• Journal of Biomedical Engineering Research
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• 제25권6호
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• pp.455-464
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• 2004

Total hip arthroplasty(THA) considerably depends on high-experienced doctors because of high difficulty of the operation. Selection of acetabular cup's and femoral implant's position is closely related with success or failure of THA. Nevertheless the selection has usually depended on doctor's eye measurement, which makes the position accuracy of artificial joint lower after THA, often resulting in revision of THA. The present study determined a method to select accurately the position of acetabular cup and femoral implant through surgical simulation with 3D characteristic geometrical information of patient's pelvis and femur. We examined the change of femoral anteversion angle and neck-shaft angle accompanied by the change of acetabular cup's position and the insertion position of femoral implant. As result of analyzing geometrical information through different surgical simulations, we found that it was possible to select the accurate position of acetabular cup and femoral implant. It is expected to help doctors get experienced in THA operation through repetitive surgical simulations using the method suggested in the study.

• Congress of the korean instutite of fire investigation
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• 한국화재조사학회 2011년도 제21회 춘계학술대회
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• pp.102-116
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• 2011

With the spread of FMD and AI in the country livestock farmers have used lime(CaO) prevalently and due to incorrect storage lime served as a fire ignition source in a number of cases. As combined chemically with water, lime has exothermic reaction. Then In these experiments we want to know how exothermic reaction - caused by lime - acts as sources of fire ignition in any circumstances and conditions. So we have done experimental work of ignition temperature and ignition process in the artificial conditions as lime combined chemically with water. As a result, we have confirmed that lime could be flammable material sufficiently as a fire ignition source with the proper presence of heat and moisture conditions. If the lime served as sources of fire ignition, as identification techniques of fire scene, we must ascertain the existence of water, flammable material and Calcium Hydroxide($Ca(OH)_2$). We should take special precautions in order to prevent fire and educate the safe handling of lime to the manufacturer and agricultural cooperative's joint livestock farmers who product or use lime.

• Nutrition Research and Practice
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• 제13권6호
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• pp.480-487
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• 2019

BACKGROUND/OBJECTIVES: Osteoarthritis (OA) is a major public health issue in Japan and other countries, and foods that prevent or treat OA are in strong demand. Proteins and peptides in chicken meat and bones are known for being rich in functional and nutritional ingredients for the improvement of osteoporosis. We speculated that chicken legs, a food consumed in many regions of the world, may also contain such ingredients. In this study, we aim to (i) evaluate the effect of chicken leg extract (CLE) on the promotion of cartilage matrix production and (ii) identify the active ingredient in CLE that contributes to this function. MATERIALS/METHODS: Artificial CLE digest was prepared, and the acid mucopolysaccharide production-promoting activity of the CLE digest was evaluated by alcian blue staining of ATDC5 cells. CLE was orally administered to rabbits with burr holes in the knee joint of the femur, and the degree of regeneration of cartilage matrix was evaluated. Furthermore, we investigated orally administered CLE-derived peptides in human plasma using LC-MS. From measuring the acid mucopolysaccharide production-promotion activity of these peptides, a molecule considered to be an active ingredient in the CLE digest was identified. RESULTS: CLE digest promoted acid mucopolysaccharide production and facilitated regeneration of cartilage matrix in in vitro and in vivo experiments. Four peptides including phenylalanyl-hydroxyproline (Phe-Hyp) were detected as CLE-derived peptides in human plasma. The effect of CLE was inferred to be due to Phe-Hyp, which was confirmed to be present in the CLE digest. CONCLUSIONS: It was shown that CLE stimulated the production of articular cartilage matrix both in vitro and in vivo, and that CLE could be an effective food for preventing or treating OA. Furthermore, only Phe-Hyp was confirmed as the active compound in the CLE digest, suggesting that the activity of CLE was due to Phe-Hyp.

• Clinics in Orthopedic Surgery
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• 제10권4호
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• pp.427-432
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• 2018

Background: The purpose of this study was to evaluate the usefulness of sonication technique for microbiological diagnosis and the sterility of the recycled autoclaved femoral components from infected total knee arthroplasty (TKA) using a sonication method. Methods: Nineteen femoral implants explanted from patients with infected TKA were sterilized with a standard autoclave method. Standard culture of the fluid before and after sonication of the sterilized implants was performed to detect pathogenic microorganisms. Additional experiments were performed to evaluate the sterility of the recycled implant by inducing artificial biofilm formation. Methicillin-resistant Staphylococcus aureus (MRSA) was inoculated into 10 implants and sterilization in a standard autoclave was performed, and then the fluid was cultured before and after sonication. Results: Two of the 19 sterilized implants were positive for growth of bacteria after sonication, whereas no growth was detected in the cultured fluid from the sterilized implants before sonication. The bacteria were Staphylococcus species in all two cases. In one of 10 implants inoculated with MRSA, the culture was positive for growth of bacteria both before and after sonication. However, Staphylococcus epidermidis was cultured from both occasions and thus this implant was thought to be contaminated. Conclusions: We found sonication for identification of pathogens could be helpful, but this finding should be interpreted carefully because of the possibility of contamination. Sterilization of an infected femoral implant with an autoclave method could be a good method for using the temporary articulating antibiotic spacer in two-stage revision arthroplasty.

• Journal of the Korean Crystal Growth and Crystal Technology
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• 제28권6호
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• pp.250-255
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• 2018

The CoCrMo as-built alloys prepared by 3D-printing process are studied on tensile strength, wear resistance, crystal structure and microstructure after complex heat-treatment including HIP. In this study, HIP treatment for removing micropores, ambient heat-treatment for formation of metal carbides, and solution heat-treatment for homogenization of the created metal carbides were tried and characterized for applying to artificial joint. The complex heat-treatment effects of the CoCrMo as-built alloys prepared by 3D-printing process were owing to the densification during HIP, formation of metal carbides and homogenization of the created metal carbides. The effects of the complex heat-treatment were confirmed by XRD, FE-SEM and EDS.

• The Journal of the Convergence on Culture Technology
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• 제5권1호
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• pp.77-82
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• 2019

AI is applied increasingly to overall industries such as living, medical, financial service, autonomous car, etc. thanks to rapid technology development. AI-leading countries are strengthening their competency to secure competitiveness since AI is positioned as the core technology in $4^{th}$ Industrial Revolution. Although Korea has the competitive IT infra and human resources, it lags behind traditional AI-leaders like United States, Canada, Japan and, even China which devotes all its might to develop intelligent technology-intentive industry. AI is the critical technology influencing on the national industry in the near future according to advancement of intelligent information society so that concentration of capability is required with national interest. Also, joint development with global AI-leading companies as well as development of own technology are crucial to prevent technology subordination. Additionally, regulatory reform and preparation of related law are very urgent.

• The Research Journal of the Costume Culture
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• 제29권6호
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• pp.779-794
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• 2021

In this study, the sales status of female ball-jointed dolls and their parts were investi- gated and analyzed. Baseline data from 194 products and 54 brands on domestic and international Internet sites was gathered for the manufacture of ball-jointed dolls and the development of prototype costumes for them. The results are as follows. First, the sizes used for ball-jointed dolls are SD, USD, MSD, 13SD, and 70SD together with height. This study analyzed 39 sizes (15~70cm) by classifying them into numbered groups: 1 (15~22cm), 2 (23~33cm), 3 (35~51cm), 4 (53~62cm), and 5 (63~70cm). The price varied depending on the size; for example, 50cm dolls were approximately 45,000 won, while limited editions were sold at high prices, regardless of their size. They were classified into designs according to their body proportions and facial features as follows: 7- or 8-head-figure, 5-head figure, and 3-head figure, and were presented proportionally as images of women, adolescents, and infants. Second, the head was incised so that the top could be removed horizontally or the facial region vertically, allowing attachment of the eyeballs (which were either glass, resin, or acrylic) to the inside. More than 30 different colors were sold. Various wig styles were provided, including cut, short hair, and perm. These were made from human hair, heat-resistant fiber, and artificial hair. For the hands, there was a design expressing human hand gestures. For the feet, heels were in the form of wearing either high-heels or flat soles.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.193-202
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• 2022

The classification of hyperspectral imagery (HSI) is essential in the surface of earth observation. Due to the continuous large number of bands, HSI data provide rich information about the object of study; however, it suffers from the curse of dimensionality. Dimensionality reduction is an essential aspect of Machine learning classification. The algorithms based on feature extraction can overcome the data dimensionality issue, thereby allowing the classifiers to utilize comprehensive models to reduce computational costs. This paper assesses and compares two HSI classification techniques. The first is based on the Joint Spatial-Spectral Stacked Autoencoder (JSSSA) method, the second is based on a shallow Artificial Neural Network (SNN), and the third is used the SVM model. The performance of the JSSSA technique is better than the SNN classification technique based on the overall accuracy and Kappa coefficient values. We observed that the JSSSA based method surpasses the SNN technique with an overall accuracy of 96.13% and Kappa coefficient value of 0.95. SNN also achieved a good accuracy of 92.40% and a Kappa coefficient value of 0.90, and SVM achieved an accuracy of 82.87%. The current study suggests that both JSSSA and SNN based techniques prove to be efficient methods for hyperspectral classification of snow features. This work classified the labeled/ground-truth datasets of snow in multiple classes. The labeled/ground-truth data can be valuable for applying deep neural networks such as CNN, hybrid CNN, RNN for glaciology, and snow-related hazard applications.

• Journal of Korea Multimedia Society
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• 제25권8호
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• pp.1212-1223
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• 2022

Skin lesions are common diseases that range from skin rashes to skin cancer, which can lead to death. Note that early diagnosis of skin diseases can be important because early diagnosis of skin diseases considerably can reduce the course of treatment and the harmful effect of the disease. Recently, the development of computer-aided diagnosis (CAD) systems based on artificial intelligence has been actively made for the early diagnosis of skin diseases. In a typical CAD system, the accurate classification of skin lesion types is of great importance for improving the diagnosis performance. Motivated by this, we propose a novel deep ensemble classification with multi-scale attention networks. The proposed deep ensemble networks are jointly trained using a single loss function in an end-to-end manner. In addition, the proposed deep ensemble network is equipped with a multi-scale attention mechanism and segmentation information of the original skin input image, which improves the classification performance. To demonstrate our method, the publicly available human skin disease dataset (HAM 10000) and the private animal skin lesion dataset were used for the evaluation. Experiment results showed that the proposed methods can achieve 97.8% and 81% accuracy on each HAM10000 and animal skin lesion dataset. This research work would be useful for developing a more reliable CAD system which helps doctors early diagnose skin diseases.

• Advances in aircraft and spacecraft science
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• 제10권6호
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• pp.495-519
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• 2023

The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.