-ray photoelectron spectroscopy. The frequency-dependent complex dielectric properties and electric modulus were studied in the temperature range of 100~380 K. A colossal dielectric permittivity (>1.5 × 10⁴) and low dielectric loss (<0.01) were demonstrated at the optimal dopant concentration x = 0.04. The observed dielectric behavior of Ba(Al_0.5Nb_0.5)_xTi_1-xO₃ ceramics can be attributed to the Universal Dielectric Response. The complex electric modulus spectra indicated the grains exhibited a significant decrease in capacitance and permittivity with increasing co-doping concentration. Our results provide insight into the roles of donor and acceptor co-doping on the properties of BaTiO₃-based ceramics, which is important for dielectric and energy storage applications.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.141-147
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• 2024

Progressive photon mapping is a widely adopted rendering technique that conducts a kernel-density estimation on photons progressively generated from lights. Its hyperparameter, which controls the reduction rate of the density estimation, highly affects the quality of its rendering image due to the bias-variance tradeoff of pixel estimates in photon-mapped results. We can minimize the errors of rendered pixel estimates in progressive photon mapping by estimating the optimal parameters based on gradient-based optimization techniques. To this end, we derived the gradients of pixel estimates with respect to the parameters when performing progressive photon mapping and compared our estimated gradients with finite differences to verify estimated gradients. The gradient estimated in this paper can be applied in an online learning algorithm that simultaneously performs progressive photon mapping and parameter optimization in future work.

• Journal of Korean Neurosurgical Society
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• v.50 no.3
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• pp.166-172
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• 2011

Objective : The intralaminar screw (ILS) fixation technique offers an alternative to pedicle screw (PS) and lateral mass screw (LMS) fixation in the C7 spine. Although cadaveric studies have described the anatomy of the pedicles, laminae, and lateral masses at C7, 3-dimensional computed tomography (CT) imaging is the modality of choice for pre-surgical planning. In this study, the goal was to determine the anatomical parameter and optimal screw trajectory for ILS placement at C7, and to compare this information to PS and LMS placement in the C7 spine as determined by CT evaluation. Methods : A total of 120 patients (60 men and 60 women) with an average age of $51.7{\pm}13.6$ years were selected by retrospective review of a trauma registry database over a 2-year period. Patients were included in the study if they were older than 15 years of age, had standardized axial bone-window CT imaging at C7, and had no evidence of spinal trauma. For each lamina and pedicle, width (outer cortical and inner cancellous), maximal screw length, and optimal screw trajectory were measured, and the maximal screw length of the lateral mass were measured using m-view 5.4 software. Statistical analysis was performed using Student's t-test. Results : At C7, the maximal PS length was significantly greater than the ILS and LMS length (PS, $33.9{\pm}3.1$ mm; ILS, $30.8{\pm}3.1$ mm; LMS, $10.6{\pm}1.3$; p<0.01). When the outer cortical and inner cancellous width was compared between the pedicle and lamina, the mean pedicle outer cortical width at C7 was wider than the lamina by an average of 0.6 mm (pedicle, $6.8{\pm}1.2$ mm; lamina, $6.2{\pm}1.2$ mm; p<0.01). At C7, 95.8% of the laminae measured accepted a 4.0-mm screw with a 1.0 mm of clearance, compared with 99.2% of pedicle. Of the laminae measured, 99.2% accepted a 3.5-mm screw with a 1.0 mm clearance, compared with 100% of the pedicle. When the outer cortical and inner cancellous height was compared between pedicle and lamina, the mean lamina outer cortical height at C7 was wider than the pedicle by an average of 9.9 mm (lamina, $18.6{\pm}2.0$ mm; pedicle, $8.7{\pm}1.3$ mm; p<0.01). The ideal screw trajectory at C7 was also measured ($47.8{\pm}4.8^{\circ}$ for ILS and $35.1{\pm}8.1^{\circ}$ for PS). Conclusion : Although pedicle screw fixation is the most ideal instrumentation method for C7 fixation with respect to length and cortical diameter, anatomical aspect of C7 lamina is affordable to place screw. Therefore, the C7 intralaminar screw could be an alternative fixation technique with few anatomic limitations in the cases when C7 pedicle screw fixation is not favorable. However, anatomical variations in the length and width must be considered when placing an intralaminar or pedicle screw at C7.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.3-14
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• 2006

Music summarization means a technique which automatically generates the most importantand representative a part or parts ill music content. The techniques of music summarization have been studied with two categories according to summary characteristics. The first one is that the repeated part is provided as music summary and the second provides the combined segments which consist of segments with different characteristics as music summary in music content In this paper, we propose and evaluate two kinds of music summarization techniques. The algorithm using multi-level vector quantization which provides a repeated part as music summary gives fixed-length music summary is evaluated by overlapping ration between hand-made repeated parts and automatically generated summary. As results, the overlapping ratios of conventional methods are 42.2% and 47.4%, but that of proposed method with fixed-length summary is 67.1%. Optimal length music summary is evaluated by the portion of overlapping between summary and repeated part which is different length according to music content and the result shows that automatically-generated summary expresses more effective part than fixed-length summary with optimal length. The cluster-based algorithm using 2-D similarity matrix and k-means algorithm provides the combined segments as music summary. In order to evaluate this algorithm, we use MOS test consisting of two questions(How many similar segments are in summarized music? How many segments are included in same structure?) and the results show good performance.