Mingon Kang

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In this paper, we present causes of variation in performance for passive UHF RFID tags with empirical results in two different environments: practical conditions and an anechoic chamber. We study the critical causes of RSSI ambiguity, such as a posture of tag, and variations among uniform tags. Moreover, in passive UHF RFID systems, Tag-to-Tag interferences(More)
One of the major obstacles in computational modeling of a biological system is to determine a large number of parameters in the mathematical equations representing biological properties of the system. To tackle this problem, we have developed a global optimization method, called Discrete Selection Levenberg-Marquardt (DSLM), for parameter estimation. For(More)
While genome-wide association studies (GWAS) have focused on discovering genetic loci mapped to a disease, expression quantitative trait loci (eQTL) studies combine micro array data and provide a powerful approach. Micro arrays allow one to measure thousands of gene expressions simultaneously and the advances in eQTL studies enable one to capture the(More)
Developing vigorous mathematical models and estimating accurate parameters within feasible computational time are two indispensable parts to build reliable system models for representing biological properties of the system and for producing reliable simulation. For a complex biological system with limited observations, one of the daunting tasks is the large(More)
Detecting arrhythmia from ECG data is now feasible on mobile devices, but in this environment it is necessary to trade computational efficiency against accuracy. We propose an adaptive strategy for feature extraction that only considers normalized beat morphology features when running in a resource-constrained environment; but in a high-performance(More)
Computational modeling and simulation play an important role in analyzing the behavior of complex biological systems in response to the implantation of biomedical devices. Quantitative computational modeling discloses the nature of foreign body responses. Such understanding will shed insight on the cause of foreign body responses, which will lead to(More)
In this paper, we propose a novel model for the appropriate recommendation of antiarrhythmic drugs by introducing a fusion of a latent semantic analysis and k-means clustering. Our model not only captures the latent factors between the types of arrhythmia and patients but also has the ability to search a group of patients with similar arrhythmias. The(More)