• Quality Improvement in Health Care
• /
• v.8 no.2
• /
• pp.186-207
• /
• 2001

Background : This study presented an analysis of healthcare quality indicators using data mining and a development of decision support system for quality improvement. Method : Specifically, important factors influencing the key quality indicators were identified using a decision tree method for data mining based on 8,405 patients who discharged from a medical center during the period between December 1, 2000 and January 31, 2001. In addition, a decision support system was developed to analyze and monitor trends of these quality indicators using a Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. Result : Among 12 selected quality indicators, decision tree analysis was performed for 3 indicators ; unscheduled readmission due to the same or related condition, unscheduled return to intensive care unit, and inpatient mortality which have a volume bigger than 100 cases during the period. The optimum range of target group in healthcare quality indicators were identified from the gain chart. Important influencing factors for these 3 indicators were: diagnosis, attribute of the disease, and age of the patient in unscheduled returns to ICU group ; and length of stay, diagnosis, and belonging department in inpatient mortality group. Conclusion : We developed a decision support system through analysis of healthcare quality indicators and data mining technique which can be effectively implemented for utilization review and quality management in a healthcare organization. In the future, further number of quality indicators should be developed to effectively support a hospital-wide Continuous Quality Improvement activity. Through these endevours, a decision support system can be developed and the newly developed decision support system should be well integrated with the hospital Order Communication System to support concurrent review, utilization review, quality and risk management.

• Journal of Internet Computing and Services
• /
• v.13 no.2
• /
• pp.59-71
• /
• 2012

PKI-based public key scheme is outstanding in terms of authenticity and privacy. Nevertheless its application brings big burden due to the certificate/key management. It is difficult to apply it to limited computing devices in WSN because of its high encryption complexity. The Bilinear Pairing emerged from the original IBE to eliminate the certificate, is a future significant cryptosystem as based on the DDH(Decisional DH) algorithm which is significant in terms of computation and secure enough for authentication, as well as secure and faster. The practical EC Weil Pairing presents that its encryption algorithm is simple and it satisfies IND/NM security constraints against CCA. The Random Oracle Model based IBE PKG is appropriate to the structure of our target system with one secret file server in the operational perspective. Our work proposes modification of the Weil Pairing as proper to the closed network for secret file distribution[2]. First we proposed the improved one computing both encryption and message/user authentication as fast as O(DES) level, in which our scheme satisfies privacy, authenticity and integrity. Secondly as using the public key ID as effective as PKI, our improved IBE variant reduces the key exposure risk.

• Journal of Korea Society of Industrial Information Systems
• /
• v.19 no.3
• /
• pp.31-39
• /
• 2014

In KSLV-I launch mission, real-time data from the tracking stations are acquired, processed and distributed by the Mission Control System to the user group who needed to monitor processed data for safety and flight monitoring purposes. The processed trajectory data by the mission control system is sent to each tracking system for target designation in case of tracking failure. Also, the processed data are used for decision making for flight termination when anomalies occur during flight of the launch vehicle. In this paper, we propose the processing mechanism of slaving data which plays a key role of launch vehicle tracking mission. The best position data is selected by predefined logic and current status after every available position data are acquired and pre-processed. And, the slaving data is distributed to each tracking stations through time delay is compensated by extrapolation. For the accurate processing, operation timing of every procesing modules are triggered by time-tick signal(25ms period) which is driven from UTC(Universial Time Coordinates) time. To evaluate the proposed method, we compared slaving data to the position data which received by tracking radar. The experiments show the average difference value is below 0.01 degree.

• Korean Journal of Veterinary Research
• /
• v.50 no.1
• /
• pp.43-48
• /
• 2010

Animal disease surveillance system, defined as the continuous investigation of a given population to detect the occurrence of disease or infection for control purposes, has been key roles to assess the health status of an animal population and, more recently, in international trade of animal and animal products with regard to risk assessment. Especially, for a system aiming to determine whether or not a disease is present in a population sensitivity of the system should be maintained high enough not to miss an infected animal. Therefore, when planning the implementation of surveillance system a number of factors that affecting surveillance sensitivity should be taken into account. Of these parameters sample size is of important, and different approaches are used to calculate sample size, usually depending on the objective of surveillance systems. The purpose of this study was to evaluate the sensitivity of the current national serological surveillance programs for four selected bovine diseases assuming a specified sampling plan, to examine factors affecting the probability of detection, and to provide sample sizes required for achieving surveillance goal of detecting at least an infection in a given population. Our results showed that, for example, detecting low level of prevalence (0.2% for bovine tuberculosis) requires selection of all animals per typical Korean cattle farm (n = 17), and thus risk-based target surveillance for high risk groups can be an alternative strategy to increase sensitivity while not increasing overall sampling efforts. The minimum sample size required for detecting at least one positive animal was sharply increased as the disease prevalence is low. More importantly, high reliability of prevalence estimation was expected with increased sampling fraction even when zero-infected animal was identified. The effect of sample size is also discussed in terms of the maximum prevalence when zero-infected animals were identified and on the probability of failure to detect an infection. We suggest that for many serological surveillance systems, diagnostic performance of the testing method, sample size, prevalence, population size, and statistical confidence need to be considered to correctly interpret results of the system.

• Journal of the Korean Society of Physical Medicine
• /
• v.18 no.4
• /
• pp.155-162
• /
• 2023

PURPOSE: The primary objective of this study was to develop a virtual reality-based vestibular rehabilitation system to enhance balance perception, target rehabilitation specialists, and evaluate its usability. A key goal was establishing a system refinement strategy based on the collected data. METHODS: We conducted a study involving ten adults aged 10 to 29 in Gwangju Metropolitan City to evaluate the usability of a virtual reality-based vestibular rehabilitation system to enhance balance perception. After introducing the product and explaining its use to the participants, balance assessments and training were conducted using computerized dynamic posturography (CDP) (also called the test of balance [TOB]). Subsequently, participants were given a questionnaire to evaluate subjective stability, operability, and satisfaction. Frequency analysis was utilized to determine the frequency of the variable values of the measurement items in the survey for descriptive statistics. RESULTS: We found that the average usability score was 2.587. When broken down by category, stability received an average rating of 2.725, operability scored an average of 2.783, and satisfaction averaged 2.454. These findings suggest that most participants experienced positive sentiments and considerable satisfaction. CONCLUSION: The study successfully developed a virtual reality-based vestibular rehabilitation system, which was an improvement over the previous model and addressed its shortcomings. The results show that users with vestibular impairments are satisfied and more engaged with this system, indicating that additional studies are warranted.

• Database Research
• /
• v.34 no.3
• /
• pp.137-147
• /
• 2018

A key to a well-performing human activity recognition (HAR) system through machine learning technique is the availability of a substantial amount of labeled data. Collecting sufficient labeled data is an expensive and time-consuming task. To build a HAR system in a new environment (i.e., the target domain) with very limited labeled data, it is unfavorable to naively exploit the data or trained classifier model from the existing environment (i.e., the source domain) as it is due to the domain difference. While traditional machine learning approaches are unable to address such distribution mismatch, transfer learning approach leverages the utilization of knowledge from existing well-established source domains that help to build an accurate classifier in the target domain. In this work, we propose a transfer learning approach to create an accurate HAR classifier with very limited data through the multitask neural network. The classifier loss function minimization for source and target domain are treated as two different tasks. The knowledge transfer is performed by simultaneously minimizing the loss function of both tasks using a single neural network model. Furthermore, we utilize the unlabeled data in an unsupervised manner to help the model training. The experiment result shows that the proposed work consistently outperforms existing approaches.

• Mass Spectrometry Letters
• /
• v.10 no.1
• /
• pp.11-17
• /
• 2019

Drosophila melanogaster (fruits fly) is a representative model system widely used in biological studies because its brain function and basic cellular processes are similar to human beings. The whole head of the fly is often used to obtain the key function in brain-related diseases like degenerative brain diseases; however the biomolecular distribution of the head may be slightly different from that of a brain. Herein, lipid profiles of the head and dissected brain samples of Drosophila were studied using electrospray ionization-mass spectrometry (ESI-MS). According to the sample types, the detection of phospholipid ions was suppressed by triacylglycerol (TAG), or the specific phospholipid signals that are absent in the mass spectrum were measured. The lipid distribution was found to be different in the wild-type and the microRNA-14 deficiency model ($miR-14{\Delta}^1$) with abnormal lipid metabolism. A few phospholipids were also profiled by comparison of the head and the brain in two fly model systems. The mass spectra showed that the phospholipid distributions in the $miR-14{\Delta}^1$ model and the wild-type were different, and principal component analysis revealed a correlation between some phospholipids (phosphatidylethanolamine (PE), phosphatidylinositol (PI), and phosphatidylserine (PS)) in $miR-14{\Delta}^1$. The overall results suggested that brain-related lipids should be profiled using fly samples after dissection for more accurate analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.11
• /
• pp.3950-3969
• /
• 2021

Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.

• Journal of Periodontal and Implant Science
• /
• v.53 no.1
• /
• pp.20-37
• /
• 2023

Purpose: Our pilot study showed that a 3-dimensional dual drug delivery scaffold (DDDS) loaded with Chinese herbs significantly increased the regenerated bone volume fraction. This study aimed to confirm the synergistic anti-inflammatory and osteogenic preclinical effects of this system. Methods: The targets and pathways of parthenolide and naringin were predicted. Three cell models were used to assess the anti-inflammatory effects of parthenolide and the osteogenic effects of naringin. First, the distance between the cementoenamel junction and alveolar bone crest (CEJ-ABC) and the bone mineral density (BMD) of surgical defects were measured in a rat model of periodontitis with periodontal fenestration defects. Additionally, the mRNA expression levels of matrix metallopeptidase 9 (MMP9) and alkaline phosphatase (ALP) were measured. Furthermore, the number of inflammatory cells and osteoclasts, as well as the protein expression levels of tumor necrosis factor-alpha (TNF-α) and levels of ALP were determined. Results: Target prediction suggested prostaglandin peroxidase synthase (PTGS2) as a potential target of parthenolide, while cytochrome P450 family 19 subfamily A1 (CYP19A1) and taste 2 receptor member 31 (TAS2R31) were potential targets of naringin. Parthenolide mainly targeted inflammation-related pathways, while naringin participated in steroid hormone synthesis and taste transduction. In vitro experiments revealed significant antiinflammatory effects of parthenolide on RAW264.7 cells, and significant osteogenic effects of naringin on bone marrow mesenchymal stem cells and MC3T3-E1 cells. DDDS loaded with parthenolide and naringin decreased the CEJ-ABC distance and increased BMD and ALP levels in a time-dependent manner. Inflammation was significantly alleviated after 14 days of DDDS treatment. Additionally, after 56 days, the DDDS group exhibited the highest BMD and ALP levels. Conclusions: DDDS loaded with parthenolide and naringin in a rat model achieved significant synergistic anti-inflammatory and osteogenic effects, providing powerful preclinical evidence.

• Progress in Medical Physics
• /
• v.34 no.4
• /
• pp.48-54
• /
• 2023

Purpose: In this study, the dosimetric characteristics of lung stereotactic body radiotherapy (SBRT) plans using the new Halcyon system were analyzed to assess its suitability. Methods: We compared the key dosimetric parameters calculated for the Halcyon SBRT plans with those of a conventional C-arm linear accelerator (LINAC) equipped with a high-definition multileaf collimator (HD-MLC)-Trilogy Tx. A total of 10 patients with non-small-cell lung cancer were selected, and all SBRT plans were generated using the RapidArc technique. Results: Trilogy Tx exhibited significant superiority over Halcyon in terms of target dose coverage (conformity index, homogeneity index, D_{0.1 cc}, and D_95%) and dose spillage (gradient). Trilogy Tx was more efficient than Halcyon in the lung SBRT beam delivery process in terms of the total number of monitor units, modulation factor, and beam-on time. However, it was feasible to achieve a dose distribution that met SBRT plan requirements using Halcyon, with no significant differences in satisfying organs at risk dose constraints between both plans. Conclusions: Results confirm that Halcyon is a viable alternative for performing lung SBRT in the absence of a LINAC equipped with HD-MLC. However, extra consideration should be taken in determining whether to use Halcyon when the planning target volume setting is enormous, as in the case of significant tumor motions.