Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.17
no.3
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pp.215-227
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2022
In the digital transformation paradigm, IT employee work as a key human resource to accept new technologies and to lead their organization to be settled them efficiently. However, due to relatively short term of their job life and high turnover rate, the companies and the organizations are still experiencing problem the lack of IT manpower or turnover. In this study, it attempted to analyze the relationship between IT employee's technostress factors such as techno-overload, techno-complexity, techno-uncertainty, techno-invasion, and techno-insecurity and job burnout through stress coping. To reveal the structural relationship between main variables, the survey was conducted on 318 IT employees. An EFA, CFA, and reliability analysis were performed to confirm reliability and validity, and the structural equation model was conducted to testify research hypotheses. The main results are as follows. First, it was found that techno-uncertainty and techno-insecurity had the significant positive effect on problem focused coping(PFC). And, techno-complexity, techno-uncertainty, and techno-insecurity were found to have a significant positive effect on emotion focused coping(EFC). Second, in the relationship between stress coping and job burnout, it was found that EFC had a significant positive effect on burnout. Third, in the relationship between technostress and burnout, techno-uncertainty and techno-invasion were found to have a significant positive effect on burnout. In addition, it was found that the mediator effect of stress coping between techno-overload and techno-complexity through EFC. Therefore, these outputs are expected to suggest how to motivate IT employees who work as key role in efficient management on IT assets and strengthen competitiveness in digital transformation paradigm.
Recently, many interests in the economic contribution of performing arts for the city's tourist attractions have been increasing, and the policy projects supporting surtitle for foreign tourists are expanding. Therefore, the purpose of this study is to explore the acceptance process of subtitle systems using the TAM(Technical Acceptance Model) to understand the influential relations of factors affecting the viewing of the performance of subtitling service by foreign tourists. Data for empirical analysis were collected in a survey of foreign tourists who had experienced performance subtitles with smart pads in three languages. The results of this study are as follows. First, the higher the information system quality of the performance subtitles, the higher the perceived usefulness of the subtitles. Second, for Korean performances, the decreasing level of both the performance-based risk and the psychological risk has a positive influence on the viewing intent. But, the decreasing level of the financial risk has a negative influence on the viewing intent. Third, the decreasing level of performance risk has a positive influence on the perceived usefulness, while the decreasing level of psychological risk has a negative influence on the perceived usefulness. Finally, the psychological risk has the moderating effect of the viewing intention, which it has a negative influence on the perceived usefulness.
Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.
A.M. Abd-Alla;Esraa N. Thabet;S.M.M.El-Kabeir;H. A. Hosham;Shimaa E. Waheed
Advances in nano research
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v.16
no.4
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pp.325-340
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2024
There are several novel uses for dispersing many nanoparticles into a conventional fluid, including dynamic sealing, damping, heat dissipation, microfluidics, and more. Therefore, melting heat and mass transfer characteristics of a 3-D MHD Hybrid Nanofluid flow over a rotating disc with presenting dufour and soret effects are assessed numerically in this study. In this instance, we investigated both ferric sulfate and molybdenum disulfide as nanoparticles suspended within base fluid water. The governing partial differential equations are transformed into linked higher-order non-linear ordinary differential equations by the local similarity transformation. The collection of these deduced equations is then resolved using a Chebyshev spectral collocation-based algorithm built into the Mathematica software. To demonstrate how different instances of hybrid/ nanofluid are impacted by changes in temperature, velocity, and the distribution of nanoparticle concentration, examples of graphical and numerical data are given. For many values of the material parameters, the computational findings are shown. Simulations conducted for different physical parameters in the model show that adding hybrid nanoparticle to the fluid mixture increases heat transfer in comparison to simple nanofluids. It has been identified that hybrid nanoparticles, as opposed to single-type nanoparticles, need to be taken into consideration to create an effective thermal system. Furthermore, porosity lowers the velocities of simple and hybrid nanofluids in both cases. Additionally, results show that the drag force from skin friction causes the nanoparticle fluid to travel more slowly than the hybrid nanoparticle fluid. The findings also demonstrate that suction factors like magnetic and porosity parameters, as well as nanoparticles, raise the skin friction coefficient. Furthermore, It indicates that the outcomes from different flow scenarios correlate and are in strong agreement with the findings from the published literature. Bar chart depictions are altered by changes in flow rates. Moreover, the results confirm doctors' views to prescribe hybrid nanoparticle and particle nanoparticle contents for achalasia patients and also those who suffer from esophageal stricture and tumors. The results of this study can also be applied to the energy generated by the melting disc surface, which has a variety of industrial uses. These include, but are not limited to, the preparation of semiconductor materials, the solidification of magma, the melting of permafrost, and the refreezing of frozen land.
Ji Hye Kwon;Seung Soo Lee;Jee Seok Yoon;Heung-Il Suk;Yu Sub Sung;Ho Sung Kim;Chul-min Lee;Kang Mo Kim;So Jung Lee;So Yeon Kim
Korean Journal of Radiology
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v.22
no.12
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pp.1985-1995
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2021
Objective: Although the liver-to-spleen volume ratio (LSVR) based on CT reflects portal hypertension, its prognostic role in cirrhotic patients has not been proven. We evaluated the utility of LSVR, automatically measured from CT images using a deep learning algorithm, as a predictor of hepatic decompensation and transplantation-free survival in patients with hepatitis B viral (HBV)-compensated cirrhosis. Materials and Methods: A deep learning algorithm was used to measure the LSVR in a cohort of 1027 consecutive patients (mean age, 50.5 years; 675 male and 352 female) with HBV-compensated cirrhosis who underwent liver CT (2007-2010). Associations of LSVR with hepatic decompensation and transplantation-free survival were evaluated using multivariable Cox proportional hazards and competing risk analyses, accounting for either the Child-Pugh score (CPS) or Model for End Stage Liver Disease (MELD) score and other variables. The risk of the liver-related events was estimated using Kaplan-Meier analysis and the Aalen-Johansen estimator. Results: After adjustment for either CPS or MELD and other variables, LSVR was identified as a significant independent predictor of hepatic decompensation (hazard ratio for LSVR increase by 1, 0.71 and 0.68 for CPS and MELD models, respectively; p < 0.001) and transplantation-free survival (hazard ratio for LSVR increase by 1, 0.8 and 0.77, respectively; p < 0.001). Patients with an LSVR of < 2.9 (n = 381) had significantly higher 3-year risks of hepatic decompensation (16.7% vs. 2.5%, p < 0.001) and liver-related death or transplantation (10.0% vs. 1.1%, p < 0.001) than those with an LSVR ≥ 2.9 (n = 646). When patients were stratified according to CPS (Child-Pugh A vs. B-C) and MELD (< 10 vs. ≥ 10), an LSVR of < 2.9 was still associated with a higher risk of liver-related events than an LSVR of ≥ 2.9 for all Child-Pugh (p ≤ 0.045) and MELD (p ≤ 0.009) stratifications. Conclusion: The LSVR measured on CT can predict hepatic decompensation and transplantation-free survival in patients with HBV-compensated cirrhosis.
Thomas Weikert;Saikiran Rapaka;Sasa Grbic;Thomas Re;Shikha Chaganti;David J. Winkel;Constantin Anastasopoulos;Tilo Niemann;Benedikt J. Wiggli;Jens Bremerich;Raphael Twerenbold;Gregor Sommer;Dorin Comaniciu;Alexander W. Sauter
Korean Journal of Radiology
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v.22
no.6
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pp.994-1004
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2021
Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients' needs for intensive care (yes/no) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79-0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77-0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85-0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66-0.88). Conclusion: Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.
Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.
Jisun Lee;Woo Kyoung Jeong;Jae-Hun Kim;Jong Man Kim;Tae Yeob Kim;Gyu Seong Choi;Choon Hyuck David Kwon;Jae-Won Joh;Sang-Yong Eom
Korean Journal of Radiology
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v.22
no.2
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pp.189-197
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2021
Objective: Muscle depletion in patients undergoing liver transplantation affects the recipients' prognosis and therefore cannot be overlooked. We aimed to evaluate whether changes in muscle and fat mass during the preoperative period are associated with prognosis after deceased donor liver transplantation (DDLT). Materials and Methods: This study included 72 patients who underwent DDLT and serial computed tomography (CT) scans. Skeletal muscle index (SMI) and fat mass index (FMI) were calculated using the muscle and fat area in CT performed 1 year prior to surgery (1 yr Pre-LT), just before surgery (Pre-LT), and after transplantation (Post-LT). Simple aspects of serial changes in muscle and fat mass were analyzed during three measurement time points. The rate of preoperative changes in body composition parameters were calculated (preoperative ΔSMI [%] = [SMI at Pre-LT - SMI at 1 yr Pre-LT] / SMI at Pre-LT x 100; preoperative ΔFMI [%] = [FMI at Pre-LT - FMI at 1 yr Pre-LT] / FMI at Pre-LT x 100) and assessed for correlation with patient survival. Results: SMI significantly decreased during the preoperative period (mean preoperative ΔSMI, -13.04%, p < 0.001). In the multivariable analysis, preoperative ΔSMI (p = 0.016) and model for end-stage liver disease score (p = 0.011) were independent prognostic factors for overall survival. The mean survival time for patients with a threshold decrease in the preoperative ΔSMI (≤ -30%) was significantly shorter than for other patients (p = 0.007). Preoperative ΔFMI was not a prognostic factor but FMI increased during the postoperative period (p = 0.009) in all patients. Conclusion: A large reduction in preoperative SMI was significantly associated with reduced survival after DDLT. Therefore, changes in muscle mass during the preoperative period can be considered as a prognostic factor for survival after DDLT.
Chan Park;Jin Hyoung Kim;Pyeong Hwa Kim;So Yeon Kim;Dong Il Gwon;Hee Ho Chu;Minho Park;Joonho Hur;Jin Young Kim;Dong Joon Kim
Korean Journal of Radiology
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v.22
no.2
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pp.213-224
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2021
Objective: Clinical outcomes of patients who undergo transarterial chemoembolization (TACE) for single small hepatocellular carcinoma (HCC) are not consistent, and may differ based on certain imaging findings. This retrospective study was aimed at determining the efficacy of pre-TACE CT or MR imaging findings in predicting survival outcomes in patients with small HCC upon being treated with TACE. Besides, the study proposed to build a risk prediction model for these patients. Materials and Methods: Altogether, 750 patients with functionally good hepatic reserve who received TACE as the first-line treatment for single small HCC between 2004 and 2014 were included in the study. These patients were randomly assigned into training (n = 525) and validation (n = 225) sets. Results: According to the results of a multivariable Cox analysis, three pre-TACE imaging findings (tumor margin, tumor location, enhancement pattern) and two clinical factors (age, serum albumin level) were selected and scored to create predictive models for overall, local tumor progression (LTP)-free, and progression-free survival in the training set. The median overall survival time in the validation set were 137.5 months, 76.1 months, and 44.0 months for low-, intermediate-, and high-risk groups, respectively (p < 0.001). Time-dependent receiver operating characteristic curves of the predictive models for overall, LTP-free, and progression-free survival applied to the validation cohort showed acceptable areas under the curve values (0.734, 0.802, and 0.775 for overall survival; 0.738, 0.789, and 0.791 for LTP-free survival; and 0.671, 0.733, and 0.694 for progression-free survival at 3, 5, and 10 years, respectively). Conclusion: Pre-TACE CT or MR imaging findings could predict survival outcomes in patients with small HCC upon treatment with TACE. Our predictive models including three imaging predictors could be helpful in prognostication, identification, and selection of suitable candidates for TACE in patients with single small HCC.
Journal of The Korean Association For Science Education
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v.27
no.7
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pp.645-662
/
2007
The purpose of this study was to explore the manners in which models are used in secondary science classrooms. A total of thirteen video-recordings of science lessons dealing with the domains of atmospheric and oceanic earth sciences and their verbatim transcripts were analysed both quantitatively and qualitatively. Interviews with three inservice science teachers were also conducted. Six interrelated assertions were generated as the result of the study: 1) The most frequently used models in secondary earth science classrooms include two-dimensional pictorial, symbolic, iconic, and diagrammatic ones; 2) Science teachers employ models as a mode of representation to make the subject matter available to students; 3) In earth science classrooms, teachers use typical forms of models in intensive manners; 4) Students themselves deal with models on a few occasions, but they just follow similar procedures with the same models; 5) Teachers talk rarely about the nature of scientific models and provide few opportunities for students to think about it; and, 6) Teachers in practice think that the value of using models should be appraised in consideration of the pedagogical intentions of the teacher. Implications for science education and science education research were discussed.
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