• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.35-42
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• 2021

This paper presents an on-line finite element model updating method for in-service structures using measured data. Conventional updating methods, which are based on numerical optimization, are not efficient for on-line updating because they generally require repeated eigenvalue analyses until convergence criteria are met. The proposed method enables fully automated on-line finite element model updating, almost simultaneously with vibration measurement, without any user intervention or off-line procedures. The automated covariance-driven stochastic subspace identification (Cov-SSI) method is utilized to identify modal frequencies and vectors, and the identified modal data is fed to the neural network of the inverse eigenvalue function to produce the updated finite element model parameters. Numerical examples for a wind excited 20-story building structure shows that the proposed method can update the series of finite element model parameters automatically. It is also shown that sudden changes in the structural parameters can be detected and traced successfully.

• Journal of Korean Port Research
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• v.9 no.2
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• pp.9-24
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• 1995

The intensification of the competition among container terminals has led to important affect such as, decision making or aggressive intervention of customers for terminal operation. Therefore, in case of developed ports, the large transition of port operation is composed of the press of terminal customer than decision making of terminal manager. Overall port tariffs for using terminal is made out by the conference of terminal customers than the supreme headquarters of terminal operation, and the related investment of terminal has been made according to requisition or proposal of customers. Therefore, among decision making problems that shippers, shipping companies, and freight forwarder among decision making problems that shippers, shipping companies, and freight forwarder face, the choice of the container terminal is one of the most important problems. So, the decision making of the users seems to have a significant impact on the competitive power of container terminals. The main objective of this study is to design port marketing strategy for strengthening the competitive power of container terminals. The results of this study were found as follows: Firstly, port authority should establish user-oriented operation policy of terminal as the means of activating the opinion window, using terminal monitoring system(TMS). Secondly, terminal planning and development of government should be made to minimize the lead time, to induce the civil capital and to utilize the economies of scale. Thirdly, port authority needs to endeavor to analyze the information of competing foreign terminals as well to promote the concentrated marketing for the terminal on the users, to train the expert and to develop the new port charge system. Fourthly, to improve the competitive power of the container terminal, Port Authority should optimize the subsystems related to port marketing, far more these systems should be joined organically to work effectively. Finally, port authority system should be introduced, Namely, port should have the enterprise inclination as well s the public inclination.

• The Journal of Bigdata
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• v.7 no.1
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• pp.29-36
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• 2022

The prevalence of stress and depression among emotional workers is increasing due to the rapid increase in emotional labor and service workers. However, the current mental health management of emotional workers is difficult to consider the emotional response at the time of stress situations, and the existing mental health management is limited because the individual's base state is not reflected. In this study, we present mental healthcare digital twin solution technology, a personalized stress risk management solution. For mental health risk management due to emotional labor, a solution simulation is performed to accurately predict stress risk through synchronization/modeling of dynamic objects in virtual space by extracting individual stress risk factors such as emotional/physical response and environment into various modalities. It provides a mental healthcare digital twin solution for predicting personalized mental health risks that can be configured with modalities and objects tailored to the environment of emotional workers and improved according to user feedback.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.237-246
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• 2006

In order to evaluate the seismic performance of damaged reinforced concrete members, particularly bridge piers, an inelastic time-dependent element is proposed. The proposed element enables increased characteristics due to structural intervention(i.e., repair or retrofitting) to be accurately reflected to the degraded strength and stiffness of the members. The inelastic time-dependent element having both birth and death time can freely be activated within the user-defined time intervals during static and dynamic time-history analysis. Comparative studies are carried out for reinforced concrete bridge piers that are repaired and retrofitted. Analytical predictions using the developed element show reasonable correlation with experimental results. Also conducted is a nonlinear time-history analysis of a reinforced concrete bridge under multiple earthquakes. The comparative analytical results prove the validation of current development. In all, it is concluded that the present element is capable of providing salient features for the healthy evaluation of seismic performance and hence seismic stability assessment of RC bridge piers being repaired and retrofitted.

• Nutrition Research and Practice
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• v.18 no.2
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• pp.294-307
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• 2024

BACKGROUND/OBJECTIVES: Dietitians frequently use nutrition education tools to facilitate dietary counselling sessions. Nevertheless, these tools may require adaptation to keep pace with technological advancements. This study had a 2-fold purpose: first, to identify the types of nutrition education tools currently in use, identify their limitations, and explore dietitians' perspectives on the importance of these tools; second, to investigate the features that dietitians prefer in digital nutrition education tools. SUBJECTS/METHODS: A semi-structured face-to-face interview was conducted among 15 dietitians from selected public hospitals, primary care clinics, and teaching hospitals in Malaysia. Inductive thematic analysis of the responses was conducted using NVivo version 12 software. RESULTS: Most dietitians used physical education tools including the healthy plate model, pamphlets, food models, and flip charts. These tools were perceived as important as they facilitate the nutrition assessment process, deliver nutrition intervention, and are time efficient. However, dietitians described the current educational tools as impersonal, outdated, limited in availability due to financial constraints, unhandy, and difficult to visualise. Alternatively, they strongly favoured digital education tools that provided instant feedback, utilised an automated system, included a local food database, were user-friendly, developed by experts in the field, and seamlessly integrated into the healthcare system. CONCLUSION: Presently, although dietitians have a preference for digital educational tools, they heavily rely on physical nutrition education tools due to their availability despite the perception that these tools are outdated, impersonal, and inconvenient. Transitioning to digital dietary education tools could potentially address these issues.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• v.25 no.3
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• pp.275-287
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• 2023

Objective: Flow diverting stents (FDS) are a validated device in the treatment of intracranial aneurysms, allowing for minimally invasive intervention. However, after its approval for use in the United States in 2011, post-market surveillance of adverse events is limited. This study aims to address this critical knowledge gap by analyzing the FDA Manufacturer and User Facility Device Experience (MAUDE) database for patient and device related (PR and DR) reports of adverse events and malfunctions. Methods: Using post-market surveillance data from the MAUDE database, PR and DR reports from January 2012-December 2021 were extracted, compiled, and analyzed with R-Studio version 2021.09.2. PR and DR reports with insufficient information were excluded. Raw information was organized, and further author generated classifications were created for both PR and DR reports. Results: A total of 2203 PR and 4017 DR events were recorded. The most frequently reported PR adverse event categories were cerebrovascular (60%), death (11%), and neurological (8%). The most frequent PR adverse event reports were death (11%), thrombosis/thrombus (9%) cerebral infarction (8%), decreased therapeutic response (7%), stroke/cerebrovascular accident (6%), intracranial hemorrhage (5%), aneurysm (4%), occlusion (4%), headache (4%), neurological deficit/dysfunction (3%). The most frequent DR reports were activation/positioning/separation problems (52%), break (9%), device operates differently than expected (4%), difficult to open or close (4%), material deformation (3%), migration or expulsion of device (3%), detachment of device or device component (2%). Conclusions: Post-market surveillance is important to guide patient counselling and identify adverse events and device problems that were not identified in initial trials. We present frequent reports of several types of cerebrovascular and neurological adverse events as well as the most common device shortcomings that should be explored by manufacturers and future studies. Although inherent limitations to the MAUDE database are present, our results highlight important PR and DR complications that can help optimize patient counseling and device development.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.25-34
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• 2020

In the current medical information system, a system environment is constructed in which Biometric data generated by using IoT or medical equipment connected to a patient can be stored in a medical information server and monitored at the same time. Also, the patient's biometric data, medical information, and personal information after simple authentication using only the ID / PW via the mobile terminal of the medical staff are easily accessible. However, the method of accessing these medical information needs to be improved in the dimension of protecting patient's personal information, and provides a quick authentication system for first aid. In this paper, we implemented an automatic authentication system based on the patient's situation and evaluated its performance. Patient's situation was graded into normal and emergency situation, and the situation of the patient was determined in real time using incoming patient biometric data from the ward. If the patient's situation is an emergency, an emergency message including an emergency code is send to the mobile terminal of the medical staff, and they attempted automatic authentication to access the upper medical information of the patient. Automatic authentication is a combination of user authentication(ID/PW, emergency code) and mobile terminal authentication(medical staff's role, working hours, work location). After user authentication, mobile terminal authentication is proceeded automatically without additional intervention by medical staff. After completing all authentications, medical staffs get authorization according to the role of medical staffs and patient's situations, and can access to the patient's graded medical information and personal information through the mobile terminal. We protected the patient's medical information through limited medical information access by the medical staff according to the patient's situation, and provided an automatic authentication without additional intervention in an emergency situation. We performed performance evaluation to verify the performance of the implemented automatic authentication system.

• Journal of Preventive Medicine and Public Health
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• v.36 no.4
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• pp.390-398
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• 2003

Objectives : To evaluate the degree of adolescent internet addiction, and investigate its relationship to the general characteristics, internet environments, and contents, especially the stress measured by the psychosocial wellbeing index-short form(PWI-SF). Methods : The data was obtained from self-administered questionnaires from 886 11th grade urban area students. The questionnaires consisted of general characteristics, internet user's environments, frequencies by internet contents, internet addiction test and PWI-SF. Results : The possible rate of internet use at home was 95.1%, and the area of most internet use was the home. The frequencies of internet game and porno site use were higher in males, with web searching and community uses higher in females. The total mean of internet addiction score was 56.8, and was higher for male than for female students. From multiple regression, as analyzed by the internet addiction score as a dependent variable, on-line friends, internet use times, years of internet use, frequencies of internet game, & porno site use, and PWI-SF scores were significant in male. Internet use times, the frequencies of internet game, chatting, community use, and PWI-SF score were significant in female. Four PWI-SF subscales(social role & self reliability, depression, general health & vitality, and sleep disturbance & anxiety) and internet addiction were significantly correlated in both male and female students, with depression having the most correlation. Conclusion : The results of this study suggest that intervention should be provided to prevent internal addiction, especially for coping with stress in Korean teenage students.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.12-18
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• 2006

This paper presents a method to extract a good high-resolution image from a low-resolution video in an automatic manner. Since a high-resolution image reconstruction method utilizing several low-resolution input images works better than a conventional interpolation method utilizing single low-resolution input image only if the input images are well registered onto a common high-resolution grid, low-resolution input images should be carefully chosen so that the registration errors can be carefully considered. In this paper, the statistics obtained from the motion-compensated low-resolution images are utilized to evaluate the feasibility of the input image candidates. Maximum motion-compensation error is estimated from the high-resolution image observation model. U the motion-compensation error of the input image candidate is greater than the estimated maximum motion-compensation error, the input image candidate is discarded. The number of good input image candidates and the statistics of the motion-compensation errors are used to choose final input images. The final input images chosen from the input image selection block are given to the following high-resolution image reconstruction block. It is expected that the proposed method is utilized to extract a good high-resolution image efficiently from a low-resolution video without any user intervention.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.57-66
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• 2011

To prevent cardiac diseases, quantifying cardiac function is important in routine clinical practice by analyzing blood volume and ejection fraction. These works have been manually performed and hence it requires computational costs and varies depending on the operator. In this paper, an automatic left ventricle segmentation algorithm is presented to segment left ventricle on cardiac magnetic resonance images. After coil sensitivity of MRI images is compensated, a K-mean clustering scheme is applied to segment blood area. A graph searching scheme is employed to correct the segmentation error from coil distortions and noises. Using cardiac MRI images from 38 subjects, the presented algorithm is performed to calculate blood volume and ejection fraction and compared with those of manual contouring by experts and GE MASS software. Based on the results, the presented algorithm achieves the average accuracy of 6.2mL${\pm}$5.6, 2.9mL${\pm}$3.0 and 2.1%${\pm}$1.5 in diastolic phase, systolic phase and ejection fraction, respectively. Moreover, the presented algorithm minimizes user intervention rates which was critical to automatize algorithms in previous researches.