• East Asian mathematical journal
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• v.38 no.1
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• pp.65-84
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• 2022

This paper is based on Yanbian University's physical test data, and uses statistical analysis methods to study the relationship between college students' physical test scores to promote college physical education. Firstly, using gender as categorical variables, we conduct a general analysis of students in different majors and different grades, and obtain the advantages and disadvantages of male and female college students; then we use Decision Trees and Random Forest algorithms to conduct modeling analysis to provide valuable suggestions for relevant departments of the university. the aiming of this research analyzing about the undergraduates physical test is that giving universities the targeted suggestions to improve the college graduate rate and promote the overall development of higher education, lay the foundation for achieving universal health.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.131-135
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• 2023

Neural network-based time series models called time series neural networks (TSNNs) are trained by the error backpropagation algorithm and used to predict process shifts of parameters such as gas flow, RF power, and chamber pressure in reactive ion etching (RIE). The training data consists of process conditions, as well as principal components (PCs) of optical emission spectroscopy (OES) data collected in-situ. Data are generated during the etching of benzocyclobutene (BCB) in a SF₆/O₂ plasma. Combinations of baseline and faulty responses for each process parameter are simulated, and a moving average of TSNN predictions successfully identifies process shifts in the recipe parameters for various degrees of faults.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.3
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3859-3865
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• 2010

Modeling a virtual reader and tags, the emulator system is realized by using a commercial signal generation device to make signal, a data collection equipment, and DSP board. By using a Virtual UHF RFID (860 ~ 960 [MHz]) reader/tags module, a developed RFID reader, protocol of tag, and properties of RF support to provide the way how to verify the suitability to international standards (ISO 18000-6 Type C, EPCglobal C1G2). In this paper, to implement a proposed model reader and tag model, Visual DSP is applied by using DSP board, composing the system's signal generators, signal analyzers and performance verification, the target readers or tags, RFID emulator control computesr and control programs.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.52-59
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• 2004

Recently, many researches for fine particles plasma have been focused on the fabrication of the new devices and materials in micro-electronic industry, although reduction or elimination of fine particles was interested in plasma processing until now on. In order to enhance their utilization, it is necessary to control and analyze fine particle behavior. Therefore, we developed simulation model of fine particles in RF Ar plasmas. This model consists of the calculation parts of plasma structure using a two-dimensional fluid model and of fine particle behavior. The motion of fine particles was derived from the charge amount on the fine particles and forces applied to them. In this paper, Ar plasma properties using two-dimensional fluid model without fine particles were calculated at power source voltage 15[V] and pressure 0.5[Torr]. Time-averaged spatial distributions of Ar plasma were shown. The process on the formation of Coulomb crystal of fine particles was investigated and it was explained by combination of ion drag and electrostatic forces. And also analysis on the forces of fine particles was presented.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.12
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• pp.49-57
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• 2001

In this paper, equivalent circuit model and novel model parameter extraction method of a silicon(Si) substrate are presented. Substrate coupling through Si-substrate is quantitatively investigated by analyzing equivalent circuit with operating frequency and characteristic frequencies (i.e., pole and zero frequency) of a system. For the experimental verification of the equivalent circuit and parameter extraction method, test patterns are designed and fabricated in standard CMOS technology with various isolation distances, substrate resistivity, and guard-ring structures. Then, these are measured in l00MHz-20GHz frequency range by using vector network analyzer. It is shown that the equivalent-circuit-based HSPICE simulation results using extracted parameters have excellent agreement with the experimental results. Thus, the proposed equivalent circuit and parameter extraction methodology can be usefully employed in mixed-signal circuit design and verification of a circuit performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.114-122
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• 2014

For an efficient finite-difference time-domain(FDTD) analysis of coaxial-probe feeding structures in radio frequency(RF) and microwave bands, an interrelation between equivalent source modeling techniques is investigated. In existing literature, equivalent source models with delta-gap or magnetic-frill concepts have been developed by many researchers. It is well known that FDTD implementation and computational accuracy of these source models are slightly different. In this paper, the interrelation between FDTD equivalent source models for coaxial feeding structures under the quasi-static approximation(QSA) is presented. As a function of FDTD equivalent source models, time-domain and frequency-domain responses of a coaxial-probe fed conical monopole antenna are calculated numerically. And comparison results of computational accuracy and efficiency are provided.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.50-60
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• 2018

In this paper, we developed a broadband multi-layered radome applicable for high-power applications. In this regard, we presented the wave propagation characteristics of the broadband multi-layered radome with the ABCD matrix and obtained the optimal thickness and the material constant for each layer by an optimization algorithm called "particle swarm optimization," implemented by a commercial numerical modeling tool. Further, we redesigned it in view of mechanical properties to reflect environmental conditions such as wind, snow, and ice. The power transmission property was reanalyzed based on the recalculated data of each layer's thickness to consider the limitations of the fabrication of a large structure. Under the condition of a peak electric field strength that is 10 dB above the critical electric field strength in air breakdown, we analyzed the air breakdown by radio frequency(RF) in the designed radome using the commercial full-wave electromagnetic tool. The radome was manufactured and tested by continuous wave(CW) RF small signal and large signal in an anechoic chamber. The test results showed good agreement with those attained by simulation.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.29-39
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• 2017

Various electronic warfare situations drive the need to develop an integrated electronic warfare simulator that can perform electronic warfare modeling and simulation on radar threats. In this paper, we analyze the components of a simulation system to reversely model the radar threats that emit electromagnetic signals based on the parameters of the electronic information, and propose a method to gradually maintain the reverse extrapolation model of RF threats. In the experiment, we will evaluate the effectiveness of the incremental model update and also assess the integration method of reverse extrapolation models. The individual model of RF threats are constructed by using decision tree, naive Bayesian classifier, artificial neural network, and clustering algorithms through Euclidean distance and cosine similarity measurement, respectively. Experimental results show that the accuracy of reverse extrapolation models improves, while the size of the threat sample increases. In addition, we use voting, weighted voting, and the Dempster-Shafer algorithm to integrate the results of the five different models of RF threats. As a result, the final decision of reverse extrapolation through the Dempster-Shafer algorithm shows the best performance in its accuracy.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.185-190
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• 2007

In this paper, minimum sampling rates and method of nonlinear characterization were suggested for low power, quasi-memoryless PAs. So far, the Nyquist rate of the input signal has been used for nonlinear PA modeling, and it is burdening Analog-to-digital converters for wideband signals. This paper shows that the input Nyquist rate sampling is not a necessary condition for successful modeling of quasi-memoryless PAs. Since this sampling requirement relives the bandwidth requirements for Analog-to-digital converters (ADCs) for feedback paths in digital pre-distortion systems, relatively low-cost ADcs can be used to identify nonlinear PAs for wideband signal transmission, even at severe aliasing conditions. Simulation results show that a generic memoryless nonlinear RF power amplifier with AMAM and AMPM distortion can be successfully identified at any sampling rates. Measurement results show the modeling error variation is less than 0.8dB over any sampling rates.