• Advances in aircraft and spacecraft science
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• v.5 no.2
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• pp.225-237
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• 2018

The difficulties of satellite vibration testing are due to the commonly expressed qualification requirements being incompatible with the limited performance of the entire controlled system (satellite + interface + shaker + controller). Two features cause the problem: firstly, the main satellite modes (i.e., the first structural mode and the high and low tank modes) are very weakly damped; secondly, the controller is just too basic to achieve the expected performance in such cases. The combination of these two issues results in oscillations around the notching levels and high amplitude beating immediately after the mode. The beating overshoots are a major risk source because they can result in the test being aborted if the qualification upper limit is exceeded. Although the abort is, in itself, a safety measure protecting the tested satellite, it increases the risk of structural fatigue, firstly because the abort threshold has been already reached, and secondly, because the test must restart at the same close-resonance frequency and remain there until the qualification level is reached and the sweep frequency can continue. The beat minimum relates only to small successive frequency ranges in which the qualification level is not reached. Although they are less problematic because they do not cause an inadvertent test shutdown, such situations inevitably result in waiver requests from the client. A controlled-system analysis indicates an operating principle that cannot provide sufficient stability: the drive calculation (which controls the process) simply multiplies the frequency reference (usually called cola) and a function of the following setpoint, the ratio between the amplitude already reached and the previous setpoint, and the compression factor. This function value changes at each cola interval, but it never takes into account the sensor signal phase. Because of these limitations, we firstly examined whether it was possible to empirically determine, using a series of tests with a very simple dummy, a controller setting process that significantly improves the results. As the attempt failed, we have performed simulations seeking an optimum adjustment by finding the Least Mean Square of the difference between the reference and response signal. The simulations showed a significant improvement during the notch beat and a small reduction in the beat amplitude. However, the small improvement in this process was not useful because it highlighted the need to change the reference at each cola interval, sometimes with instructions almost twice the qualification level. Another uncertainty regarding the consequences of such an approach involves the impact of differences between the estimated model (used in the simulation) and the actual system. As limitations in the current controller were identified in different approaches, we considered the feasibility of a new controller that takes into account an estimated single-input multi-output (SIMO) model. Its parameters were estimated from a very low-level throughput. Against this backdrop, we analyzed the feasibility of an LQG control in cancelling beating, and this article highlights the relevance of such an approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.3 no.1
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• pp.18-25
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• 1978

The 1/f noise spectrum of short-circuited output drain current due to the Shockley-Read-Hal] recombination centers with a single lifetime in homogeneous nondegenerate MOS-field effcte transtors with n-type channel is calculated under the assumptions that the quasi-Fermi level for the carriers in each energy band can not be defined if we include the fluctuation for time varying quantities. and so 1/f noise is a majority carrier effect. Under these assumptions the derived 1/f noise in this paper show some essential features of the 1/f noise in MOS-field effect transistors. That is, it has no lowfrequency plateau and is proportionnal to the channel cross area A and to the driain bias voltage Vd and inversely proportional to the channel length L3 in MOS field effect transistors. This model can explain the discrepancy between the transition frequency of the noise spectrum from 1/f- response to 1/f2 and the frequency corresponding to the relaxation time related to the surface centers in p-n junction diodes. In this paper the results show that the functional form of noise spectrum is greatly influenced by the functional forms of the electron capture probability cn (E) and the relaxation time r (E) for scattering and the case of lattice scattering show to be responsible for the 4 noise in MOS fold effect transistors. So we canconclude that the source of 1/f noise is due to lattice scattering.

• Journal of the Korean Society of Radiology
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• v.6 no.6
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• pp.447-454
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• 2012

To examine the performance of a diagnostic X-ray system, we tested a linearity, reproducibility, and Half Value Layer(HVL). The linearity was examined 4 times of irradiation with a given condition, and we recorded a level of radiation. We then calculated the mR/mAs. And the measured value should not be more than 0.1. If the measured value was more than 0.1, we could know that the linearity was decreased. The reproducibility was analyzed 10 times of irradiations at 80kVp, 200mA, 20mAs and 120kVp, 300mA, 8mAs. The values from these analyses were integrated into CV equation, and we could get outputs. The reproducibility was good if the output was lower than 0.05. HVL was measured 3 times of irradiation without a filter, and we inserted additional HLV filters with 0, 1, 2, 4 mm of thickness. We tested the values until we get the measured value less than a half of the value measured without additional filter. We tested the linearity, the reproducibility, and HVL of 5 diagnostic X-ray generators in this facilities. The linearity of No. 1 and No. 5 generator didn't satisfy the standard for radiation safety around 300mA~400mA and 100mA~200mA, respectively. HVL of No.1 generator was not satisfied at 80kVp. The outputs were higher in the three-phase equipment than the single-phase equipment. The old generators need to maintain and exchange of components based on the these results. Then, we could contribute to getting more exact diagnosis increasing a quality of the image and decreasing an expose dose of radiation.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.