This study was performed to investigate the stress level and health-related behaviors of nurses and to provide basic information for developing educational programs in the health care field. The subjects of this study were 197 nurses and 94 nursing assistants working at hospitals in the Kyung-nam area. A survey was conducted using a self-administered questionnaire in November, 2002. The results were as follows : The average age and work experience of the subjects were 26.9 and 5.6 years, respectively. The number of respondents in the shift and non-shift operations was equally distributed. The mean height and weight were 161.2 cm and 52.7 kg, respectively. Even though the average body mass index (BMI) and obesity index were normal in the subjects, 9.2% of the subjects were overweight/obese, while 28.9% of the subjects were under weight, according to the obesity index. The mean score of stress was 27.5 \pm$\pm$ 4.6 out of 50 points. Most of the subjects were highly stressed about the amount of their work, problems regarding their future, and relationships with their superiors. With regard to changes in food intake due to stress, 44.1% showed an increased intake, while 32.3% showed a reduced intake. The degree of health consciousness of the married nurses, those over 36 years of age, and those with over 10 years of nursing experience was significantly higher than that of the unmarried nurses, those under 35 years of age, and those with under 10 years of nursing experience (p<0.01). Fifty-one point three percent of the subjects thought their health status was unhealthy. Fifty-seven percent of the subjects had tried weight control. Their main reason for trying weight control was to have a slender figure (62.3%), and their methods of weight control were moderation in intake(45.6%), exercise and dieting (36.9%). TV/radio (49.5%) and newspaper/magazines (47.1%) were the primary sources of nutritional and health information for the subjects, and professional (25.1%) and the internet (13.4%) were ranked relatively highly. The food components of most concern to the subjects during meal time were (in order of importance) fats (51.9%), calories (40.2%) and salt (35.1%). The subjects considered 'taking a rest' (73.5%) as the most important factor in maintaining an optimal health status, followed by self-relaxation (56.4%), moderation in diet (39.5), bathing or using a sauna (25.7%) and exercising (22.7%).
Under the quickly changing health care environment in our society competitions among hospitals are getting harder and accordingly the hospital authorities do their best efforts to renovate their hospital management and let directors of food and nutrition services in hospital be seeking the drastic changes in their clinic-support operations. To attain this end it is essential to build an information system in food and nutrition services in hospital for practicing those operational changes efficiently. By building an information system we can totally manage a number of information about hospital food and nutrition services. This kind of information system can not only relieve dieticians and food-service workers from their repetitively routine jobs, but also connect with hospital management information systems organically. Resultantly productivity in this service area can be improved and the efficiency of hospital management will be increased. And accordingly the competitive advantage of the hospital can be greater than ever and that brings patients' and hospital employees' satisfaction. I would like to name this kind of information system for hospital food and nutrition services "TASTY", abbreviated from "Time-based Advanced Service Technology for Yong-Dong Severance Hospital, Nutrition Department" There are one basic information management area and five business management areas in TASTY. Five specific business areas are divided by menu, procurement, clinical nutrition service, production(including distribution and meal service), and financial management.inancial management.
Background: The success rate of intubation under direct laryngoscopy is greatly influenced by laryngoscopic grade using the Cormack-Lehane classification. However, it is not known whether grade under direct laryngoscopy can also affects the success rate of nasotracheal intubation using a fiberoptic bronchoscpe, so this study investigated the same. In addition, we investigated other factors that influence the success rate of fiberoptic nasotracheal intubation (FNI). Methods: FNI was performed by 18 anesthesiology residents under general anesthesia in patients over 15 years of age who underwent elective oral and maxillofacial operations. In all patients, the Mallampati grade was measured. Laryngeal view grade under direct laryngoscopy, and the degree of secretion and bleeding in the oral cavity was measured and divided into 3 grades. The time required for successful FNI was measured. If the intubation time was > 5 minutes, it was evaluated as a failure and the airway was managed by another method. The failure rate was evaluated using appropriate statistical method. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were also measured. Results: A total of 650 patients were included in the study, and the failure rate of FNI was 4.5%. The patient's sex, age, height, weight, Mallampati, and laryngoscopic view grade did not affect the success rate of FNI (P > 0.05). BMI, the number of FNI performed by residents (P = 0.03), secretion (P < 0.001), and bleeding (P < 0.001) grades influenced the success rate. The AUCs of bleeding and secretion were 0.864 and 0.798, respectively, but the AUC of BMI, the number of FNI performed by residents, Mallampati, and laryngoscopic view grade were 0.527, 0.616, 0.614, and 0.544, respectively. Conclusion: Unlike in intubation under direct laryngoscopy, in the case of FNI, oral secretion and nasal bleeding had a significant effect on FNI difficulty than Mallampati grade or Laryngeal view grade.
Financial service industry has introduced and operated management systems such as information security management system (ISMS), personal information security management system, business continuity management system to protect and maintain suitably customer's financial information and financial service. This study started that it's desirable financial industry takes consideration of ISMS and it can be different types among various organizations taking consideration of culture, practical work, and guideline of information security. The study derives primary control areas of ISMS through analyzing non-conformity trends and control factors according to certification audit for finance-related organizations introduced international ISMS of ISO27001 which is well known and commonly applicable irrespective of areas in financial service industry. Through case analyses for five finance-related organizations operating ISMS, this study analyzed improvement effects of ISMS. It has a meaning as an initial research though it was difficulty in acquiring data for empirical study because of rare organizations maintaining certification in financial sector. As a result, number of non-confirmity from the first audit to three years' elapse was decreased every year. Physical and environmental security, communication and operations management, and access control having the highest frequency of non-conformity each presented 23%, 19%, and 17%, which reached 59% in total and they are derived into primary control areas. ISMS can fulfill technical, managerial, physical security issues, which have not been treated importantly in financial industry. In addition, this study presented that ISMS can be an effective management system applicable for financial service industry.
KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.5
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pp.667-674
/
2023
In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.
Utilizing chi-square test statistics, inter-species association and covariation were analyzed for the 37 woody plant species in a deciduous forest dominated by Quercus mongolica and Q. variabilis. within 50 temporarily established $20m{\times}20m$ square quadrats, the association for each pair of species was presented based on the presence-absence parameters. Acer palmatum had significant positive association with Acer mono and Kalopanax pictus, but negative association with Pinus densiflora. Other positively associated species pairs were Prunus sargentii-Macckia amurensis, Quercus serrata-Kalopanax pictus, Symplocos chinensis var. pilosa-Euonymus oxyphyllus, and Ulmus davidiana var. japonica-Lindera obtusiloba. The covariation far each pair of species was evaluated based on the quantitative measures, density and basal area. Overall results showed that the association and covariation values among species generally agreed with each other. Because covariation was calculated by density and basal area of the tallied species in the sample plots, the number of species pairs of covariation tended to be greater than those of association. Especially, Pinus densiflora, considered to be pioneer species in the successional stage, had negative covariation with most of climax species. These ecological information could be applied to silvicultural practices, such as ecosystem classification, establishment of mixed hardwood forest, and tending operations for marking crop trees and desirable species.
The present study was done to determine the efficacy and safety of varicose vein removal using a minimally invasive, powered vein-extracting device with cutaneous transillumination and tumescent anesthesia techniques and then compared this to a retrospective group of conventional phlebectomy operations. There were 133 limbs in 104 patients(72 women, 32 men) treated with the use of the vein extractor aided by transcutaneous illumination. The hydrodissection was performed with Trivex™ Irrigated illuminator(Smith & Nephe $w^{ R}$) system using normal saline after the 2~3mm sized skin incision. Varicose clusters were extracted by the use of TriveTM esector(Smith & Nephe $w^{ R}$) system under transillumination. After the varisoce vein extraction, the operation area was compressed with surgical pad for bleeding control. The complication rate was 3.84% The mean number of incisions was 3.24 and mean operative time per limb was 65.9 minutes. The mean hospitalization was 1.86 days. The varicose vein extraction using transilluminated powered phlebectomy(TIPP) is a safe, efficacious and cosmetically satisfactory method. The procedure decreases the operating time and the number of incisions required to remove varicose clusters. Further evaluation and long term follow up will be necessary to determine the recurrence rate and long termcomplications.to determine the recurrence rate and long termcomplications.
Journal of the Korea Society of Computer and Information
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v.26
no.11
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pp.1-9
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2021
3D-NAND flash memory provides high capacity per unit area by stacking 2D-NAND cells having a planar structure. However, due to the nature of the lamination process, there is a problem that the frequency of error occurrence may vary depending on each layer or physical cell location. This phenomenon becomes more pronounced as the number of write/erase(P/E) operations of the flash memory increases. Most flash-based storage devices such as SSDs use ECC for error correction. Since this method provides a fixed strength of data protection for all flash memory pages, it has limitations in 3D NAND flash memory, where the error rate varies depending on the physical location. Therefore, in this paper, pages and layers with different error rates are classified into clusters through the K-means machine learning algorithm, and differentiated data protection strength is applied to each cluster. We classify pages and layers based on the number of errors measured after endurance test, where the error rate varies significantly for each page and layer, and add parity data to stripes for areas vulnerable to errors to provides differentiate data protection strength. We show the possibility that this differentiated data protection policy can contribute to the improvement of reliability and lifespan of 3D NAND flash memory compared to the protection techniques using RAID-like or ECC alone.
Robot related injuries in industrial accidents statistics during 2008~2010 have accounted for a total of 109 cases equivalent to 30~40 cases for each of those years. The number of injured compared to the dissemination of industrial robots(51,302 units/2004) can be regarded as quite low. However, the fatal injuries sustained by 7 (6.4%) out of 109 cases paints the stark reality of robot-related accident fatalities. It is a sad probability that as the automation process expands its use of industrial robots which have increased significantly in demand, the incidence of workplace accidents will also increase. Therefore, the incidence of accidents throughout the period of 2008~2010 has been analysed to prevent the injuries due to the increased use of industrial robots. In the analysis, the injuries occurred during the industrial robot operation accounted for 45.9% of the entire accidents. Thus, we examined the present status of the industrial robot operation to analyze the root cause of accidents occurred in our studied time period. We looked at a total of 469 workplaces. 456 workplaces responded in the year 2009 and survey studies were implemented at 13 of the 29 workplaces where work injuries were sustained in the year 2010. Even where protective measures and interlock devices were in place, our studies indicated that workers could access the robot area to perform the tasks in 188 sites(40.1%). Also, the 143 sites(30.5%) had control measures and equipment located in the safety fence. In addition, the robots found at 164 sites(35.0%) could be restarted without additional restarting operation. These three causes accounted for most of the workplace injuries during the industrial robot operations. Futhermore, we confirmed the fact that the protective measures of the current safety regulations were not strictly enforced. Based upon our studies and the investigation of the present status of the industrial robot operation, higher standards in training and supervision of workers in the robot operation must quickly be met in order to prevent these industrial injuries.
Recently, many suggestions have been made in image segmentation methods for extracting human organs or disease affected area from huge amounts of medical image datasets. However, images from some areas, such as brain, which have multiple structures with ambiruous structural borders, have limitations in their structural segmentation. To address this problem, clustering technique which classifies voxels into finite number of clusters is often employed. This, however, has its drawback, the influence from noise, which is caused from voxel by voxel operations. Therefore, applying image enhancing method to minimize the influence from noise and to make clearer image borders would allow more robust structural segmentation. This research proposes an efficient structural segmentation method by filtering based clustering to extract detail structures such as white matter, gray matter and cerebrospinal fluid from brain MR. First, coherence enhancing diffusion filtering is adopted to make clearer borders between structures and to reduce the noises in them. To the enhanced images from this process, fuzzy c-means clustering method was applied, conducting structural segmentation by assigning corresponding cluster index to the structure containing each voxel. The suggested structural segmentation method, in comparison with existing ones with clustering using Gaussian or general anisotropic diffusion filtering, showed enhanced accuracy which was determined by how much it agreed with the manual segmentation results. Moreover, by suggesting fine segmentation method on the border area with reproducible results and minimized manual task, it provides efficient diagnostic support for morphological abnormalities in brain.
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