• ETRI Journal
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• 제43권4호
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• pp.728-745
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• 2021

Carbon nanotube field-effect transistors (CNTFETs) have been widely studied as a promising technology to be included in post-complementary metal-oxide-semiconductor integrated circuits. Despite significant advantages in terms of delay and power dissipation, the fabrication process for CNTFETs is plagued by fault occurrences. Therefore, developing a fast and accurate method for estimating the reliability of CNTFET-based digital circuits was the main goal of this study. In the proposed method, effects related to faults that occur in a gate's transistors are first represented as a probability transfer matrix. Next, the target circuit's graph is traversed in topological order and the reliabilities of the circuit's gates are computed. The accuracy of this method (less than 3% reliability estimation error) was verified through various simulations on the ISCAS 85 benchmark circuits. The proposed method outperforms previous methods in terms of both accuracy and computational complexity.

• International journal of advanced smart convergence
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• 제11권2호
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• pp.185-193
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• 2022

There have been various studies in Korea to develop a %IMF(Intramuscular Fat Percentage) estimation method suitable for Hanwoo. Recently, a %IMF estimation method using a convolutional neural network (CNN), a kind of deep learning method among artificial intelligence methods, has been studied. In this study, we performed a performance comparison when various preprocessing methods were applied to the %IMF estimation of ultrasound images using CNN as mentioned above. The preprocessing methods used in this study are normalization, histogram equalization, edge enhancement, and a method combining normalization and edge enhancement. When estimating the %IMF of Hanwoo by the conventional method that did not apply preprocessing in the experiment, the accuracy was 98.2%. The other hand, we found that the accuracy improved to 99.5% when using preprocessing with histogram equalization alone or combined regularization and edge enhancement.

• Journal of Positioning, Navigation, and Timing
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• 제12권2호
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• pp.157-166
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• 2023

Several experiments were carried out to analyze the impact of the modernized Global Positioning System (GPS) L2C signal on pseudorange-based point positioning. Three dual-frequency positioning algorithms, ionosphere-free linear combination, ionospheric error estimation, and simple integration, were used, and the results were compared with those of Standard Point Positioning (SPP). An analysis was conducted to determine the characteristics of each dual-frequency positioning method, the impact of the magnitude of ionospheric error, and receiver grade. Ionosphere-free and ionospheric error estimation methods can provide improved positioning accuracy relative to SPP because they are able to significantly reduce the ionospheric error. However, this result was possible only when the ionospheric error reduction effect was greater than the disadvantage of these dual-frequency positioning algorithms such as the increment of multipath and noise, impact of uncertainty of unknown parameter estimation. The RMSE of the simple integration algorithm was larger than that of SPP, because of the remaining ionospheric error. Even though the receiver grade was different, similar results were observed.

• 한국포장학회지
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• 제29권3호
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• pp.163-174
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• 2023

Though box compression strength (BCS) is commonly used as a performance criterion for shipping containers, estimating BCS remains a challenge. In this study, artificial neural networks (ANN) are implemented as a new tool, with a focus on building up ANN architectures for BCS estimation. An Artificial Neural Network (ANN) model can be constructed by adjusting four modeling factors: hidden neuron numbers, epochs, number of modeling cycles, and number of data points. The four factors interact with each other to influence model accuracy and can be optimized by minimizing model's Mean Squared Error (MSE). Using both data from the literature and "synthetic" data based on the McKee equation, we find that model estimation accuracy remains limited due to the uncertainty in both the input parameters and the ANN process itself. The population size to build an ANN model has been identified based on different data sets. This study provides a methodology guide for future research exploring the applicability of ANN to address problems and answer questions in the corrugated industry.

• 한국군사과학기술학회지
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• 제3권1호
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• pp.85-91
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• 2000

Underwater sensor accuracy test which measures the detection range and bearing accuracies of sonar simulates sonar transmitting ping and underwater radiating noise of target vessels. In this test, because the position of sonar target is the reference position of test, the sonar target position should be precisely estimated. Hence, this paper suggests to apply USBL algorithm which adopts cross phase spectrum of received sensor signals, and presents its performance by range and bearing estimation simulations. As a result of simulations, suggested algorithm shows good accuracy for underwater sensor accuracy test near 5㏈ SNR.

• 전기학회논문지
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• 제65권1호
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• pp.194-199
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• 2016

EMG has specific information which is related to movements according to the activities of muscles. Therefore, users can intuitively control a prosthesis. For this reason, biosignals are very useful and convenient in this kind of application. Bioimpednace also provides specific information about movements like EMG. In this study, we used both EMG and bioimpedance to classify the typical hand gestures such as hand open, hand close, no motion (rest), supination, and pronation. Nine able-bodied subjects and one amputee were used as experimental data set. The accuracy was $98{\pm}1.9%$ when 2 bio-impedance and 8 EMG channels were used together for normal subjects. The number of EMG channels affected the accuracy, but it was stable when more than 5 channels were used. For the amputee, the accuracy is higher when we use both of them than when using only EMG. Therefore, accurate and stable hand motion estimation is possible by adding bioimepedance which shows structural information and EMG together.

• 한국정밀공학회지
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• 제23권9호
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• pp.76-83
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• 2006

Machining accuracy is closely related with tool deflection induced by cutting forces. In this research, cutting forces and tool deflection in end milling are expressed as a closed form of tool rotational angle and cutting conditions. The discrete cutting fores caused by periodic tool entry and exit are represented as a continuous function using the Fourier series expansion. Tool deflection is predicted by direct integration of the distributed loads on cutting edges. Cutting conditions, tool geometry, run-outs and the stiffness of tool clamping part are considered together far cutting forces and tool deflection estimation. Compared with numerical methods, the presented method has advantages in prediction time reduction and the effects of feeding and run-outs on cutting forces and tool deflection can be analyzed quantitatively. This research can be effectively used in real time machining error estimation and cutting condition selection for error minimization since the form accuracy is easily predicted from tool deflection curve.

• Journal of international Conference on Electrical Machines and Systems
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• 제2권2호
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• pp.184-189
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• 2013

This paper proposes a method for improving the performance of a position sensorless control system for a slotless surface permanent magnet synchronous motor (SPMSM) in a very low-speed region. In position sensorless control based on a motor model, accurate motor parameters are required because parameter errors would affect position estimation accuracy. Therefore, online parameter identification is applied in the proposed system. The error between the reference voltage and the voltage applied to the motor is also affect position estimation accuracy and stability, thus it is compensated to ensure accuracy and stability of the sensorless control system. In this study, two voltage error compensation methods are used, and the effects of the compensation methods are discussed. The performance of the proposed sensorless control method is evaluated by experimental results.

• 한국멀티미디어학회논문지
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• 제17권8호
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• pp.915-922
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• 2014

We propose an adaptive zoom motion estimation method where a picture is divided into two areas based on the distance information with a depth camera : the one is object area and the other is background area. In the proposed method, the zoom motion is only applied to the object area except the background area. Further, the block size of motion estimation for the object area is set to smaller than that of background area. This adaptive zoom motion estimation method can be reduced at the complexity of motion estimation and can be improved at the motion estimation performance by reducing the block size of the object area in comparison with the conventional zoom motion estimation method. Based on the simulation results, the proposed method is compared with the conventional methods in terms of motion estimation accuracy and computational complexity.

• International Journal of Computer Science & Network Security
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• 제24권6호
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• pp.17-22
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• 2024

Software cost and schedule estimation is usually based on the estimated size of the software. Advanced estimation techniques also make use of the diverse factors viz, nature of the project, staff skills available, time constraints, performance constraints, technology required and so on. Usually, estimation is based on an estimation model prepared with the help of experienced project managers. Estimation of software cost is predominantly a crucial activity as it incurs huge economic and strategic investment. However accurate estimation still remains a challenge as the algorithmic models used for Software Project planning and Estimation doesn't address the true dynamic nature of Software Development. This paper presents an efficient approach using the contemporary Constructive Cost Model (COCOMO) augmented with the desirable feature of fuzzy logic to address the uncertainty and flexibility associated with the cost drivers (Effort Multiplier Factor). The approach has been validated and interpreted by project experts and shows convincing results as compared to simple algorithmic models.