• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.2 s.332
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• pp.23-30
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• 2005

This paper describes a DLL(delay locked loop)-based multi-clock generator having the lower active stand-by power as well as a fast relocking after re-activating the DLL. for low power and high speed VLSI chip. It enables a frequency multiplication using frequency multiplier scheme and produces output clocks with 50:50 duty-ratio regardless of the duty-ratio of system clock. Also, digital control scheme using DAC enables a fast relocking operation after exiting a standby-mode of the clock system which was obtained by storing analog locking information as digital codes in a register block. Also, for a clock multiplication, it has a feed-forward duty correction scheme using multiphase and phase mixing corrects a duty-error of system clock without requiring additional time. In this paper, the proposed DLL-based multi-clock generator can provides a synchronous clock to an external clock for I/O data communications and multiple clocks of slow and high speed operations for various IPs. The proposed DLL-based multi-clock generator was designed by the area of $1796{\mu}m\times654{\mu}m$ using $0.35-{\mu}m$ CMOS process and has $75MHz\~550MHz$ lock-range and maximum multiplication frequency of 800 MHz below 20psec static skew at 2.3v supply voltage.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.361-366
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• 2012

This paper presents speed control of an electric motorcycle using a fuzzy controller. The electric motorcycle required to meet not only fast throttle response but also stability, when it is on a cruise. However, a 1.5KW (50cc) electric motorcycles selling in the current market are difficult to cruise under the following conditions which are occupant's weight, load weight, wind resistance and road conditions (dirt roads, asphalt road). Because of these reasons, the rapid speed changing occurs in uphill and downhill road. To solve these problems, The input value for Improved fuzzy controller use the speed error and error variance. The output value for improved fuzzy controller uses Q-axis of the motor controlled variable. The D-axis of the motor output for improved fuzzy control uses D-axis controlled variable in proportional to Q-axis controlled variable. Improved fuzzy controller drives the electric motorcycle equipped with IPMSM. The control subject used in this paper is a 1.5KW electric motorcycle equipped with improved fuzzy controller that was used to control the motor speed. To control IPMSM Type of motor torque, D, Q-axis current controller was used. The Fuzzy controller using the proposed algorithm is demonstrated by experimental hardware simulator.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.284-287
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• 2000

Recently, developing medical devices have a tendency becoming the module for satisfying user's mutual complex needs. Because the most effective method for the observation of patients condition a diagnosis and a treatment is collecting data from various devices and controling operation following it. Module tendency is more popular due to manage easily totally many individual systems. This study implemented communication protocol to control by one control system connecting modular medical devices. Implemented system consist of one master module controlling all module and managing communication and many Slave modules. Communication between each modules introduced SPI(Serial Peripheral Interface) among many synchronous serial communication methods for the exact transmission and receipt of data. All communication executes by packet format. This can detect error. And, this protocol introduced PNP(Plug And Play) function that auto-detect connecting or removing module during running. This protocol exactly transmitted and received in faster speed more than 1Mbps. And in practical application to the ventilator this confirmed to give and take real-time data. And various functions by th central control system is implemented in this protocol.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.