• Smart Structures and Systems
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• v.31 no.3
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• pp.229-245
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• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

• Geomechanics and Engineering
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• v.36 no.4
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• pp.355-366
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• 2024

The original elastoplastic Hardening Soil model is formulated actually partly under hexagonal pyramidal Mohr-Coulomb failure criterion, and can be only used in specific stress paths. It must be completely generalized under Mohr-Coulomb criterion before its usage in engineering practice. A set of generalized constitutive equations under this criterion, including shear and volumetric yield surfaces and hardening laws, is proposed for Hardening Soil model in principal stress space. On the other hand, a Mohr-Coulumb type yield surface in principal stress space comprises six corners and an apex that make singularity for the normal integration approach of constitutive equations. With respect to the isotropic nature of the material, a technique for processing these singularities by means of Koiter's rule, along with a transforming approach between both stress spaces for both stress tensor and consistent stiffness matrix based on spectral decomposition method, is introduced to provide such an approach for developing generalized Hardening Soil model in finite element analysis code ABAQUS. The implemented model is verified in comparison with the results after the original simulations of oedometer and triaxial tests by means of this model, for volumetric and shear hardenings respectively. Results from the simulation of oedometer test show similar shape of primary loading curve to the original one, while maximum vertical strain is a little overestimated for about 0.5% probably due to the selection of relationships for cap parameters. In simulation of triaxial test, the stress-strain and dilation curves are both in very good agreement with the original curves as well as test data.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.74-85
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• 2024

Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27-42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (≥ 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter. The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836-0.976) in the training dataset and 0.877 (95% confidence interval, 0.755-0.999) in the test dataset. The nomogram showed good calibration. Conclusion: Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.4
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• pp.15-27
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• 2024

Ecosystem-disturbing plant species pose a significant threat to native ecosystems due to their high reproductive capacity, making it essential to monitor their distribution and develop effective mitigation strategies. Consequently, it is crucial to enhance the evaluation of the impacts of these species in environmental impact assessments by incorporating scientific evidence alongside qualitative assessments. This study introduces a dispersal model into the species distribution model to simulate the potential spread of ecosystem-disturbing plant species, reflecting their ecological characteristics. Additionally, we developed mitigation scenarios and quantitatively calculated reduction rates to propose effective mitigation strategies. The species distribution model showed a reliable AUC (Area Under the Curve) of at least 0.890. The dispersal model's results were also credible, with 31 out of 34 validation coordinates falling within the predicted spread range. Simulating the impact of the spread of ecosystem-disturbing plant species over the next five years revealed that one project site had potential habitats for Ambrosia artemisiifolia, necessitating robust mitigation measures such as seed removal. Another project site, with potential habitats for Symphyotrichum pilosum, indicated that physical removal methods within the site were effective due to the species' relatively short dispersal distance. These findings can serve as fundamental data for project executors and reviewers in evaluating the impact of the spread of ecosystem-disturbing plant species during the planning stages of projects.

• Journal of Gastric Cancer
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• v.8 no.1
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• pp.27-34
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• 2008

Purpose: Many recent studies have reported on the feasibility and usefulness of laparoscopy assisted distal gastrectomy (LADG) for treating early gastric cancer. On the other hand, there has been few reports about laparoscopy assisted total gastrectomy (LATG) because upper located gastric cancer is relatively rare and the surgical technique is more difficult than that for LADG, We now present our procedure and results of performing LATG for the gastric cancer located in the upper or middle portion of the stomach. Materials and Methods: From Jan 2005 to Sep 2007, 96 patients underwent LATG by four surgeons at the Asan Medical Center, Seoul, Korea. Among them, 48 consecutive patients who were operated on by asingle surgeon were analyzed with respect to the clinicopathological features, the surgical results and the postoperative courses with using the prospectively collected laparoscopy surgery data. Results: There was no conversion to open surgery during LATG. For all the reconstructions, Roux-en Y esophago-jejunostomy and D1+beta lymphadenectomy were the standard procedures. The mean operation time was $212{\pm}67$ minutes. The mean total number of retrieved lymph nodes was $28.9{\pm}10.54$ (range: $12{\sim}64$) and all the patients had a clear proximal resection margin in their final pathologic reports. The mean time to passing gas, first oral feeding and discharge from the hospital was 2.98, 3.67 and 7.08 days, respectively. There were 5 surgical complications and 2 non-surgical complications for 5 (10.4%) patients, and there was no mortality. None of the patients needed operation because of complications and they recovered with conservative treatments. The mean operation time remained constant after 20 cases and so a learning curve was present. The morbidity rate was not different between the two periods, but the postoperative course was significantly better after the learning curve. Analysis of the factors contributing to the postoperative morbidity, with using logistic regression analysis, showed that the 8MI is the only contributing factor forpostoperative complications (P=0.029, HR=2.513, 95% CI=1.097-5.755). Conclusions: LATG with regional lymph node dissection for upper and middle early gastric cancer is considered to be a safe, feasible method that showed an excellent postoperative course and acceptable morbidity. BMI should be considered in the patient selection at the beginning period because of the impact of the BMI on the postoperative morbidity.

• Journal of the Korean Orthopaedic Association
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• v.54 no.5
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• pp.427-434
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• 2019

Purpose: This study evaluated the long term clinical and radiographic results and the survival rates of unicompartmental knee arthroplasty (UKA). In addition, the factors affecting the survival of the procedure were analyzed and the survival curve was compared according to the affecting factors. Materials and Methods: Ninety-nine cases of UKA performed between December 1982 and January 1996 were involved: 10 cases with Modular II, 44 cases with Microloc, and 45 cases with Allegretto prostheses. The mean follow-up period was 16.5 years. Clinically, the hospital for special surgery (HSS) scoring system and the range of motion (ROM) were evaluated. Radiographically, the femorotibial angle (FTA) was measured. The survival rate was analyzed using the Kaplan-Meier method. Cox regression analysis was used to identify the factors affecting the survival according to age, sex, body mass index, preoperative diagnosis, and type of implant. The Kaplan-Meier survival curves were compared according to the factors affecting the survival of UKA. Results: The overall average HSS score and ROM was 57.7 and 134.3° preoperatively, 92.7 and 138.4° at 1 year postoperatively, and 79.1 and 138.4° at the last follow-up (p<0.001, respectively). The overall average FTA was varus 0.8° preoperatively, valgus 4.1° at postoperative 2 weeks, and valgus 3.0° at the last follow-up. The overall 5-, 10-, 15- and 20-year survival rates were 91.8%, 82.9%, 71.0%, and 67.0%, respectively. The factors affecting the survival were the age and type of implant. The risk of the failure decreased with age (hazard ratio=0.933). The Microloc group was more hazardous than the other prostheses (hazard ratio=0.202, 0.430, respectively). The survival curve in the patients below 60 years of age was significantly lower than those of the patients over 60 years of age (p=0.003); the survival curve of the Microloc group was lower compared to the Modular II and Allegretto groups (p=0.025). Conclusion: The long-term clinical and radiographic results and survival of UKA using old fixed bearing prostheses were satisfactory. The selection of appropriate patient and prosthesis will be important for the long term survival of the UKA procedure.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.21-26
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• 2011

Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.

• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.545-555
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• 2020

A feasibility modeling for potential hydroelectric dam site selection was suggested using 1 sec ASTGTM (ASTER Global Digital Elevation Model) and Terra/Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) derived land use (MCD12Q1) data. The modeling includes DEM pre-processing of peak, sink, and flat, river network generation, watershed delineation and segmentation, terrain analysis of stream cross section and reservoir storage, and estimation of submerged area for compensation. The modeling algorithms were developed using Python and as an open source GIS. When a user-defined stream point is selected, the model evaluates potential hydroelectric head, reservoir surface area and storage capacity curve, watershed time of concentration from DEM, and compensation area from land use data. The model was tested for 4 locations of already constructed Buhang, BohyunMountain, Sungdeok, and Yeongju dams. The modeling results obtained maximum possible heads of 37.0, 67.0, 73.0, 42.0 m, surface areas of 1.81, 2.4, 2.8, 8.8 ㎢, storages of 35.9, 68.0, 91.3, 168.3×10⁶ ㎥ respectively. BohyunMountain and Sungdeok show validity but in case of Buhang and Yeongju dams have maximum head errors. These errors came from the stream generation error due to ASTGTM. So, wrong dam watershed boundary limit the head. This study showed a possibility to estimate potential hydroelectric dam sites before field investigation especially for overseas project.

• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.116-129
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• 2006

The progress of data transmission technology through the Internet has spread a variety of realistic contents. One of such contents is multi-view video that is acquired from multiple camera sensors. In general, the multi-view video processing requires encoders and decoders as many as the number of cameras, and thus the processing complexity results in difficulties of practical implementation. To solve for this problem, this paper considers a simple multi-view system utilizing a single encoder and a single decoder. In the encoder side, input multi-view YUV sequences are combined on GOP units by a video mixer. Then, the mixed sequence is compressed by a single H.264/AVC encoder. The decoding is composed of a single decoder and a scheduler controling the decoding process. The goal of the scheduler is to assign approximately identical number of decoded frames to each view sequence by estimating the decoder utilization of a Gap and subsequently applying frame skip algorithms. Furthermore, in the frame skip, efficient frame selection algorithms are studied for H.264/AVC baseline and main profiles based upon a cost function that is related to perceived video quality. Our proposed method has been performed on various multi-view test sequences adopted by MPEG 3DAV. Experimental results show that approximately identical decoder utilization is achieved for each view sequence so that each view sequence is fairly displayed. As well, the performance of the proposed method is examined in terms of bit-rate and PSNR using a rate-distortion curve.