• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.1
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• pp.13-23
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• 2015

Recently, a few image-processing based mobile urine testers have actively been studied since the urine-analysis result can be available to the user in real time immediately after the test is done. However, the accuracy of test result can be severely degraded due to variable illumination environments and a variety of manners to capture the image with a camera embedded in the smartphone according to different users. This paper proposes the Check4Urine system, a novel smartphone-based portable urine-analysis tester and provides three techniques to improve such a performance degradation problem robust to various test environments and disturbances, which are the compensation algorithm to correct the varying illumination effect, an urine strip detection algorithm robust to edge loss of the object image, and the color decision algorithm based on the pre-processed reference table. Experimental results show that the proposed Check4Urine system increases the accuracy of urine-analysis by 20-50% at various test conditions, compared with the existing image-processing based mobile urine tester.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.1 no.2
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• pp.214-220
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• 1991

As chromium in urine remains as oxychromic acid ions, chromium was extracted by using ion pair formed by anion exchanger trioctylamine. then after it is noted whether this TOA-MIBK method is effective or not for the chromium analysis by using flame method of Atomic absorption Spectrophotometric Analysis. The result is as following. 1. Effects of various acids on the extraction of Cr with MIBK including TOA are good in order $NHO_3$, $H_2SO_4$, HCl in distilled water sample and its proper concentration of HCl is 0.2 N. 2. For the analysis of urine sample, the best result can be achieved by following condition. After finished pretreatment adjusted to pH 6.5-7.5 by NaOH and again controlled pH 0.5-0.6 by HCl. 3. Though TOA concentration slightly affects the analytic value, best result is noted in 1-3% concentration. 4. Recovery rates of urine samples made by $0.3mg/l{\cdot}urine$, $0.6mg/l{\cdot}urine$, $0.9mg/l{\cdot}urine$ are shown from 96.7% to 104.8%. 5. Recovery rates of urine samples made by $0.01mg/l{\cdot}urine$, $10.03mg/{\cdot}urine$, $0.05mg/l{\cdot}urine$ are shown from 89.3% to 98.6%.

• Journal of Biomedical Engineering Research
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• v.9 no.2
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• pp.149-152
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• 1988

From the analysis of proton NMR signals of human urine it is found that the signals corresponding to a phenolic compound of tyrosine are more frequently observed in cancer urine than in non-cancer urine. An effective reagent is obtained to detect the substance excreted in the urine and to find out a close connection with the result of the NMR analysis. An attempt is made to determine the reagent sensitivity and specificity for cancer diagnosis. The results of the attempt are respectively above 75% for both on an average.

• Archives of Pharmacal Research
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• v.11 no.2
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• pp.134-138
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• 1988

Urine measurements by MNR were made for 25 persons including cancer and non-cancer patients. The aromatic proton signals of NMR wer observed much more often in cancer patients' urine than non-cancer patients' one. To compare the amount of the phenolic compounds excreted in urine between cancer and non-cancer patient, urine analysis by HPLC with UV detector was performed. Total peak area and major peak areas of cancer patients' urine wer emuch greater than those of non-cancer patients' one. To check the phenolic compound excreted in urine, a new jellied reagent named Gift reagent which was based on Millon's reagent, was developed for urine color reaction. When the reagent was tested, the sensitivity and specificity for urine samples of 69 persons including cancer and non-cancer patients were measured by 85.3% and 91.4%, respectively, indicating that the Gift reagent afford a possibility of cancer diagnosis.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1059-1065
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• 2020

In hospitals, nurses are subjectively determining the urine status to check the kidneys and circulatory system of patients whose statuses are related to patients with kidney disease, critically ill patients, and nursing homes before and after surgery. To improve this problem, this paper proposes a urine spectrum analysis system which clusters urine test results based on a hybrid machine learning model consists of unsupervised learning and supervised learning. The proposed system clusters the spectral data using unsupervised learning in the first part, and classifies them using supervised learning in the second part. The results of the proposed urine spectrum analysis system using a mixed model are evaluated with the results of pure supervised learning. This paper is expected to provide better services than existing medical services to patients by solving the shortage of nurses, shortening of examination time, and subjective evaluation in hospitals.

• Animal Bioscience
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• v.36 no.3
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• pp.492-497
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• 2023

Objective: The objectives were to demonstrate that the nitrogen and energy in pig urine supplemented with hydrochloric acid (HCl) are not volatilized and to determine the minimum amount of HCl required for nitrogen preservation from pig urine. Methods: In Exp. 1, urine samples of 3.0 L each with 5 different nitrogen concentrations were divided into 2 groups: 1.5 L of urine added with i) 100 mL of distilled water or ii) 100 mL of 6 N HCl. The urine in open plastic containers was placed on a laboratory table at room temperature for 10 d. The weight, nitrogen concentration, and gross energy concentration of the urine samples were determined every 2 d. In Exp. 2, three urine samples with different nitrogen concentrations were added with different amounts of 6 N HCl to obtain varying pH values. All urine samples were placed on a laboratory table for 5 d followed by nitrogen analysis. Results: Nitrogen amounts in urine supplemented with distilled water decreased linearly with time, whereas those supplemented with 6 N HCl remained constant. Based on the linear broken-line analysis, nitrogen was not volatilized at a pH below 5.12 (standard error = 0.71 and p<0.01). In Exp. 3, an equation for determining the amount of 6 N HCl to preserve nitrogen in pig urine was developed: additional 6 N HCl (mL) to 100 mL of urine = 3.83×nitrogen in urine (g/100 mL)+0.71 with R² = 0.96 and p<0.01. If 62.7 g/d of nitrogen is excreted, at least 240 mL of 6 N HCl should be added to the urine collection container. Conclusion: Nitrogen in pig urine is not volatilized at a pH below 5.12 at room temperature and the amount of 6 N HCl required for nitrogen preservation may be up to 240 mL per day for a 110-kg pig depending on urinary nitrogen excretion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1394-1397
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• 2020

The urine test used as a basic test method of in vitro diagnosis for health care has been used for a long time to be simple and convenient. The urine test method is using a color that appears depending on the change in the ion concentration that reacts over time buried in the standard color test paper(Strips) with a urine sample applied to some reaction reagents. In this paper, it was proposed a neural network algorithm to obtain a suitable and reproducibility and accuracy classifier suitable for the urine analysis system. The experimental results were compared with the visual colorimetric analysis, and the neural network algorithm showed better results.

• Journal of Biomedical Engineering Research
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• v.19 no.5
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• pp.477-486
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• 1998

In this paper, we implemented the urine analysis system capable of measuring a qualitative and semi-quantitative and assay using strip. The analysis algorithm of urine analysis was adopted a fuzzy logic-based classifiers that was robust to external error factors such as temperature and electric power noises. The spectroscopic properties of 9 pads In a strip were studied to developing the urine analysis system was designed for robustnesss and stability. The urine analysis system was consisted of hardware and software. The hardware of the urine analysis system was based on one-chip microprocessor, and Its peripherals which composed of optic modulo, tray control, preamplifier, communication with PC, thermal printer and operating status indicator. The software of the urine analysis system was composed of system program and classification program. The system program did duty fort system control, data acquisition and data analysis. The classification program was composed of fuzzy inference engine and membership function generator. The membership function generator made triangular membership functions by statical method for quality control. Resulted data was transferred through serial cable to PC. The transferred data was arranged and saved be data acquisition program coded by C+ + language. The precision of urine analysis system and the stability of fuzzy classifier were evaluated by testing the standard urine samples. Experimental results showed a good stability states and a exact classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1319-1325
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• 2006

Urine analysis is basic test in clinical medicine using visual examination by expert nurse. Recently, this test is measured by automatic urine analysis system. But, this system has different results by each instrument. So, a new classification algorithm is required for accurate classify and urine color collection. In this paper, a intelligent color classifier of urine analysis system was designed using neural network algorithm. The input parameters are three stimulus(RGB) after preprocessing using normalization. The fuzzy inference and neural network ware constructed for classify class according to 9 urine test items and $3{\sim}7$ classes. The experiment material to be used a standard sample of medicine. The possibility to adapt classifier designed for urine analysis system was verified as classifying measured standard samples and observing classified result. Of many test items, experimental results showed a satisfactory agreement with test results of reference system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.320-323
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• 2001

A computer simulation was performed to distinguish quantitatively a color reaction in a urine analysis systems by using the spectral power distribution of LEDs, the spectral reflectance of a urine strip, and the spectral sensitivity of photodiode. The CIE tristimulus values and CIE chromaticity coordinates ware modified to be conformable with real color reactions in a urine strips. Results on color simulation showed a of real color in comparison with those obtained by Colorimeter CM2C(Color Savvy).