• 가정과삶의질연구
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• 제21권2호
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• pp.131-144
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• 2003

Selective Optimization with Compensation (SOC), a concept defined by Baltes and Baltes, is known to predict successful aging. This study was conducted to find out which factors affect Korean elderly people SOC The data for this study were obtained from a survey conducted between March and May 2001, on a sample of middle-class male and female participants over 60 years old. Two hundred and fifty four completed questionnaires were used for final analyses. Descriptive statistics, t-test, ANOVA, Duncan test, Pearson correlations, multiple regressions, multiple response frequencies and sequential threshold methods were used to analyze the data. In order to measure successful aging, the Selective Optimization with Compensation Scale developed by Baltes, Baltes, Freud, and Lang (1996) was used. The SOC scale consists of four subscales, Elective Selection, Loss-based Selection, Optimization, and Compensation. The major findings are summarized in the following. First, the level of SOC by various socio-demographic variables was examined. It tuned out that health status is the most important variable in predicting SOC. Also important was satisfaction with family life. Second, significant correlations were found between SOC and duration of the marriage (negative), practicing a religion, health, and economic stability (all positive). Third, religion and health status affected SOC, but health was a stronger predictor Those who practiced a religion and were healthy had a higher score in SOC as a whole. Fourth, the participants were divided into three groups by their SOC score, and their idea.; of successful aging were compared. The top- and middle-score groups considered satisfaction with family life to be more important, whereas the bottom-score group regarded the social status as more important.

• 대한치과교정학회지
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• 제52권6호
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• pp.387-398
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• 2022

Objective: Controlling the incisal inclination is fundamental in orthodontics. However, the relationship between the inclination prescription and its clinical outcome is not obvious, and the incisal inclination changes generated by different bracket prescriptions were investigated. Methods: Twenty-eight non-extraction dental Class II patients (15 females, 13 males; mean age = 12.9) were retrospectively analyzed. Patients were treated using passive self-ligating fixed appliances with three inclination prescriptions for maxillary incisors (high, standard, low), and two for mandibular incisors (standard, low). Clinical outcomes were compared among different prescriptions, and regression analysis was used to explain the effects of bracket prescriptions and to understand the prescription selection criteria (α = 0.05). Results: For maxillary central incisors, low and high prescriptions were related to linguoversion (p = 0.046) and labioversion (p = 0.005), respectively, while standard prescription maintained the initial dental inclination. Maxillary lateral incisors did not show significant changes. For mandibular incisors, low prescription led to linguoversion (p = 0.005 for central incisors, p = 0.010 for lateral incisors), while standard prescription led to labioversion (p = 0.045 for central incisors, p = 0.005 for lateral incisors). The factors affecting inclination changes were the imposed change and selected prescription, while prescription selection was influenced by the initial dental inclination and initial intercanine distance. Conclusions: The direction of correction of incisal inclination can be controlled by choosing a certain prescription, but the final inclination may show limited consistency with it. The amount of imposed inclination change was the most relevant predictor of the clinical outcome.

• Asian Pacific Journal of Cancer Prevention
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• 제13권2호
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• pp.689-692
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• 2012

Objective: To investigate correlations between adenosine triphosphate chemotherapy response assay (ATP-CRA) and clinical outcomes after ATP-CRA-based chemotherapy for drug selection in patients receiving intravesical chemotherapy to prevent recurrence of superficial bladder cancer after surgery. Methods: The chemosensitivities of 12 anticancer drugs were evaluated, including 5-Fu ADM, and EPI, using ATP-CRA and primary tumor cell culture in 54 patients. In addition, a further 58 patients were treated according to clinical experience. Differences in post-chemotherapeutical effects between drug sensitivity assay and experience groups were compared. Results: The evaluable rate of the test was 96.3%, the clinical effective rate was 80.8%, the sensitivity rate was 97.6% (41/42), the specificity was 20%, the total predicting accuracy was 74.3%, the positive predictive value was 83.7% (41/49), the negative predictive value was 66.7% (2/3); in the drug sensitivity test group, the clinical effective rate was 80.8%, the experience group response rate was 63.8%, with a significant difference in clinical effects between the ATP-based sensitivity and experience groups (${\chi}^2$=7.0153, P<0.01). Conclusion: ATP-CRA is a stable, accurate and potentially practical chemosensitivity test providing a predictor of chemotherapeutic response in patients with superficial bladder cancer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1419-1436
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• 2020

For an energy harvesting sensor network, when the network lifetime is not the only primary goal, maximizing the network performance under environmental energy harvesting becomes a more critical issue. However, clustering protocols that aim at providing maximum information throughput have not been thoroughly explored in Energy Harvesting Wireless Sensor Networks (EH-WSNs). In this paper, clustering protocols are studied for maximizing the data transmission in the whole network. Based on a long short-term memory (LSTM) energy predictor and node energy consumption and supplement models, an uneven clustering protocol is proposed where the cluster head selection and cluster size control are thoroughly designed for this purpose. Simulations and results verify that the proposed scheme can outperform some classic schemes by having more data packets received by the cluster heads (CHs) and the base station (BS) under these energy constraints. The outcomes of this paper also provide some insights for choosing clustering routing protocols in EH-WSNs, by exploiting the factors such as uneven clustering size, number of clusters, multiple CHs, multihop routing strategy, and energy supplementing period.

• 대기
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• 제25권2호
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• pp.367-374
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• 2015

Korean Peninsula has high potential for occurrence of aviation turbulence. A Korean aviation Turbulence Guidance (KTG) system focused on the Korean Peninsula, named Korean-Peninsula KTG (KP-KTG) system, is developed using the high resolution (horizontal grid spacing of 1.5 km) Local Data Assimilation and Prediction System (LDAPS) of the Korea Meteorological Administration (KMA). The KP-KTG system is constructed first by selection of 15 best diagnostics of aviation turbulence using the method of probability of detection (POD) with pilot reports (PIREPs) and the LDAPS analysis data. The 15 best diagnostics are combined into an ensemble KTG predictor, named KP-KTG, with their weighting scores computed by the values of area under curve (AUC) of each diagnostics. The performance of the KP-KTG, represented by AUC, is larger than 0.84 in the recent two years (June 2012~May 2014), which is very good considering relatively small number of PIREPs. The KP-KTG can provide localized turbulence forecasting in Korean Peninsula, and its skill score is as good as that of the operational-KTG conducting in East Asia.

• Steel and Composite Structures
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• 제39권4호
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• pp.471-491
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• 2021

In this study, we estimate the ultimate load of rectangular concrete-filled steel tubes (CFST) by developing a novel hybrid predictive model (ANN-BCMO) which is a combination of balancing composite motion optimization (BCMO) - a very new optimization technique and artificial neural network (ANN). For this aim, an experimental database consisting of 422 datasets is used for the development and validation of the ANN-BCMO model. Variables in the database are related with the geometrical characteristics of the structural members, and the mechanical properties of the constituent materials (steel and concrete). Validation of the hybrid ANN-BCMO model is carried out by applying standard statistical criteria such as root mean square error (RMSE), coefficient of determination (R²), and mean absolute error (MAE). In addition, the selection of appropriate values for parameters of the hybrid ANN-BCMO is conducted and its robustness is evaluated and compared with the conventional ANN techniques. The results reveal that the new hybrid ANN-BCMO model is a promising tool for prediction of the ultimate load of rectangular CFST, and prove the effective role of BCMO as a powerful algorithm in optimizing and improving the capability of the ANN predictor.

• Asian Journal of Business Environment
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• 제12권3호
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• pp.1-12
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• 2022

Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

• 산경연구논집
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• 제15권3호
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• pp.11-20
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• 2024

Purpose: This study focuses on the Chinese smartphone market to estimate product attributes influencing Chinese customers' preference for developing new smartphones through conjoint analysis. Research design, data and methodology: The online questionnaire survey is processed among Chinese potential smartphone customers. Conjoint analysis including traditional conjoint analysis (TCA) and choice-based conjoint analysis (CBCA), is used to analyze the useful data of 500. Results: Results indicate that price is the most important predictor while screen size is the least for Chinese customers' preference whether the method is TCA or CBCA. However, the importance of brand, capacity, CPU, and screen design is different. Moreover, based on each smartphone attribute level's utility, the new products with the best combinations are different compared with both methods. Finally, the predicted market shares of the top 3 products are the same with maximum utility rule model between TCA and CBCA. However, when considering with the new best combined product, they are significantly different. Conclusions: Managers should recognize the differences between TCA and CBCA and select the best method to develop new smartphones for sustainable business in the Chinese competitive market based on the important attributes of price, brand, capacity, CPU, screen design, and size.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.432-438
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• 2011

The purpose of the present thesis is to develop bankruptcy prediction models capable of being applied to the Korean construction industry and to deduce an optimal model through comparative evaluation of final developed models. A study population was selected as general contractors in the Korean construction industry. In order to ease the sample securing and reliability of data, it was limited to general contractors receiving external audit from the government. The study samples are divided into a bankrupt company group and a non-bankrupt company group. The bankruptcy, insolvency, declaration of insolvency, workout and corporate reorganization were used as selection criteria of a bankrupt company. A company that is not included in the selection criteria of the bankrupt company group was selected as a non-bankrupt company. Accordingly, the study sample is composed of a total of 112 samples and is composed of 48 bankrupt companies and 64 non-bankrupt companies. A financial ratio was used as early predictors for development of an estimation model. A total of 90 financial ratios were used and were divided into growth, profitability, productivity and added value. The MDA (Multivariate Discriminant Analysis) model and BLRA (Binary Logistic Regression Analysis) model were used for development of bankruptcy prediction models. The MDA model is an analysis method often used in the past bankruptcy prediction literature, and the BLRA is an analysis method capable of avoiding equal variance assumption. The stepwise (MDA) and forward stepwise method (BLRA) were used for selection of predictor variables in case of model construction. Twenty two variables were finally used in MDA and BLRA models according to timing of bankruptcy. The ROC-Curve Analysis and Classification Analysis were used for analysis of prediction performance of estimation models. The correct classification rate of an individual bankruptcy prediction model is as follows: 1) one year ago before the event of bankruptcy (MDA: 83.04%, BLRA: 93.75%); 2) two years ago before the event of bankruptcy (MDA: 77.68%, BLRA: 78.57%); 3) 3 years ago before the event of bankruptcy (MDA: 84.82%, BLRA: 91.96%). The AUC (Area Under Curve) of an individual bankruptcy prediction model is as follows. : 1) one year ago before the event of bankruptcy (MDA: 0.933, BLRA: 0.978); 2) two years ago before the event of bankruptcy (MDA: 0.852, BLRA: 0.875); 3) 3 years ago before the event of bankruptcy (MDA: 0.938, BLRA: 0.975). As a result of the present research, accuracy of the BLRA model is higher than the MDA model and its prediction performance is improved.

• Journal of Periodontal and Implant Science
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• 제23권1호
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• pp.109-126
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• 1993

Refractory periodontitis manifest progressive attachment loss in a rapid and unrelenting manner regardless of the type or frequency of therapy applied. The purpose of this study was ta evaluate the relation between the level of cytokines in GCF and periodontopathic microflora with disease activity of refractory periodontitis. Selection of patients with refractory periodontitis (7 males, 3 females) were made by long term clinical observation including conventional clinical history and parameters. Teeth that showed pocket depth greater than 6mm were selected as sample teeth. Subjects were examined at baseline and after 3 months. Prior to baseline test, individual acrylic stent was fabricated. Reference grooves were made on each sample tooth site. Pocket depth and attachment loss were measured by Florida Probe. Gingival index was measured at 4 sites each sample teeth. Disease activity was defined as attachment loss of ${\ge}$ 2.1mm, as determined by sequential probing and tolerance method. The pattern and amount of alveolar bone resorption was observed with quantitative digital subtraction image processing radiography. Morphological analysis of subgingival bacteria was taken by phase contrast microscopy. Predominant cultivable bacterial distribution and frequency were compared between disease-active and disease-inactive site using immunofluorescence microscopy and selective microbial culturing. Levels of $interleukin-l{\beta}$, 2, 4, 6 and $TNF-{\alpha}$ in GCF and blood serum sample were quantified by ELISA. In active sites, P. intermedia was significantly increased to compare with inactive site. $IL-1{\beta}$, IL-2, IL-6 and $TNF-{\alpha}$ in GCF were increased in active sites and IL-2 in serum was increased in active patients significantly. Alveolar bone loss in active site was correlated with $IL-1{\beta}$, IL-2 in GCF. And loss of attachment in active site was correlated with IL-2 in GCF. These results demonstrate that IL-2 in serum, $IL-1{\beta}$, IL-2, IL-6 and $TNF-{\alpha}$ in GCF, P, intermedia might be used as possible predictors of disease activity in refractory periodontitis before it is clinically expressed as attachment loss and quantitative alveolar bone change.