• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.50-59
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• 2014

In mobile healthcare service, the accurate detection and the notification of the emergency situation are important to chronic patients' life. In the existing healthcare service, the medical staff or medical service provider always judges patients' health status by monitoring from the measured from bio-data. However, it is difficult to monitor many patients in real-time simultaneously, because the medical staff should monitor the health status continuously. Furthermore, an emergency condition diagnosis based solely on the statistical level of the bio-data may be difficult, since the emergency judgment of the bio-data might differ depending on the health characteristics of each person such as age, history of disease, gender, etc. In order to solve this problem, this article presents an mobile healthcare system for emergency bio-data management using a personalized emergency policy. The salient feature of the proposed mobile healthcare system is that the characteristics of the health status of an unique patient is defined to the policy, which is used to judge the emergency condition of the bio-data measured from the patient. The prototype of proposed mobile healthcare system has been built to demonstrate the design concept.

• Journal of Biomedical Engineering Research
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• v.44 no.4
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• pp.255-263
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• 2023

Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.176-179
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• 2001

A portable bio-signal measurement system for 24-hours continuous health monitoring of the elderly and the disabled is presented. The measurement system has the functions of acquisition of various bio-signals such as ECG, EMG and EEG, wireless data transmission/receive and adjustment of parameters such as gain and cut-off frequency. The data is sent to a host computer or other device via a Bluetooth. The design targets of the developing system for volume and power consumption are $20{\times}30{\times}5(mm^3)$ and 8mW.

• Genomics & Informatics
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• v.8 no.2
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• pp.94-96
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• 2010

Integrating various pathway data collections to create new biological knowledge is a challenge, for which novel computational tools play a key role. For this purpose, we developed the Java-based conversion modules KGML2SBML and KGML2BioPAX to translate KGML (KEGG Markup Language) into a couple of common data exchange formats: SBML (Systems Biology Markup Language) and BioPAX (Biological Pathway Exchange). We hope that our work will be beneficial for other Java developers when they extend their bioinformatics system into SBML- or BioPAX-aware analysis tools. This is part of our ongoing effort to develop an ultimate KEGG-based pathway enrichment analysis system.

• Bulletin of the Korean Chemical Society
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• v.27 no.10
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• pp.1537-1541
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• 2006

The $^1H$ and $^{13}C$ chemical shifts of eleven flavone derivatives were completely determined by basic 1D and 2D NMR experiments. Nineteen flavone derivatives including the above eleven derivatives were examined for anti-oxidative effects using the 1,1-diphenyl-2-picryl-hydrazyl assay and Caenorhabditis elegans. In order to understand the relationships between the structures of flavone derivatives and their anti-oxidative activities, a Comparative Molecular Field Analysis was performed.

• Journal of Bio-Environment Control
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• v.30 no.1
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• pp.19-26
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• 2021

In this study, analysis was performed to identify three greenhouses located in the same area using principal component analysis (PCA) and linear discrimination analysis (LDA). The environmental data in the greenhouse were from 3 farms in the same area, and the values collected at 1 hour intervals for a total of 4 weeks from April 1 to April 28 were used. Before analyzing the data, it was pre-processed to normalize the data, and the analysis was performed by dividing it into 80% of the training data and 20% of the test data. As a result of PCA and LDA analysis, it was found that PCA classification accuracy was 57.51% and LDA classification was 67.06%, indicating that it can be classified by greenhouse. Based on the farmhouse data classified in advance, the data of the new environment can be classified into specific groups to determine the tendency of the data. Such data is judged to be a way to increase the utilization of data by facilitating identification.

• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.652-662
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• 2015

It is necessary to develop small, implantable bio-telemetry systems which can measure and transmit patients' bio-signals from internal body to external receiver. When measuring bio-signals, like electrical bio-signals, acoustic bio-signal measurement has also a big clinical usefulness. But, sound signal has larger frequency bandwidth than any other bio-signals. When considering these issues, a wireless telemetry system which has rapid data transmission rate proportional to wide frequency bandwidth is necessary to be developed. The bluetooth module is used to overcome the data rate limitation caused by the large frequency bandwidth. In this paper, a novel multimedia bluetooth biotelemetry system was developed which consists of transmitter module located in the body and receiver device located outside of the body. The transmitter consists of microphone, bluetooth, and wireless charging device. And the receiver consists of bluetooth and codec system. The sound inside the skin is captured by microphone and sent to receiver by bluetooth while charging. The wireless charging system constantly supplies the electric power to the system. To verify the performance of the developed system, an in vitro experiment has been performed. The results show that the proposed biotelemetry system has ability to acquire the sound signals under the skin.

• Genomics & Informatics
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• v.13 no.3
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• pp.81-85
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• 2015

Molecular characterization technology in genetically modified organisms, in addition to how transgenic biotechnologies are developed now require full transparency to assess the risk to living modified and non-modified organisms. Next generation sequencing (NGS) methodology is suggested as an effective means in genome characterization and detection of transgenic insertion locations. In the present study, we applied NGS to insert transgenic loci, specifically the epidermal growth factor (EGF) in genetically modified rice cells. A total of 29.3 Gb (${\sim}72{\times}coverage$) was sequenced with a $2{\times}150bp$ paired end method by Illumina HiSeq2500, which was consecutively mapped to the rice genome and T-vector sequence. The compatible pairs of reads were successfully mapped to 10 loci on the rice chromosome and vector sequences were validated to the insertion location by polymerase chain reaction (PCR) amplification. The EGF transgenic site was confirmed only on chromosome 4 by PCR. Results of this study demonstrated the success of NGS data to characterize the rice genome. Bioinformatics analyses must be developed in association with NGS data to identify highly accurate transgenic sites.

• Restorative Dentistry and Endodontics
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• v.46 no.4
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• pp.59.1-59.14
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• 2021

Objectives: This study compared the Biodentine, MTA Repair HP, and Bio-C Repair bioceramics in terms of bond strength to dentin, failure mode, and compression. Materials and Methods: Fifty-four slices obtained from the cervical third of 18 single-rooted human mandibular premolars were randomly distributed (n = 18). After insertion of the bioceramic materials, the push-out test was performed. The failure mode was analyzed using stereomicroscopy. Another set of cylindrically-shaped bioceramic samples (n = 10) was prepared for compressive strength testing. The normality of data distribution was analyzed using the Shapiro-Wilk test. The Kruskal-Wallis and Friedman tests were used for the push-out test data, while compressive strength was analyzed with analysis of variance and the Tukey test, considering a significance level of 0.05. Results: Biodentine presented a higher median bond strength value (14.79 MPa) than MTA Repair HP (8.84 MPa) and Bio-C Repair (3.48 MPa), with a significant difference only between Biodentine and Bio-C Repair. In the Biodentine group, the most frequent failure mode was mixed (61%), while in the MTA Repair HP and Bio-C Repair groups, it was adhesive (94% and 72%, respectively). Biodentine showed greater resistance to compression (29.59 ± 8.47 MPa) than MTA Repair HP (18.68 ± 7.40 MPa) and Bio-C Repair (19.96 ± 3.96 MPa) (p < 0.05). Conclusions: Biodentine showed greater compressive strength than MTA Repair HP and Bio-C Repair, and greater bond strength than Bio-C Repair. The most frequent failure mode of Biodentine was mixed, while that of MTA Repair HP and Bio-C Repair was adhesive.

• Korean Journal of Environmental Agriculture
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• v.30 no.4
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• pp.357-366
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• 2011

BACKGROUND: Mathematical model such as GLEAMS have been developed and successfully applied to upland fields to estimate the level of pesticide residues in soil. But, the GLEAMS model rarely applied to the Korean conditions. METHODS AND RESULTS: To evaluate pesticide transport in soil residue using the GLEAMS model from pepper plot, Alachlor, Endosulfan, Cypermethrin and Fenvalerate were applied for standard and double rate. Soil sampling was conducted and decaying patterns of pesticides were investigated. Observed climate data such as temperature and irrigation amount were used for hydrology simulation. The observed pesticide residue data of 2008 were used for parameter calibration, and validation of GLEAMS model was conducted with observed data of 2009. After calibration, the $K_{oc}$ (Organic carbon distribution coefficient) and WSHFRC (Washoff fraction) parameters were identified as key parameters. The simulated concentrations of the pesticides except Fenvalerate were sensitive to $K_{oc}$ parameter. Overall, soil residue concentrations of Alachlor, Cypermethrin and Fenvalerate were fairly simulated compared to those of Endosulfan. The applicability of the GLEAMS model was also confirmed by statistical analysis. CONCLUSION(s): GLEAMS model was eligible for evaluation of pesticide soil residue for Alachlor, Cypermethrin and Fenvalerate.