• Journal of the Korean Society of Safety
• /
• v.20 no.2 s.70
• /
• pp.127-132
• /
• 2005

The purpose of this study is to compare representative posture classification schemes of OWAS, RULA and REBA in terms of correctness for postural load. The comparison was based on the evaluation results by the three methods for 224 working postures sampled from steel, electronics, automotive, and chemical industries. The results showed that OWAS and REBA generally underestimated postural stress than RULA irrespective of industry type, work performed and whether or not leg posture is balanced. While about $71\%\;and\;73\%$ of the 224 posture were evaluated with the action category/level 1 or 2 by OWAS and REBA respectively, about $60\%$ of the postures were classified into the action level of 3 or 4 by RULA. The coincidence rate of postural stress category between OWAS and RULA was just $33.5\%$, while the rate between RULA and REBA was $46.0\%$. It is concluded from the findings of this study and the previous research that compared to OWAS and REBA, RULA more precisely evaluates postural stress.

• Journal of Convergence for Information Technology
• /
• v.9 no.5
• /
• pp.86-94
• /
• 2019

This study investigated the differences of perceived parenting attitude and academic stress on smartphone addiction according to the classification of addiction-risk group among middle school students. A descriptive research design was used. The subjects were 358 middle school students from five middle school in Daegu. Data were analyzed by descriptive statistics, ${\chi}^2$ test, t-test, and stepwise multiple regression using SPSS 18.0. Smartphone addiction-risk group was 97(27.0%) and general group was 261(72.9%). Smartphone addiction-risk group was more negatively perceived parenting attitude and higher academic stress than the general group. The most influential factors on addiction-risk group was using time in a day(${\beta}=.29.4$, p=.003) and general group was academic stress(${\beta}=.298$, p=.000). It is important to develop an intervention program to prevention the smartphone addiction according to the classification of addiction-risk group.

• Journal of People, Plants, and Environment
• /
• v.23 no.1
• /
• pp.47-53
• /
• 2020

This study conducted a horticultural therapy program for trainees entrusted to the Juvenile Classification Review Center in order to fill the educational gap while providing emotional stability during the one-month period of commissioned education. The effects of horticultural therapy were examined by the pretest and posttest changes of the emotional items such as anxiety, self-esteem, self-efficacy and stress index. As the research method, this study used the one-group pretest-posttest experimental design on 16 female trainees of commissioned education staying at the Juvenile Classification Review Center in the juvenile reformatory located in A city. The horticultural therapy program was carried out in four sessions: two on flower arrangement and two on planting. The scores before and after the horticultural therapy program were measured using the Revised Children's Manifest Anxiety Scale (RCMAS) to examine the effects of horticultural therapy on the reduction of anxiety for the adolescents staying in the Juvenile Classification Review Center. The results show that there was significant decrease in the mean of anxiety from 62.5 (SD = 6.8) to 57.6 (SD = 8.1) points after the program (p = .002). There was no significant change in self-esteem, which was 76.9 (SD = 11.2) before the horticultural therapy and 78.3 (SD = 8.7) after the therapy (p = .420). In self-efficacy, there was no significant change from 72.9 (SD = 10.9) before and 75.1 (SD = 11.0) after horticultural therapy (p = .178). In order to examine the physiological changes in such emotional functions, this study measured the stress index using the uBioMacpa as the tool. The result of the measurement showed that there was a significant change in the mean from 33.8 (SD = 2.3) before to 31.1 (SD = 2.2) after the horticultural therapy (p < .001).

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.30 no.5 s.248
• /
• pp.520-527
• /
• 2006

The design of major industrial facilities for the prevention of fatigue failure is customarily done by defining a set of transients and performing a calculation of cumulative usage factor. However, sometimes, the inherent conservatism or lack of details as well as unanticipated transients in old plant may cause maintenance problems. Even though several famous on-line monitoring and diagnosis systems have been developed world-widely, in this paper, a new system fur fatigue monitoring and life evaluation of crane is proposed to reduce customizing effort and purchasing cost. With regard to the system, at first, comprehensive operating transient data has been acquired at critical locations of crane. The real-time data were classified, by using adaptive resonance theory that is one of typical artificial neural network, into representative stress groups. Then the each classified stress pattern was mapped to calculated cumulative usage factor in accordance with ASME procedure. Thereby, promising results were obtained fur the crane and it is believed that the developed system can be applicable to other major facilities extensively.

• Journal of Electrical Engineering and Technology
• /
• v.1 no.2
• /
• pp.257-262
• /
• 2006

Insulation failure in an electrical utility depends on the continuous stress imposed upon it. Monitoring of the insulation condition is a significant issue for safe operation of the electrical power system. In this paper, comparison of recognition rate variable classification scheme of PD (partial discharge) sources that occur within an electrical utility are studied. To acquire PD data, five defective models are made, that is, air discharge, void discharge and three types of treeinging discharge. Furthermore, these statistical distributions are applied to classify PD sources as the input data for the classification tools. ANFIS shows the highest rate, the value of which is 99% and PCA-LDA and ANFIS are superior to BP in regards to other matters.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.8 no.1
• /
• pp.61-68
• /
• 1988

This study is intended to propose an approach to reliability-based safety evaluation as well as LRFR(Load and Resisitance Factor Rating) type capacity classification of military or civilian bridges based on the limit state models which are delived by incorporating all the uncertainties of resistance and load random variables including deterioration, and are used in a practical AFOSM (Advanced First Order Second Moment) method. The proposed methods for the assement of safety and load carrying capacity are applied for the evaluation of rating and classifications of several practical bridges against the crossing of military vehicles. Based on the observation of the numerical results, it can be concluded that the current NATO classification method which is based on the traditionl allowable stress concept can not provide real load carrying capacity but results in nominal classification, and therefore the reliability-based safety evaluation and LRFR-classification method or the corresponding rational allowable stress method proposed in this paper may have to be introduced into the classification practice.

• The Journal of the Korea Contents Association
• /
• v.14 no.2
• /
• pp.409-420
• /
• 2014

The purpose of this study is to examine the level of stress and depressive symptom and to assess the utilization of professional consultation. Data extracted from Community Health Survey (CHS), conducted by Korea Centers for Disease Control and Prevention. The subjects were 174,975 (19-65 years). In result, 'Managers', 'Professionals and related workers', 'Clerks', 'Service workers', and 'Sales workers', 'Equipment, machine operating assembling workers', and 'Armed forces' were more in risk of stress. However, theses groups were less in probability of utilization for stress consultation. Based on these findings, mental health screening program for detecting risk group among occupation classification and employment status will be essential. It may be necessary to have sustainable strategies for utilizing mental health service to reduce the level of stress and depressive symptom of workers.

• Journal of the Korean Wood Science and Technology
• /
• v.23 no.2
• /
• pp.47-54
• /
• 1995

This study was to measure the properties of logs and classify them by non-destructive methods. The purpose of this experiment was focused at mensurability of logs by non-destructive methods. The non-destructive instrument, Stress-Wave Timer 239A which was made by Metriguard in U.S.A., was used. The stress wave velocities of log's cross direction were measured and compared with three different methods; 1. with hammer, 2. with hammer and D.B.H. meter, 3. with manufactured instrument. Number of used logs were seven logs, which were classified by naked eye into six groups; very severe rot, severe rot, mild rot & knot, mild rot & check, mild rot, sound log, and in diameter were into three groups; large(57.4cm), medium(36~41.2cm), small(28.9cm) log. The results, which were classified by mensurability with non-destructive methods, were followed; 1. The stress wave velocities were very different between rot and sound log. So it meant the possibility of mensurability of logs by non-destructive method even if high standard error. 2. The stress wave velocities decreased with checks more than with rots, which meant the checks affected speeds more. 3. The stress wave velocities increased with knot. 4. The velocities with manufactured instrument showed lower standard error, so more accurate results than other methods. Especially the required labour decreased from 3~4 to 2 persons. 5. Finally, the mensurability showed more accurate results and made the classification of logs scientific.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.12
• /
• pp.3943-3959
• /
• 2022

People are constantly exposed to stress and anxiety environment, which could contribute to a variety of psychological and physical health problems. Therefore, it is particularly important to identify psychological stress in time and to find a feasible and universal method of stress reduction. This research investigated the influence of different music, such as relaxation music and natural rhythm music, on stress relief based on Electroencephalogram signals. Mental arithmetic test was implemented to create a stressful environment. 23 participants performed the mental arithmetic test with and without music respectively, while their Electroencephalogram signal was recorded. The effect of music on stress relief was verified through stress test questionnaires, including Trait Anxiety Inventory (STAI-6) and Self-Stress Assessment. There was a significant change in the stress test questionnaire values with and without music according to paired t-test (p<0.01). Furthermore, a model based on Transformer for stress level classification from Electroencephalogram signal was proposed. Experimental results showed that the method of listening to relaxation music and natural rhythm music achieved the effect of reducing psychological stress and the proposed model yielded a promising accuracy in classifying the Electroencephalogram signal of mental stress.

• Smart Structures and Systems
• /
• v.29 no.4
• /
• pp.589-598
• /
• 2022

Timber structures are susceptible to structural damages caused by variations in moisture content (MC), inducing severe durability deterioration and safety issues. Therefore, it is of great significance to detect MC levels in timber structures. Compared to current methods for timber MC detection, which are time-consuming and require bulky equipment deployment, Lead Zirconate Titanate (PZT)-enabled stress wave sensing combined with statistic machine learning classification proposed in this paper show the advantage of the portable device and ease of operation. First, stress wave signals from different MC cases are excited and received by PZT sensors through active sensing. Subsequently, two non-baseline features are extracted from these stress wave signals. Finally, these features are fed to a statistic machine learning classifier (i.e., naïve Bayesian classification) to achieve MC detection of timber structures. Numerical simulations validate the feasibility of PZT-enabled sensing to perceive MC variations. Tests referring to five MC cases are conducted to verify the effectiveness of the proposed method. Results present high accuracy for timber MC detection, showing a great potential to conduct rapid and long-term monitoring of the MC level of timber structures in future field applications.