• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.6
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• pp.477-482
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• 2017

When using the FDM to create a 3D object, a thermoplastic filament is heated to its melting point and then extruded layer by layer. Although the FDM printing process has many advantages, its accuracy, and surface finish are not satisfactory. In recent years, much research has been devoted to improving the accuracy of the FDM printing process. The temperature difference between the nozzle and the interior of the chamber of a 3D printer is one of the important parameters affecting the printing process. In this study, we propose a methodology to reduce this temperature difference through design improvement. In addition, we elucidate how this design improvement affects product quality. The FDM printing process is conventionally carried out in a closed chamber. However, in this study, an open heating system is used to reduce the temperature. The FDM printing processes were simulated using FEM analysis.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.406-413
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• 2020

In this paper, to improve the classification accuracy of bird and amphibian acoustic sound, we utilize GLU (Gated Linear Unit) and Self-attention that encourages the network to extract important features from data and discriminate relevant important frames from all the input sequences for further performance improvement. To utilize acoustic data, we convert 1-D acoustic data to a log-Mel spectrogram. Subsequently, undesirable component such as background noise in the log-Mel spectrogram is reduced by GLU. Then, we employ the proposed temporal self-attention to improve classification accuracy. The data consist of 6-species of birds, 8-species of amphibians including endangered species in the natural environment. As a result, our proposed method is shown to achieve an accuracy of 91 % with bird data and 93 % with amphibian data. Overall, an improvement of about 6 % ~ 7 % accuracy in performance is achieved compared to the existing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.979-985
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• 2011

One of the most important means in modem NQ (Network Quotient) emphasized society is the communication skill. Therefore, it is mostly necessary to accurately express his or her own idea and maximize own communication competence. For this, efforts on improving pronunciation accuracy, such as pronunciation stretching practice and vocal cords reflex point acupressure therapy, have been devoted for communication competence in daily life. However, objective and positive method to substantiate such efforts has not yet been studied to find if the methods can improve pronunciation accuracy in effect. We, therefore, propose an IT based method of substantiation and quantization for such pronunciation accuracy improvement methods. Voice analysis on voice data sample of 30 males in 20s, before and after pronunciation stretching practice and vocal cords reflex point acupressure, has been performed in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2727-2732
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• 2014

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.335-340
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• 2018

Commercialized speech recognition systems that have an accuracy recognition rates are used a learning model from a type of speaker dependent isolated data. However, it has a problem that shows a decrease in the speech recognition performance according to the quantity of data in noise environments. In this paper, we proposed the vector quantization based speech recognition performance improvement using maximum log likelihood in Gaussian distribution. The proposed method is the best learning model configuration method for increasing the accuracy of speech recognition for similar speech using the vector quantization and Maximum Log Likelihood with speech characteristic extraction method. It is used a method of extracting a speech feature based on the hidden markov model. It can improve the accuracy of inaccurate speech model for speech models been produced at the existing system with the use of the proposed system may constitute a robust model for speech recognition. The proposed method shows the improved recognition accuracy in a speech recognition system.

• Journal of IKEEE
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• v.26 no.3
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• pp.468-474
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• 2022

In this paper, we propose a method to implement a real-time fire alarm system using deep learning. The deep learning image dataset for fire alarms acquired 1,500 sheets through the Internet. If various images acquired in a daily environment are learned as they are, there is a disadvantage that the learning accuracy is not high. In this paper, we propose a fire image data expansion method to improve learning accuracy. The data augmentation method learned a total of 2,100 sheets by adding 600 pieces of learning data using brightness control, blurring, and flame photo synthesis. The expanded data using the flame image synthesis method had a great influence on the accuracy improvement. A real-time fire detection system is a system that detects fires by applying deep learning to image data and transmits notifications to users. An app was developed to detect fires by analyzing images in real time using a model custom-learned from the YOLO V4 TINY model suitable for the Edge AI system and to inform users of the results. Approximately 10% accuracy improvement can be obtained compared to conventional methods when using the proposed data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.190-197
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• 2024

The O2O store model dissolves the boundaries between online and offline platforms, providing significant convenience to customers. To effectively operate such platforms, small business owners must provide necessary information in digital format. Specifically, the process of digitizing Korean menus manually can lead to multiple issues, and the use of OCR technology often results in high error rates due to the low accuracy in recognizing Korean. In response, this paper proposes an enhanced OCR model based on the popular EasyOCR framework, aimed at improving the recognition accuracy of Korean. The proposed model integrates the structural advantages of VGG and ResNet, and incorporates an attention mechanism to significantly improve the recognition performance of Korean. Moreover, experimental results indicate that the proposed model achieved approximately a 3.5% improvement in accuracy and around a 1% improvement in both confidence score and normalized edit distance compared to EasyOCR. Therefore, this demonstrates that the proposed method effectively addresses the existing challenges.

• Journal of Dental Rehabilitation and Applied Science
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• v.35 no.2
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• pp.55-63
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• 2019

The aim of this article was to review various methods used to evaluate the accuracy of digital dental models. When evaluating the accuracy of digital models, the errors can be reduced by educating examiners and using artificial landmarks. The accuracy evaluation methods of digital dental models are divided into linear measurement, 2-dimensional cross-sectional analysis, and 3-dimensional best fit measurement. As the technology of scanners develops, many studies have been conducted to compare the accuracy of digital impression and conventional impression. According to improvement of scan technologies and development of 3-dimensional model analysis software, the ability to evaluate the accuracy of digital models is becoming more efficient. In this article, we describe the methods for evaluating the accuracy of a digital model and investigate effective accuracy analysis methods for each situation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.408-413
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• 2013

Micro-features such as grooves and lenses, which perform optical functions in flat displays, should be manufactured with a good form accuracy because this is directly related to their optical performance. As the size of the display increases, it is very difficult to maintain a high relative accuracy because of the inherent geometric errors such as the waviness of a large-area plate. In this paper, the optical effect of these geometric errors is investigated, and surface-referenced micro-grooving to measure and compensate for such geometric errors on line is proposed to improve the form accuracy of the micro-grooves. A PZT-based fast depth adjustment servo system is implemented in the tool holder to maintain a uniform groove depth in reference to the wavy surface. Through experiments, the proposed method is shown to be an efficient way to produce high-quality micro- grooves on a wavy die surface.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.68-74
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• 1999

One of the recent changes in machining technology is rapid application of micro- and high precision grinding processes. A fine groove generation is necessary for the fabrication of optic, electronic and semiconductor parts, and achieved by chemical or mechanical processes. Slot grinding is very efficient for the generation of micro ordered groove with hard and brittle materials. As slot grinding is continuous, the ground depth become gradually shallow because of wheel wear. The form accuracy become worse from the increase of ground slot width by the loading phenomena at wheel side, results on chipping damage of the workpiece. The experiments achieve to the enhancement of the form accuracy and chipping free of the brittle materials using V shaped cast iron bonded diamond wheels. In this study we focused on the investigation of the effect of the high pressure air jet on the grinding characteristics. As a results, we found that the high pressure air jet is very effective on the reductions of the wheel wear, enhancement of the form accuracy.