• International Journal of Highway Engineering
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• v.4 no.1 s.11
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• pp.123-134
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• 2002

Special pavement test sections were selected to develop a distress prediction model on asphalt pavement of National Highway. Experimental design was conducted for the selection of LTPP sections on in-service pavement(new and overlaid pavement) using several variables affecting pavement performance. Preliminary sections that satisfied the design template were chosen from the national highway database, and final selection was fixed through field inspection. The number of monitoring section is 95 including 47 overlaid pavement. A pavement distress data such as crack and rutting were collected for two years. An interim pavement performance analysis was peformed to show feasibility of performance monitoring program. Data related pavement such as traffic, weather, material characteristic and crack etc. should be collected for next project years and distress prediction model will be developed through the statistical analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.4
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• pp.1621-1625
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• 2015

Background: Financial distress due to the cost of cancer treatments is prevalent among cancer patients. Identifying the level of financial distress and its affecting factors has an important role in providing supportive services. Accordingly, the aims of this study were to determine these parameters among Iranian cancer patients. Materials and Methods: This descriptive-correlational study was undertaken among 262 cancer patients admitted to both private and public hospitals in East Azerbaijan province, Iran. The financial distress/financial well being scale was used to determine financial distress. The data were analyzed using SPSS software using descriptive and inferential statistics (multiple linear regression). Results: Among the 262 cancer patients, 57.3% were male and their mean age was 47.0 years. The mean score for financial distress was 4.12 (2.01). The final regression model demonstrated that the independent variables (predictors) of income less than living expenses, income equal to living expenses, having an employed spouse in governmental job and living with parents, with regression coefficients of -1.029, -0.515, 0.198, and 0.096, respectively, were predictors of financial distress among cancer patients. These variables accounted for 50% of changes in variance of financial distress. Conclusions: Iranian cancer patients have moderate to high levels of financial distress. Considering policies for managing direct and indirect costs of cancer treatments must be followed.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.382-388
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• 2011

Being aware of the risk in advance necessitates intricate processes but is feasible. Although previous studies have demonstrated high accuracy, their performance still leaves room for improvement. A self-organizing feature map (SOM) based neurofuzzy model is developed in this study to provide another alternative for forecasting corporate financial distress. The model is designed to yield high prediction accuracy, as well as reference rules for evaluating corporate financial status. As a database, the study collects all financial reports from listed construction companies during the latest decade, resulting in over 1000 effective samples. The proportion of "failed" and "non-failed" companies is approximately 1:2. Each financial report is comprised of 25 ratios which are set as the input variable s. The proposed model integrates the concepts of pattern classification, fuzzy modeling and SOM-based optimization to predict corporate financial distress. The results exhibit a high accuracy rate at 85.1%. This model outperforms previous tools. A total of 97 rules are extracted from the proposed model which can be also used as reference for construction practitioners. Users may easily identify their corporate financial status by using these rules.

• Women's Health Nursing
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• v.24 no.4
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• pp.392-403
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• 2018

Purpose: To identify factors associated with menstrual distress and characterize the relationship between menstrual distress and sleep disturbance in middle-school girls. Methods: Participants in this correlational study were 117 middle-school girls who were recruited through convenience sampling. Data were collected from March 2018 to April 2018 using self-reported structured questionnaires and analyzed using IBM SPSS Statistics 23.0. Factors associated with menstrual distress included physiological, psychological, and situational factors based on the theory of unpleasant symptoms. Results: Age of menarche (${\beta}=-.28$, p<.001), amount of menstruation (${\beta}=.23$, p=.004), lifestyle-related exposure to endocrine-disrupting chemicals (${\beta}=.21$, p=.027), and academic and peer-relationship stress (${\beta}=.19$, p=.025) influenced menstrual distress, explaining 47.4% of the variance in this regression model. The relationship between menstrual distress and sleep disturbance was statistically significant. Sleep disturbance was increased 1.26 folds when dysmenorrhea score increased by one unit (OR=1.26, 95% CI: 1.01~1.58). However, parental support was not a significant moderating factor of sleep disturbance. Conclusion: This study provides basis to develop an intervention strategy to alleviate menstrual discomfort in adolescents and improve their quality of sleep.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.5
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• pp.281-288
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• 2022

According to statistics conducted by the Korea Coast Guard, the number of accidents on small boats under 5 tons is increasing every year. This is because only a small number of people are on board. The previously developed maritime distress and safety systems are not well distributed because passengers must be equipped with additional remote equipment. The purpose of this study is to develop a distress awareness system that recognizes man over-board situations in real time. This study aims to present the part of the passenger tracking system among the small ship's distress awareness situational system that can generate passenger's location information in real time using deep learning based object detection and tracking technologies. The system consisted of the following steps. 1) the passenger location information is generated in the form of Bounding box using its detection model (YOLOv3). 2) Based on the Bounding box data, Deep SORT predicts the Bounding box's position in the next frame of the image with Kalman filter. 3) When the actual Bounding Box is created within the range predicted by Kalman-filter, Deep SORT repeats the process of recognizing it as the same object. 4) If the Bounding box deviates the ship's area or an error occurs in the number of tracking occupant, the system is decided the distress situation and issues an alert. This study is expected to complement the problems of existing technologies and ensure the safety of individuals aboard small boats.

• Journal of Korean Academy of Nursing
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• v.41 no.5
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• pp.704-714
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• 2011

Purpose: The purpose of this study was to determine whether psychological distress is an independent risk factor for recurrent cardiac events in patients with coronary artery disease (CAD). Methods: A prospective cohort of studies that measured psychological distress and the incidence of recurrent cardiac events in the adult population were included. Three computerized databases were assessed (PubMed, CINAHL, and PSYCINFO). Meta-analysis was conducted using a random-effects model to determine summary estimates of risks of major recurrent cardiac events associated with each psychological distress. Of 506 publications identified, 33 met inclusion criteria, and 24 studies were used to estimate effect size of psychological distress on recurrent cardiac events. Results: Mean number in the research sample was 736 and mean time of follow-up was 4.0 years. Depression, anxiety, anger, and hostility as psychological factors were studied. According to estimation of effect size using random model effect, depression (OR=1.39, 95% CI: 1.22-1.57), anxiety (OR=1.22, 95% CI: 0.96-1.56), and anger/hostility (OR=1.29, 95% CI: 1.07-1.57) CAD patients in significantly increased risk for recurrent cardiac events. Conclusion: Finding suggests that psychological distress in forms of depression, anxiety, anger, and hostility impact unfavorably on recurrent cardiac events in CAD patients.

• Korean Journal of Biological Psychiatry
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• v.21 no.4
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• pp.141-150
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• 2014

Objectives The purpose of this study is to evaluate the effects of attachment security, social support and health-related burden in the prediction of psychological distress and the mediation effects of social support and health-related burden in relationship between attachment security and psychological distress. Methods Finally, 161 patients were included for the analysis. Chi-square test and independent samples t-test were used for comparing differences between depressive/anxious group and non-depressive/non-anxious group. For evaluating the relationship among attachment security, social support, psychological distress and health-related burden, structural equation modeling analysis were performed. Results 40.7% and 32.0% of the patients have significant depressive symptoms and anxiety symptoms, respectively. In the analysis for testing the differences between groups who have psychological distress and who have not, there were no significant differences of sociodemographic factors and medical characteristics between groups, except for association between depressive symptoms and type of surgery (p = 0.01). Contrary to sociodemographic and medical characteristics, there were significant differences of health-related burden and two coping resources (attachment security and social support) between groups (all p < 0.01), except for the support from medical team in between anxious group and non-anxious group (p = 0.20). In the structural equation model analysis (Model fit : chi-square/df ratio = 0.8, root mean square error of approximation = 0.000, comparative fit index = 1.000, non-normed fit index =0.991), attachment security and social support emerged as an important predictor of psychopathology. Conclusions Attachment security and social support are important factors affecting the psychological distress. We suggest that individual attachment style and the social support state must be considered to approach the newly diagnosed breast cancer patients with psychological distress.

• Research in Community and Public Health Nursing
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• v.30 no.3
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• pp.345-356
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• 2019

Purpose: The purpose of this study is to construct and test a structural equation model of posttraumatic growth (PTG) of earthquake victims based on Tedeschi and Calhoun's model (2004). Methods: Data were collected from 195 earthquake victims living in K. City. The exogenous variables include distress perception, resilience, and social support, and the endogenous variables include intrusive rumination, deliberate rumination, and posttraumatic growth. For data analysis, descriptive statistics, factor analysis, and structural equation modeling were performed. Results: The modified model showed a good fitness to the data. Moreover, 6 of the 9 paths of the final model were statistically significant, which include PTG affected by deliberate rumination (${\beta}=.58$, p<.001), resilience (${\gamma}=.18$, p=.001), and distress perception (${\gamma}=.20$, p=.002). These predictors explain 51.8% of variance in posttraumatic growth. Conclusion: Based on the results of this study, it is necessary to develop and disseminate preventive intervention programs to increase the resilience of earthquake-prone communities. In addition, after exposure to a community-scale traumatic event such as earthquake, we should provide social supports to alleviate distress perception and transition from intrusive rumination to deliberate rumination so that we can seek new meaning from the earthquake and facilitate posttraumatic growth.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.51-52
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• 2013

Recent advances in WSN and the wide use of social sensing technologies have been changing our daily lives. In the process of creating intertwining connections and interconnections greatly influencing on the way we communicate with other people, WSN and social communication media have a number of important capabilities that support their utilization in distress broadcast during emergency situations. This paper proposes a system model that makes better utilization of WSN and social sensing capabilities in sending out distress messages to the intended recipients more efficiently and effectively.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.1-12
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• 2021

Altman's Z-score is used to measure a company's financial health and to predict the probability that a company will collapse within 2 years. It is proven to be very accurate to forecast bankruptcy in a wide variety of contexts and markets. The goal of this study is to use Altman's Z-score model to forecast insolvency in non-financial publicly traded enterprises. Non-financial firms are a significant industry in Malaysia, and current trends of consolidation and long-term government subsidies make assessing the financial health of such businesses critical not just for the owners, but also for other stakeholders. The sample of this study includes 84 listed companies in the Kuala Lumpur Stock Exchange. Of the 84 companies, 52 are considered high risk, and 32 are considered low-risk companies. Secondary data for the analysis was gathered from chosen companies' financial reports. The findings of this study show that the Altman model may be used to forecast a company's financial collapse. It dispelled any reservations about the model's legitimacy and the utility of applying it to predict the likelihood of bankruptcy in a company. The findings of this study have significant consequences for investors, creditors, and corporate management. Portfolio managers may make better selections by not investing in companies that have proved to be in danger of failing if they understand the variables that contribute to corporate distress.