• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.5
• /
• pp.105-112
• /
• 2023

Steel fiber reinforced concrete (SFRC) exhibits enhanced strength and superior energy dissipation capacity compared to normal concrete, and it can also reduce crack propagation and fragmentation of concrete even when subjected to blast loads. In this study, the parameters defining failure surface and damage function of the K&C concrete nonlinear model were proposed to be applied for the properties of SFRC in LS-DYNA. Single element analysis has been conducted to validate the proposed parameters in the K&C model, which provided very close simulations on the compressive behavior of SFRC. In addition, blast analysis was performed on SFRC columns with different volume fractions of steel fibers, and the blast resistance of SFRC columns was quantitatively analyzed with Korea Occupational Safety & Health Agency (KOSHA) guidelines.

• International journal of advanced smart convergence
• /
• v.12 no.4
• /
• pp.434-442
• /
• 2023

The relationship between acute kidney injury (AKI) prediction and nephrotoxic drugs, or drugs that adversely affect kidney function, is one that has yet to be explored in the critical care setting. One contributing factor to this gap in research is the limited investigation of drug modalities in the intensive care unit (ICU) context, due to the challenges of processing prescription data into the corresponding drug representations and a lack in the comprehensive understanding of these drug representations. This study addresses this gap by proposing a novel approach that leverages patient prescription data as a modality to improve existing models for AKI prediction. We base our research on Electronic Health Record (EHR) data, extracting the relevant patient prescription information and converting it into the selected drug representation for our research, the extended-connectivity fingerprint (ECFP). Furthermore, we adopt a unique multimodal approach, developing machine learning models and 1D Convolutional Neural Networks (CNN) applied to clinical drug representations, establishing a procedure which has not been used by any previous studies predicting AKI. The findings showcase a notable improvement in AKI prediction through the integration of drug embeddings and other patient cohort features. By using drug features represented as ECFP molecular fingerprints along with common cohort features such as demographics and lab test values, we achieved a considerable improvement in model performance for the AKI prediction task over the baseline model which does not include the drug representations as features, indicating that our distinct approach enhances existing baseline techniques and highlights the relevance of drug data in predicting AKI in the ICU setting.

• Membrane and Water Treatment
• /
• v.14 no.4
• /
• pp.163-173
• /
• 2023

The presence of high amounts of organic and inorganic contaminants in textile wastewater is a major environmental concern. Therefore, the treatment of textile wastewater is an urgent issue to save the aquatic environment. The disposal of large quantities of untreated textile wastewater into inland water bodies can cause serious water pollution. In this study, synthetic dye wastewater samples were prepared using orange dye in the laboratory. The synthetic samples were then treated by a batch adsorption process using the prepared activated carbon (AC) from date pits. The wastewater parameters studied were the pH, total dissolved solids (TDS), total suspended solids (TSS), electrical conductivity (EC) and salinity. The activated adsorption process showed that the maximum removal efficiencies of electric conductivity (EC), salinity, TDS and TSS were 65%, 92%, 89% and 90%, respectively. The removal efficiencies were proportional to the increase in contact time (30-120 min) and AC adsorbent dose (1, 3 and 5 g/L). The adsorption profile indicates that 5 g/L of adsorbent delivers better results for TDS, EC, TSS and salinity at contact time of 120 min. The adsorption characteristics are better suited to the pseudo-second-order kinetic model than to the pseudo-first-order kinetic model. The Langmuir and Freundlich isotherms were well suited for describing the adsorption or contact behavior of EC and TSS within the studied system.

• Smart Structures and Systems
• /
• v.33 no.2
• /
• pp.145-163
• /
• 2024

The evaluation of dynamic characteristics of bridges under operational traffic loads is a crucial aspect of bridge structural health monitoring. In the vehicle-bridge interaction (VBI) system, the vibration responses of bridge exhibit time-varying characteristics. To address this issue, an accurate time-frequency analysis method that combines the autoregressive power spectrum based empirical wavelet transform (AR-EWT) and local maximum synchrosqueezing transform (LMSST) is proposed to identify the time-varying instantaneous frequencies (IFs) of the bridge in the VBI system. The AR-EWT method decomposes the vibration response of the bridge into mono-component signals. Then, LMSST is employed to identify the IFs of each mono-component signal. The AR-EWT combined with the LMSST method (AR-EWT+LMSST) can resolve the problem that LMSST cannot effectively identify the multi-component signals with weak amplitude components. The proposed AR-EWT+LMSST method is compared with some advanced time-frequency analysis techniques such as synchrosqueezing transform (SST), synchroextracting transform (SET), and LMSST. The results demonstrate that the proposed AR-EWT+LMSST method can improve the accuracy of identified IFs. The effectiveness and applicability of the proposed method are validated through a multi-component signal, a VBI numerical model with a four-degree-of-freedom half-car, and a VBI model experiment. The effect of vehicle characteristics, vehicle speed, and road surface roughness on the identified IFs of bridge are investigated.

• Information Systems Review
• /
• v.19 no.2
• /
• pp.57-70
• /
• 2017

Researchers and industry managers highlight the emergence of mobile healthcare market given the rapid development of IT and the expansion of average life expectancy. Medical institutions, such as university hospitals, are aiming to achieve convenience and effectiveness of treatment by providing patient education through a mobile device. This study examines a case related to the development and usage of a mobile application based on Lean Canvas, namely, the Smart Explanation Service released by Samsung Medical Center. This application comprehensively analyzes the usage status of mobile application-based patient education and its application in clinical settings. This study also examines the level of satisfaction of patients and medical workers toward this application. The result of this study is expected to provide meaningful implication to medical institutions and related industries and enable them to create and offer prepare mobile healthcare services.

• Asia pacific journal of information systems
• /
• v.18 no.1
• /
• pp.145-162
• /
• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Journal of Internet Computing and Services
• /
• v.16 no.2
• /
• pp.109-115
• /
• 2015

The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.

• Journal of Environmental Health Sciences
• /
• v.42 no.4
• /
• pp.266-273
• /
• 2016

Objectives: This study evaluated the virucidal efficacy against avian influenza virus (AIV) of a disinfectant spray containing 0.25% grapefruit seed extract, 0.2% citric acid, 0.0625% malic acid and 0.0125% benzalkonium chloride. Methods: The disinfectant spray was diluted several times with hard water (HW) and organic matter (OM). Two point five mL of each diluent was added into each test tube, and 2.5 mL of AIV suspension was inserted into each test tube. After 30 minutes of virus-disinfectant contact reaction at $4^{\circ}C$, 2.5 mL of 10% inactivated fetal bovine serum was added into each test tube to neutralize the sanitizer efficacy. The neutralized solutions were serial 10-fold dilutions with phosphate buffer solution, and 0.2 mL of the diluents was injected into the allantoic cavity of five ten-day-old-chickens per dilution time. After incubation of the embryos for five days, the viability of the AIV was examined by hemagglutination titer. The valid dilution of the disinfectant spray was estimated according to the dilution time that the virus titer was inactivated more than $10^4$ 50% egg-infective dose (EID50)/mL compared with pathogen control. Results: In HW and OM conditions, the valid dilutions of the disinfectant spray against AIV were seven- and three-fold dilutions, respectively. The AIV titer of the pathogen control was more than 6.1 log10EID50/mL, and there was no embryonic toxicity. Conclusion: The present study showed that this disinfectant spray has effective virucidal activity against AIV.

• Journal of Life Science
• /
• v.20 no.9
• /
• pp.1299-1305
• /
• 2010

Cardiac troponin-I (cTnI), creatine kinase-MB (CK-MB), and C-reactive protein (CRP) are routine cardiac markers for the diagnosis of cardiovascular disease. Recently, brain natriuretic peptide (BNP) has garnered attention as a marker of heart failure. This study was retrospectively designed to investigate the relationships between preoperative BNP, other cardiac markers levels and perioperative parameters in seventy-four adult patients that underwent off-pump coronary artery bypass grafting (OPCAB) and to assess its usefulness for predicting postoperative outcomes. Preoperative levels of BNP, cTnI, CK-MB, and CRP had significantly positive or negative correlations with echocadiographic parameters. There were significantly positive relationships between BNP, cTnI, CK-MB, and CRP concentration. Postoperative mechanical ventilation time had a positive correlation to preoperative levels of cTnI, CK-MB, and CRP, while ICU-staying period had a positive correlation with BNP, cTnI and CK-MB. These results reveal that a preoperative level of BNP is a good predictor and that its combination with cTnI, CK-MB, and CRP might be useful for diagnosis and comprehensive risk stratification of patients with coronary heart diseases, as well as prognosis of perioperative outcomes in OPCAB patients.

• Smart Structures and Systems
• /
• v.14 no.2
• /
• pp.209-224
• /
• 2014

With more and more built long-term structural health monitoring (SHM) systems, it has been considered to apply monitored data to learn the reliability of bridges. In this paper, based on a long-term SHM system, especially in which the sensors were embedded from the beginning of the construction of the bridge, a method to calculate the localized reliability around an embedded sensor is recommended and implemented. In the reliability analysis, the probability distribution of loading can be the statistics of stress transferred from the monitored strain which covered the effects of both the live and dead loads directly, and it means that the mean value and deviation of loads are fully derived from the monitored data. The probability distribution of resistance may be the statistics of strength of the material of the bridge accordingly. With five years' monitored strains, the localized reliabilities around the monitoring sensors of a bridge were computed by the method. Further, the monitored stresses are classified into two time segments in one year period to count the loading probability distribution according to the local climate conditions, which helps us to learn the reliability in different time segments and their evolvement trends. The results show that reliabilities and their evolvement trends in different parts of the bridge are different though they are all reliable yet. The method recommended in this paper is feasible to learn the localized reliabilities revealed from monitored data of a long-term SHM system of bridges, which would help bridge engineers and managers to decide a bridge inspection or maintenance strategy.