• Journal of Platform Technology
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• v.10 no.4
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• pp.11-24
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• 2022

The tool for developing airborne software requires the same level of safety as airborne software because the tool whose output is part of the airborne software and thus could insert an error into the airborne software. This paper describes how to ensure the reliability of the tool output that becomes a part of the airborne software by validating of the input and output files of the tool when generating the ARINC 661 standard UA definition file and the CDS configuration file through the A661UAGEN tool of Hanwha Systems. We present the method to validate XML data structure and contents with an XML schema definition, which is an input of the A661UAGEN tool. And the method to validate the output binary data by using mask data for the corresponding data structure and valid value, which is the output of the A661UAGEN tool, was presented. As such, validation of the input and output of the tool improves the reliability of binary DFs and CDs integrated into the airborne software, allowing airborne software developers to utilize the tool to ensure safety in developing the OFP.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.319-325
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• 2001

In this note, we propose a simple fuzzy linear regression model for fuzzy input-output data based on Tanaka's approach. Then an LP-based method to derived the satisfying solution of the decision making is developed.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.341-346
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• 2017

In this paper, we present a 60 GHz on-off keying (OOK) modulator in a 90 nm CMOS. The modulator employs a current-reuse technique and a switching modulation for low DC power dissipation, high on/off isolation, and high data rate. The measured gain of the modulator, on/off isolation, and output 1-dB compression point is 9.1 dB, 24.3 dB, and 5.1 dBm, respectively, at 60 GHz. The modulator consumes power consumption of 18 mW, and is capable of handling data rates of 8 Gb/s at bit error rate of less than $10^{-6}$ for $231^{-1}$ PRBS over a distance of 10-cm with an OOK receiver module.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.3
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• pp.121-126
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• 2014

Demand of the data storage becomes more and more growing. This requests the next generation of storage devices to have the dominated storage capability associated with superfast read/write rate. Holographic data storage (HDS) is investigated for a long time and is considered to be a candidate for the future storage system. However, it has two-dimensional intersymbol interference that conventional one-dimensional detection solutions have not yet handled strictly because of the complexity level of system as well as the cost. We propose a new scheme that combines iterative soft output Viterbi algorithm with noise filter for improving the bit error rate performance of HDS.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.419-427
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• 2023

In this study, optimal adhesion conditions to alleviate defects caused by heat shrinkage with FDM type 3D printers with machine learning are researched. Machine learning is one of the "statistical methods of extracting the law from data" and can be classified as supervised learning, unsupervised learning and reinforcement learning. Among them, a function model for adhesion between the bed and the output is presented using supervised learning specialized for optimization, which can be expected to reduce output defects with FDM type 3D printers by deriving conditions for optimum adhesion between the bed and the output. Machine learning codes prepared using Python generate a function model that predicts the effect of operating variables on adhesion using data obtained through adhesion testing. The adhesion prediction data and verification data have been shown to be very consistent, and the potential of this method is explained by conclusions.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.133-141
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• 1994

Conventional competitive learning algorithms compute the Euclidien distance to determine the winner neuron out of all predetermined output neurons. In such cases, there is a drawback that the performence of the learning algorithm depends on the initial reference(=weight) vectors. In this paper, we propose a new competitive learning algorithm that dynamically generates output neurons. The proposed method generates output neurons by dynamically changing the class thresholds for all output neurons. We compute the similarity between the input vector and the reference vector of each output neuron generated. If the two are similar, the reference vector is adjusted to make it still more like the input vector. Otherwise, the input vector is designated as the reference vector of a new outputneuron. Since the reference vectors of output neurons are dynamically assigned according to input pattern distribution, the proposed method gets around the phenomenon that learning is early determined due to redundant output neurons. Experiments using speech data have shown the proposed method to be superior to existint methods.

• Journal of Korea Technology Innovation Society
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• v.7 no.2
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• pp.283-304
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• 2004

Evaluating the sources of economic output is obviously important, and numerous attempts have been made to judge the impact of many different factors on economic output. It is widely accepted that high-technology(HT) is one of the important factors in economic output. This paper empirically explores the impacts of HT exports on economic output using a cross-county analysis based on data from 89 countries for the year 1988-2000. To this end, several versions of the neoclassical growth models, explicitly including HT exports, are estimated. Subject to the appropriate caveats, the results provide further support for several key conclusions of the former studies - investment in physical capital, population growth, and the human capital are important in accounting fer economic output across countries. More importantly, it is concluded that HT exports significantly contribute to economic output. Interestingly, the conclusion is valid f3r developing countries, but not far developed countries.

• Advances in Energy Research
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• v.5 no.4
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• pp.321-339
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• 2017

Energy simulation tools can provide information on the amount of heat transfer through building envelope components, which are considered the main sources of heat loss in buildings. Therefore, it is important to improve the quality of outputs from energy simulation tools and also the process of obtaining them. In this paper, a new Building Energy Performance Assessment Tool (BEPAT) is introduced, which provides users with granular data related to heat transfer through every single wall, window, door, roof, and floor in a building and automatically saves all the related data in text files. This information can be used to identify the envelope components for thermal improvement through energy retrofit or during the design phase. The generated data can also be adopted in the design of energy smart homes, building design tools, and energy retrofit tools as a supplementary dataset. BEPAT is developed by modifying EnergyPlus source code as the energy simulation engine using C++, which only requires Input Data File (IDF) and weather file to perform the energy simulation and automatically provide detailed output. To validate the BEPAT results, a computer model is developed in Revit for use in BEPAT. Validating BEPAT's output with EnergyPlus "advanced output" shows a difference of less than 2% and thus establishing the capability of this tool to facilitate the provision of detailed output on the quantity of heat transfer through walls, fenestrations, roofs, and floors.

• Asian Journal of Business Environment
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• v.9 no.3
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• pp.5-9
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• 2019

Purpose - This paper examines whether fiscal and monetary expansion would affect output in Australia. Research design, data, and methodology - An extended IS-LM model which describes the equilibrium in the goods market and the money market is applied. The real effective exchange rate and the real stock price are included in order to determine whether there may be any substitution or wealth effect. The sample consists of Annual data ranging from 1990 to 2018. The GARCH process is used in empirical work to correct for potential autoregressive conditional heteroscedasticity. Results - Expansionary fiscal policy reduces output; whereas, expansionary monetary policy raises output. In addition, real appreciation of the Australian dollar, a lower U.S. interest rate, a higher real stock price or a lower expected inflation would increase output. The finding that expansionary fiscal policy has a negative impact on real GDP suggests that the negative crowding-out effect on private spending dominates the positive impact. Conclusions - Fiscal prudence needs to be pursued. Real depreciation of the Australian dollar hurts output. Monetary tightening in the U.S. generates a negative effect on Australia's output. A healthy stock market is conducive to economic growth as higher stock prices tend to result in the wealth and other positive effects, increasing consumption and business spending.

• Journal of the Korean Society of Safety
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• v.39 no.2
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• pp.65-74
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• 2024

We analyzed the relationship between the normal measurement of the seismic accelerometer (SA) and the error rate of the output voltage linear ratio to propose an evaluation method to determine whether the SA in use is measuring normally. Utilizing a test bed, the regular operation of SA in use was evaluated using acceleration data measured through impact tests since there are no regulations regarding performance testing of SA in use. For the used SA, the error rate of the output voltage linear ratio, which is a major performance criterion, was evaluated. We analyzed common characteristics of the SA that satisfied the impact test and the performance criteria of the output voltage linear ratio error rate. The results indicated that we must consider the decreasing trend and convergence of the error rate as the measurement angle increases, ensuring that the average value of the output voltage linear ratio error rate is within 1%.