• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.1
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• pp.7-14
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• 2002

In this paper, neutral networks are used to build models of oxide film etched In CHF$_3$/CF$_4$ with a magnetically enhanced reactive ion etcher(MERIE). A statistical 2$\^$4-1/ experimental design plus one center point was used to characterize relationships between process factors and etch responses. The factors that were varied include radio frequence(rf) power, pressure, CHF$_3$ and CF$_4$ flow rates. Resultant 9 experiments were used to train neural networks and trained networks were subsequently tested on its appropriateness using additionally conducted 8 experiments. A total of 17 experiments were thus conducted for this modeling. The etch responses modeled are dc bias voltage, etch rate and etch uniformity A qualitative, good agreement was obtained between predicted and observed behaviors.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.43-50
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• 2022

The students' feedback is important to measure and improve teaching performance. Many teacher performance evaluation systems are based on responses to closed question, but the free text answers can contain useful information which had to be explored. In this paper we present a lexicon-based sentiment analysis to explore students' text feedback. The data was collected from a system for the evaluation of teachers by students developed and used in our university. The students comments are in Romanian language so we built a Romanian sentiment word lexicon. We used this to categorize the feeback text as positive, negative or neutral. In addition, we added a new polarity - indifferent - in order to categorize blank and "I don't answer" responses.

• Journal of Korean Port Research
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• v.6 no.2
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• pp.3-24
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• 1992

In the fuzzy control of shop the qualitative knowledge and information that the ship's operators have acquired through their experience can be logically described by the Linguistic control Rule (LCR). The algorithm of the control is made of the LCR and the control of the shop is performed by processing this algorithm implementing a computer. The problem in the fuzzy control is that it is very difficult to describe qualitative human knowledge in the LCR correctly. To tackle this difficulty a Fuzzy Neural Network (FNN) was introduced in this paper. The characteristics of the multi-layer FNN control system applied to the ship's steering system is investigated through the computer simulation, and the results were compared with those of the ordinary fuzzy control system of a ship. The results showed that the FNN method is a very effective to translate human knowledge into the LCR.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.9
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• pp.1-7
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• 2014

Brushless Direct Current(BLDC) Motor is essential to measure a rotor position because of that this motor type needs to synchronize the rotor's position and changeover phase current instead of a brush and commutator used on the existing dc motor. Recently, many researches have studied on sensorless control drive for BLDC motor. The conventional control methods are a compensation value dq, Kalman filter, Fuzzy logic, Neurons neural network, and the like. These methods has difficulties of detecting BEMF accurately at low speed because of low BEMF voltage and switching noise. And also, the operation is long and complex. So, it is required a high-performance microprocessor. Therefore, it is not suitable for a small BLDC motor sensorless drive. This paper presents control methods suitable for economic small BLDC motor sensorless drive which are an improved design of the BEMF detection circuit, simplifying a complex algorithm and computation time reduction. The improved motor sensorless drive is verified stability and validity through being designed, manufactured and analyzed.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.184-184
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• 2012

We proposed a new measurement method of cutoff probe using the reactance spectrum of the plasma in cutoff probe system instead of transmission spectrum. The high accurate reactance spectrum of the plasma which is expected in previous circuit simulation of cutoff probe [1] was measured by using the automatic port extension method of the network analyzer. The measured reactance spectrum is good agreement with E/M wave simulation result (CST Microwave Studio). From the analysis of the measured reactance spectrum based on the circuit modeling, not only the electron density but also electron-neutral collision frequency can be simply obtained. The obtained results of electron density and e-n collision frequency were presented and discussed in wide range of experimental conditions, together with comparison result with previous methods (a previous cutoff probe using transmission spectrum and a single langmuir probe).

• Korean Journal of Computational Design and Engineering
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• v.13 no.2
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• pp.131-138
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• 2008

With the advancements of the Internet and CAD data translation techniques, more CAD models are transferred from a CAD system to another through the network and interoperability is getting a common word in the CAD industry. However, when a CAD model is translated for an incompatible system into a neutral format such as STEP or IGES, its precious feature information is lost. When this feature information is lost, the advantage of feature based modeling is not valid any longer, and modification for the model is purely dependent on geometric and topological manipulations. However, the capabilities of the existing methods to modify these feature-independent models are limited as the modification involves a topological change in the model. To address this issue, we present a volumetric method to modify the solid models in neutral format. First, this method selectively decomposes the solid model to separate the portion of interest called feature volume. Next, the designer modifies the feature volume without concerning a topological change. Finally, the feature volume is united with the original solid model to complete the modification process. The results of test cases are presented to attest the usefulness of the proposed method.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.27-32
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• 2024

This study analyzed cases of hydrogen (H₂) and natural gas (CH₄) leakage from a hydrogen-blended natural gas pipeline to determine a range of leakage characteristics, including leakage type, pipe material, pipe diameter, pressure, and damage size. Based on the results of this analysis, five hydrogen-blended natural gas leakage scenarios were selected. The national vision for a carbon-neutral society by 2050 is a very important strategic objective and promotes environmentally sustainable economic development in the age of the climate crisis. Accordingly, zero-carbon and low-carbon policies are being promoted in various fields, including energy production, consumption, and industrial processes. Hydrogen-blended natural gas is eco-friendly and is considered an important step towards carbon neutrality, with various countries including the United States and several European countries conducting empirical research to further investigate its potential. In Korea, a national research project commenced in April 2023 to verify and demonstrate the life cycle safety of blending hydrogen into the natural gas network. The results of this study will provide important data for the analysis of the damage impacts caused by the leakage of hydrogen-blended natural gas, such as the diffusion of gas clouds, fires, and gas explosions.

• Journal of Digital Convergence
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• v.9 no.4
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• pp.91-101
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• 2011

We examined current publications on artificial neural network development with a View to identifying the methodologies that are being used to develop these networks, how extensive these methodologies are, the categorization of these methodologies, if these methodologies demonstrate a common underlying and generic (standard) methodology for the development of artificial neural networks, and how closely these methodologies (and the underlying genetic methodology, if established) relate to the conventional systems development methodologies.

• The Journal of Industrial Distribution & Business
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• v.13 no.6
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• pp.9-18
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• 2022

Purpose: The government around the world is still highlighting the effect of the new variant of Covid-19. The government continues to make efforts to restore the economy through several programs, one of them is National Economic Recovery. This program is expected to increase public and investor confidence in handling Covid-19. This study aims to capture public sentiment on the economic growth rate in Indonesia, especially during the third wave of the omicron variant of the covid-19 virus, that is at the time in the fourth quarter of 2021. Research design, data, and methodology: The approach used in this research is to collect crowdsourcing data from twitter, in the range of 1st to 10th October 2021. The analysis is done by building model using Deep Learning Neural Network method. Results: The result of the sentiment analysis is that most of the tweets have a neutral sentiment on the Economic Growth discussion. Several central figures who discussed were Minister of Coordinating for the Economy of Indonesia, Minister of State-Owned Enterprises. Conclusions: Data from social media can be used by the government to capture public responses, especially public sentiment regarding economic growth. This can be used by policy makers, for example entrepreneurs to anticipate economic movements under certain conditions.