• Clinical and Experimental Pediatrics
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• v.48 no.5
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• pp.476-480
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• 2005

Immunosuppressive therapy in pediatric renal transplant recipients is changing consequence of the increasing number of available immunosuppressive agents. The optimal use of immunosuppressive agents requires a thorough understanding of the pharmacokinetic characteristics, but the information on the pharmacokinetic characteristics of these drugs in pediatric transplant recipients is still limited. In general, patients younger than 5 years old show higher clearance rates, therefore the need for higher dosages in younger patients seems evident. By the therapeutic drug monitoring, trough($C_{min}$) and peak level($C_{max}$) are measured and the area under the blood concentration-time curve(AUC), which is taken as being representative of total systemic exposure can be calculated. Cyclosporine A (CSA) has poor bioavailability, which contributes to high inter- and intra-patient pharmacokinetic variability. CSA concentration measured 2 hours after administration($C_2$) has better correlation with the AUC than $C_{min}$ and is an alternative technique that predicts the AUC. Tacrolimus(Tac) has a great deal of inter-individual variability like CSA but intra-individual variability in systemic exposure is considered to be low. Both CSA and Tac are metabolized by a cytochrome P-450 enzyme isoform(CYP3A4). We should consider changing the dosages when CSA or Tac is used in combination with the medicines that inhibit or induce the CYP3A4. In case of steroid-free immunosuppressive therapy, the blood concentration of Tac should be frequently checked and dosage adjustment may be needed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1293-1302
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• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.333-335
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• 2010

Global warming gas caused an increase in a direct and indirect problems like the rising sea level, seawater overflowing and a coastal flooding. The loss and damage of the republic of korea are increasing because of the rising sea level. As a result, It is necessary to establish the foundation of the monitoring of the sea level changes for the flooding prevention. A new measurement technique is developed using GPS equipped ship to make up for the spatial-temporal and economical problems by this study. We compared the data using GPS with the value for height of the tide. And we corrected the errors using the more accurate data that we studied. In addition to we studied that the corrected value had statistical significance and similarity compared with the observed value using GPS. The following studies also performed : When the observed value of tide by a tide observatory and by using GPS are applied to sounding ; How the values of the water depth are being, and if the values are similar, whether the observed value of tide using GPS is valid or not.

• Smart Structures and Systems
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• v.7 no.3
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• Journal of Welding and Joining
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• v.32 no.1
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• pp.53-60
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• 2014

The automatic arc welding is generally accepted as the preferred joining technique and commonly chosen for assembly of large metal structures such as in areas of automotive, aircraft and shipbuilding due to its joint strength, reliability, and low cost compared to other joint processes. Recently, several mathematical models have been developed and studied for control and monitoring welding quality, productivity, microstructure and weld properties in arc welding processes. This study indicates the prediction of process parameters for the expected welding quality with accordance to the adaptive GTA welding process. Furthermore, the mathematical models is also develop to aid the selection of an optimal welding process as the generation of process controls to predict the bead geometry as a function output parameters in the GTA welding process. The developed models through this study showed comparatively excellent predicted results, and will extend to other welding processes to integrate an optimized system for the robotic welding process.

• Journal of Yeungnam Medical Science
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• v.38 no.1
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• pp.19-26
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• 2021

Adhesive capsulitis of the shoulder joint is a common disease characterized by pain at the insertional area of the deltoid muscle and decreased range of motion. The pathophysiological process involves fibrous inflammation of the capsule and intraarticular adhesion of synovial folds leading to capsular thickening and contracture. Regarding the multidirectional limitation of motion, a limitation in external rotation is especially prominent, which is related to not only global fibrosis but also to a localized tightness of the anterior capsule. Ultrasound and magnetic resonance imaging studies can be applied to rule out other structural lesions in the diagnosis of adhesive capsulitis. Hydraulic distension of the shoulder joint capsule provides pain relief and an immediate improvement in range of motion by directly expanding the capsule along with the infusion of steroids. However, the optimal technique for hydraulic distension is still a matter of controversy, with regards to the infusion volume and rupture of the capsule. By monitoring the real-time pressure-volume profile during hydraulic distension, the largest possible fluid volume can be infused without rupturing the capsule. The improvement in clinical outcomes is shown to be greater in capsule-preserved hydraulic distension than in capsule-ruptured distension. Moreover, repeated distension is possible, which provides additional clinical improvement. Capsule-preserved hydraulic distension with maximal volume is suggested to be an efficacious treatment option for persistent adhesive capsulitis.

• Archives of Plastic Surgery
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• v.49 no.6
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• pp.782-784
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• 2022

Diabetic foot ulcers are a severe complication of diabetes, and their management requires a multidisciplinary approach for optimal management. When treating these ulcers, limb salvage remains the ultimate goal. In this article, we present the "hanging" free flap for the reconstruction of chronic lower extremity diabetic ulcers. This two-staged approach involves standard free flap harvest and inset; however, following inset the "hanging" pedicle is covered within a skin graft instead of making extraneous incisions within the undisturbed soft tissues or tunnels that can compress the vessels. After incorporation, a second-stage surgery is performed in 4 to 6 weeks which entails pedicle division, flap inset revision, and end-to-end reconstruction of the recipient vessel. Besides decreasing the number of incisions on diabetic patients, our novel technique utilizing the "hanging" pedicle simplifies flap monitoring and inset and allows reconstruction of recipient vessels to reestablish distal blood flow.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1276-1295
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• 2023

Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• Journal of Advanced Navigation Technology
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• v.24 no.5
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• pp.382-392
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• 2020

The use of unmanned aerial vehicle (UAV) have been regarded as a promising technique in both military and civilian applications. Nevertheless, due to the lack of relevant and regulations and laws, the misuse of illegal drones poses a serious threat to social security. In this paper, aiming at deriving the three-dimension optimal surveillance trajectories for group monitoring drones, we develop a group trajectory planner based on the particle swarm optimization and updating mechanism. Together, to evaluate the trajectories generated by proposed trajectory planner, we propose a group-objectives fitness function in accordance with energy consumption, flight risk. The simulation results validate that the group trajectories generated by proposed trajectory planner can preferentially visit important areas while obtaining low energy consumption and minimum flying risk value in various practical situations.