• Transactions of Materials Processing
• /
• v.22 no.8
• /
• pp.450-455
• /
• 2013

In the current study, a new dynamic recrystallization model for predicting high temperature flow stress is developed based on a physical model and the mean field theory. In the model, the grain aggregate is assumed as a representative volume element to describe dynamic recrystallization. The flow stress and microstructure during dynamic recrystallization were calculated using three sub-models for work hardening, for nucleation and for growth. In the case of work hardening, a single parameter dislocation density model was used to calculate change of dislocation density and stress in the grains. For modeling nucleation, the nucleation criterion developed was based on the grain boundary bulge mechanism and a constant nucleation rate was assumed. Conventional rate theory was used for describing growth. The flow stress behavior of pure copper was investigated using the model and compared with experimental findings. Simulated results by cellular automata were used for validating the model.

• Journal of Applied Reliability
• /
• v.17 no.2
• /
• pp.129-135
• /
• 2017

Purpose: This article provides step-stress accelerated degradation test (ADT) plans based on the Wiener process. Method: Step-stress levels and the stress change times are determined based on the D-optimality criteria to develop test plans. Further, a simple grid search method is provided for obtaining the optimal test plan. Results: Based on the solution procedure, ADT plans which include the stress levels and change times are developed for conducting the reliability test. Conclusion: Optimal step-stress ADT plans are provided for the case where the number of measurements is small.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.11
• /
• pp.3099-3120
• /
• 2023

The present fast-moving era brings a serious stress issue that affects elders and youngsters. Everyone has undergone stress factors at least once in their lifetime. Stress is more among youngsters as they are new to the working environment. whereas the stress factors for elders affect the individual and overall performance in an organization. Electroencephalogram (EEG) based stress level classification is one of the widely used methodologies for stress detection. However, the signal processing methods evolved so far have limitations as most of the stress classification models compute the stress level in a predefined environment to detect individual stress factors. Specifically, machine learning based stress classification models requires additional algorithm for feature extraction which increases the computation cost. Also due to the limited feature learning characteristics of machine learning algorithms, the classification performance reduces and inaccurate sometimes. It is evident from numerous research works that deep learning models outperforms machine learning techniques. Thus, to classify all the emotions based on stress level in this research work a hybrid deep learning algorithm is presented. Compared to conventional deep learning models, hybrid models outperforms in feature handing. Better feature extraction and selection can be made through deep learning models. Adding machine learning classifiers in deep learning architecture will enhance the classification performances. Thus, a hybrid convolutional neural network model was presented which extracts the features using CNN and classifies them through machine learning support vector machine. Simulation analysis of benchmark datasets demonstrates the proposed model performances. Finally, existing methods are comparatively analyzed to demonstrate the better performance of the proposed model as a result of the proposed hybrid combination.

• International Journal of Reliability and Applications
• /
• v.17 no.1
• /
• pp.85-105
• /
• 2016

In this paper accelerated life testing is incorporated in quality control technique of acceptance sampling plan to induce early failures in high reliability products.Stress under accelerated condition can be applied in constant-stress, step-stress and progressive-stress or combination of such loadings. A ramp-stress results when stress is increased linearly (from zero) with time. In this paper optimum failure-censored ramp-stress accelerated life test sampling plan for log-logistic distribution has been formulated with cost considerations. The log-logistic distribution has been found appropriate for insulating materials. The optimal plans consist in finding optimum sample size, sample proportion allocated to each stress, and stress rate factor such that producer's and consumer's interests are safeguarded. Variance optimality criterion is used when expected cost per lot is not taken into consideration, and bilevel programming approach is used in cost optimization problems. The methods developed have been illustrated using some numerical examples, and sensitivity analyses carried out in the context of ramp-stress ALTSP based on variable SSP for proportion nonconforming.

• Journal of Biomedical Engineering Research
• /
• v.30 no.4
• /
• pp.288-293
• /
• 2009

This study investigates the relationship of affective style based on EEG asymmetry, personality, and psychological stress on stress. The experiment consists of three sessions: rest state, landscape scene, and horror film tasks. We used a short horror film to evoke stress. We classified affective style of the individual based on EEG alpha asymmetry: negative bias, positive bias and general. The participants in the negative bias group reported higher levels of stress on the neuroticism of the Big 5 model and Cohen's Perceived Stress Scale. These results demonstrate that participants with the propensity for negative affective style have a nervous temperament and are apt to be stressed.

• Korean Journal of Social Welfare
• /
• v.61 no.2
• /
• pp.5-32
• /
• 2009

This study investigates the effect of self-esteem and Korean ability on acculturative stress of marriage-based immigrant Asian women in Korea. It also attempts to find out whether self-esteem has any mediating effect between Korean ability and acculturative stress. By using purposive sampling method, 280 samples were collected among Vietnamese, Filipino, and Chinese women in Daegu from Oct. 12th to Nov. 3rd, 2008. The results are as follows: The higher the score of self-esteem and that of Korean ability is, the lower the score of acculturative stress is respectively. It is proved that self-esteem has mediating effect between Korean ability and acculturative stress. Therefore it is emphasized that programs which can improve self-esteem should be provided to marriage-based immigrant women, especially to those who do not have sufficient Korean ability. Sending money to home country shows both direct and indirect effects and subjective economic evaluation shows direct effects on acculturative stress score. For the purpose of the study acculturative stress scale has been modified based on Sandhu and Asrabadi(1994), which turns out to be useful to measure acculturative stress of marriage-based immigrant Asian women in Korea because it reflects their life circumstances quite well. Some practical implications of social work are suggested through discussion.

• Perspectives in Nursing Science
• /
• v.16 no.2
• /
• pp.65-74
• /
• 2019

Purpose: This study applied the Korean Mindfulness-Based Stress Reduction (K-MBSR) program for mothers of children and adolescents with mental illnesses, and verified its effectiveness on perceived stress and depression based on the Middle-range theory of caregiver stress. Methods: A quasi-experimental, non-equivalent control group pre-post test design was used. The K-MBSR program was reconstructed with experts' advice to adjust subjects' characters. Using a group approach, sessions were conducted once a week for six weeks, and each session took 2.5 hours. Results: The experimental group did not show a significant decrease in perceived stress than the control group. However, the experimental group showed a significant decrease in depression than the control group. Conclusion: The K-MBSR program was effective for depression. Future studies on high-stress groups or with an extended program are necessary to clarify the effects of the K-MBSR program on perceived stress. These results are consistent with the middle-range theory of caregiver stress, the theoretical framework of this study. When caregivers have similar inputs, proper intervention can change the control process. Further, it can be assumed that this change positively affects the output.

• International Journal of Advanced Culture Technology
• /
• v.10 no.4
• /
• pp.8-18
• /
• 2022

Objectives: The objective of this study was to explore the effects of the simulation-based learning program on stress, problem-solving ability, self-efficacy, and resilience of final-year nursing students in a college in South Korea. Methods: The design of the study was a one-group pretest-posttest. The participants of this study were final-year nursing students in 2018. A total of 105 students completed it. The intervention was an 8-week simulation-based practice course. The primary and secondary outcome measures were baseline and follow-up questionnaires regarding demographic factors, stress, problem-solving ability, self-efficacy, and resilience. Results: Problem-solving ability (t=6.567, p<.001), self-efficacy in four situations (p<.001) and resilience (t=2.352, p=.021) increased after simulation-based learning than before learning. Stress also increased after simulation-based learning compared to before learning (t=5.960, p<.001). The level of stress, self-efficacy, and resilience were mainly related to participants' satisfaction with their clinical placement, and interpersonal relationships (p<.05). Conclusions: Simulation-based learning is expected to improve nursing students' problem-solving ability, self-efficacy, and resilience. This can lead to induce learning motivation of nursing students, improve their coping strategies for solving problems, and ultimately provide high-quality care.

• Anxiety and mood
• /
• v.18 no.1
• /
• pp.1-9
• /
• 2022

Mindfulness has been widely researched in mental, physical health, and healthy populations. The effectiveness of mindfulness-based interventions have also been demonstrated in research studies. This report reviews the research on mindfulness based interventions currently employed for the treatment of posttraumatic stress disorder (PTSD). Mindfulness-based theories postulate that symptoms of PTSD are developed and maintained by experiential avoidance and non-mindful behaviors. Recent emerging work indicates that mindfulness based interventions, such as mindfulness-based stress reduction and mindfulness-based cognitive therapy, may improve the symptoms of PTSD. Further advances are needed to gain a better understanding of the ability of mindfulness based interventions to target specific symptom dimensions of PTSD and the psychological/neurobiological mechanisms of actions underlying these interventions.

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.387-396
• /
• 2020

Wearable biosensors have the potential to non-invasively and continuously monitor seniors' stress in their daily interaction with the urban environment, thereby enabling to address the stress and ultimately advance their outdoor mobility. However, current wearable biosensor-based stress detection methods have several drawbacks in field application due to their dependence on batch-learning algorithms. First, these methods train a single classifier, which might not account for multiple subjects' different physiological reactivity to stress. Second, they require a great deal of computational power to store and reuse all previous data for updating the signle classifier. To address this issue, we tested the feasibility of online multi-task learning (OMTL) algorithms to identify multiple seniors' stress from electrodermal activity (EDA) collected by a wristband-type biosensor in a daily trip setting. As a result, OMTL algorithms showed the higher test accuracy (75.7%, 76.2%, and 71.2%) than a batch-learning algorithm (64.8%). This finding demonstrates that the OMTL algorithms can strengthen the field applicability of the wearable biosensor-based stress detection, thereby contributing to better understanding the seniors' stress in the urban environment and ultimately advancing their mobility.