• 디지털산업정보학회논문지
• /
• 제12권4호
• /
• pp.33-40
• /
• 2016

Previous works for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods require accurate detection of ECG signal, higher computational cost and larger processing time. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system based IOT that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose R wave detection considering complexity and arrhythmia classification based on binary coding. For this purpose, we detected R wave through SOM and then RR interval from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. R wave detection and PVC, PAC, Normal classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41%, 97.18%, 94.14%, 99.83% in R wave, PVC, PAC, Normal.

• Applied Microscopy
• /
• 제9권1호
• /
• pp.35-56
• /
• 1979

To investigate ultrastructural characteristics of cancer cells of the nervous system, 25 cases; i.e. astrocytoma(9), oligodendroglioma(1), medulloblastoma(1), meningioma(5), pinealoma(2) and pituitary adenomas(7). The common findings were marked irregularity of nuclear membrane with pronounced infoldings, clumping of heterochromatin along inner nuclear membrane, enlargement of nucleolus, and frequent observations of nuclear bodies and nuclear inclusions. But these findings are also the signs that can be observed in hyperactive cells. Thus, ultrastructural characteristics of cancerous nucleus are the great variability of nuclear size, shape and composition. but none of them appear to be specific. Among cytoplasmic organelles, massive fibrils are characteristic of astrocytoma and meningiomas, cytoplasmic protofibrils such as glial process and microvesicles in oligodendroglioma, secretory granules are characteristic in pituitary adenomas, and fine filamentous fibrils and desmosomes are characteristic of fibroblastic type of meningioma. Intercellular relationships and cell membrane specialization are important features in the differential diagnosis of various undifferentiated tumors. The frequent resolution of difficult diagnosis problems by electron microscopy outweighs the disadvantages of this technique, such as the expense and time required.

• 품질경영학회지
• /
• 제46권1호
• /
• pp.39-74
• /
• 2018

Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.

• 대한원격탐사학회지
• /
• 제27권3호
• /
• pp.369-377
• /
• 2011

Since well-calibrated satellite data is critical for their applications, calibration and validation of COMS science data was one of the key activities during the IOT. COMS MI radiometric calibration process was divided into two phases according to the out-gassing of the sensor: calibrations of the visible (VI) and infrared (IR) channels. Different from the VIS calibration, the calibration steps for the IR channels followed additional processes to secure their radiometric performances. Primary calibration steps of the IR were scan mirror emissivity correction, midnight effect compensation, slope averaging and 1/f noise compensation after a nominal calibration. First, the scan mirror emissivity correction was conducted to compensate the variability of the scan mirror emissivity driven by the coating material on the scan mirror. Second, the midnight effect correction was performed to remove unreasonable high spikes of the slope values caused by the excessive radiative sources during the local midnight. After these steps, the residual (difference between the previous slope and the given slope) was filtered by a smoothing routine to eliminate the remnant random noises. The 1/f noise compensation was also carried out to filter out the lower frequency noises caused from the electronics in the Imager. With through calibration processes during the entire IOT period, the calibrated IR data showed excellent performances.

• 분석과학
• /
• 제8권4호
• /
• pp.1079-1087
• /
• 1995

The quality of human life is directly related to the quality of the environment. To assess environmental quality we must first determine the MCLG(Maximum Contaminant Level Goal), MCL(Maximum Contaminant Level), environmental impact and so on. The MCLG is the concentration at which no known adverse health effects occur. The MCLG is determined by risk assessment identifying which process is hazardous assessing, dose-response, human exposure, and characteristics of risk. With consideration of analytical methods, treatment technology, cost and regulatory impact, the MCL is set as close to the MCLG as possible. In this way, determination of the concentration and national distribution of contaminants is important for assessment of environmental quality The analytical sciences pose potential problems in assessing environmental quality. Continuing improvement in the performance of analytical instruments and operating technique has been lowering the limits of detectability. Contaminant concentration below the detection limit has usually been reported as ND(Not-Detected) and this has often been misunderstood as equivalent to zero. Because of this, more the contaminant concentration in the past was below the detection limit, whereas contaminants can be quantified now even though the contaminant concentration might remain the same or may even have decreased. In addition, environmental sampling has various components due to heterogeneous matrices. These samples are used to overestimate the concentration of the contaminant due to large variability, resulting in excess readings for MCL. In this paper, the significance of the analytical sciences is emphasized in both a conceptual and a technical approach to environmental assessment.

• 보건행정학회지
• /
• 제26권4호
• /
• pp.352-358
• /
• 2016

Summary measures of population health (SMPHs) have been used to estimate the burden of diseases. Among various type of SMPHs, disability adjusted life year (DALY) and healthy life expectancy (HALE) have been calculated in the global and national burden of disease studies. In order to calculate DALY and HALE, disability weight is an essential element. Disability weights quantify the level of disability for health states or diseases and have values between 0 (full health) to 1 (being dead). In this study, we reviewed the main disability weights studies and determined their meaning and limitations. Furthermore, we provided the whole process of typical disability weight study and reviewed key issues as follows: health state or disease description development, panel composition, valuation method, validation of disability weight, cross-cultural variability in health state or disease, and so on. The results from this study will be helpful to conduct future disability weight studies for adapting disability weights and developing new methodologies.

• 한국자동차공학회논문집
• /
• 제8권5호
• /
• pp.96-104
• /
• 2000

It is well known that combustion stability under idle and part-load conditions directly affect fuel economy and exhaust emission. In practice, there have been a lot of studies so that a significant improvement in combustion stability has been achieved in this research field. However, applying published results to the development process of mass production engine, there are still many problems which are solved previously. In this study, initial flame behavior and flame propagation characteristic were investigated statistically in order to optimize combustion chamber shapes in the development stage of mass production S.I. engine. To the purpose, the authors applied the flame image capturing system to single cylinder optical engine. The captured flame images were effectively analyzed by using the image processing program which was developed by the authors and adopted new threshold algorithm instead of conventional histogram analysis. In addition, the cylinder pressure was also measured simultaneously to compare evaluated flame results with cylinder pressure data in terms of the combustion characteristics, combustion stability, and cycle-to-cycle combustion variability.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2009년도 춘계 학술발표회
• /
• pp.456-463
• /
• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by in-situ test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network(NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network(CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• International Journal of Reliability and Applications
• /
• 제8권1호
• /
• pp.111-124
• /
• 2007

In this paper, we apply insightful statistical reliability tools to manage and seek improvements in the strengths of Oriented Strand Board (OSB). As a part of the OSB manufacturing process, the product undergoes destructive testing at various intervals to determine compliance with customers' specifications. Workers perform these tests on sampled cross sections of the OSB panel to measure the tensile strength, also called internal bond (IB), in pounds per square inches until failure. Additional stiffness strength tests include parallel and perpendicular elasticity indices (EI), which are taken from cross sectional samples of the OSB panel in the parallel and perpendicular directions with respect to the orientation of the wood strands. We explore both graphically and statistically these "pressure-to-failures" of OSB. Also, we briefly comment on reducing sources of variability in the IB and EI of OSB.

• Smart Structures and Systems
• /
• 제5권3호
• /
• pp.223-240
• /
• 2009

As in any engineering application, the problem of structural assessment should face the different uncertainties present in real world. The main source of uncertainty in Health Monitoring System (HMS) applications are those related to the sensor accuracy, the theoretical models and the variability in structural parameters and applied loads. In present work, two methodologies have been developed to deal with these uncertainties in order to adopt reliable decisions related to the presence of damage. A simple example, a steel beam analysis, is considered in order to establish a liable comparison between them. Also, such methodologies are used with a developed structural assessment algorithm that consists in a direct and consistent comparison between sensor data and numerical model results, both affected by uncertainty. Such algorithm is applied to a simple concrete laboratory beam, tested till rupture, to show it feasibility and operational process. From these applications several conclusions are derived with a high value, regarding the final objective of the work, which is the implementation of this algorithm within a HMS, developed and applied into a prototype structure.