• Design & Manufacturing
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• v.16 no.3
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• pp.22-27
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• 2022

The demand for new processing technology that can improve productivity is increasing in industries that require large-scale and various products. In response to this demand, a robot machining system with flexibility is required. Because of the low rigidity of the robot, the robot machining system has a large error during machining and is vulnerable to vibration generated during machining. Vibration generated during machining deteriorates machining quality and reduces the durability of the machine. To solve this problem, a stage for fixing the spindle during machining is required. In order to compensate for the robot's low rigidity, a system combining a piezoelectric actuator for generating a large force and a guide mechanism to actuate with a desired direction is required. Since the rigidity of flexible hinges varies depending on the structure, it is important to optimal design the flexible hinge and high-rigidity system. The purpose of this research is to make analytic model and optimize a flexible hinge and to design a high rigidity stage. In this research, to design a flexible hinge stage, a concept design of system for high rigidity and flexure hinge modeling is carried out. Based on analytic modeling, the optimal design for the purpose of high rigidity is finished and the optimal design results is used to check the error between the modeling and actual simulation results.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.7
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• pp.15-24
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• 2021

In this paper, to analyze the types of surface morphology error according to factors that cause machining error, the experiments were conducted in the ultra-precision diamond machine using a diamond tool. The factors causing machining error were classified into the pressure variation of compressed air, external shock, tool errors, machining conditions (rotational speed and feed rate), tool wear, and vibration. The pressure variation of compressed air causes a form accuracy error with waviness. An external shock causes a ring-shaped surface defect. The installed diamond tool for machining often has height error, feed-direction position error, and radius size error. The types of form accuracy error according to the tool's errors were analyzed by CAD simulation. The surface roughness is dependent on the tool radius, rotational speed, and feed rate. It was confirmed that the surface roughness was significantly affected by tool wear and vibration, and the surface roughness of Rz 0.0105 ㎛ was achieved.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.3
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• pp.9-23
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• 2022

This study aims to examine research trends on the Internet of Things and smart city based on papers from the United States, Japan, and Korea. We collected 7113 papers related to the Internet of Things and smart city published from 2016 to 2021 in Elsevier's Scopus. Keyword frequency and centrality analysis were performed based on the abstracts of the collected papers. We found keywords with high frequency of appearance by calculating keyword frequency and identified central research keywords through the centrality analysis by country. As a result of the analysis, research on security, machine learning, and edge computing related to the Internet of Things and smart city were the most central and highly mediating research conducted in each country. As an implication, studies related to deep learning, cybersecurity, and edge computing in Korea have lower degree centrality and betweenness centrality compared to the United States and Japan. To solve the problem it is necessary to combine these studies with various fields. The future research direction is to analyze research trends on the Internet of Things and smart city in various regions such as Europe and China.

• The Journal of Korea Robotics Society
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• v.16 no.4
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• pp.306-312
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• 2021

This paper describes localization of autonomous underwater vehicles(AUV), which can be used when some navigation sensor data are an outlier. In that situation, localization through existing navigation algorithms causes problems in long-range localization. Even if an outlier sensor data occurs once, problems of localization will continue. Also, if outlier sensor data is related to azimuth (direction of AUV), it causes bigger problems. Therefore, a parallel localization module, in which different algorithms are performed in a normal and abnormal situation should be designed. Before designing a parallel localization module, it is necessary to study an effective method in the abnormal situation. So, we propose a localization method through machine learning. For this method, a learning model consists of only Fully-Connected and trains through randomly contaminated real sea data. The ground truth of training is displacement between subsequent GPS data. As a result, average error in localization through the learning model is 0.4 times smaller than the average error in localization through the existing navigation algorithm. Through this result, we conclude that it is suitable for a component of the parallel localization module.

• Smart Structures and Systems
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• v.33 no.2
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• pp.105-118
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• 2024

In order to realize tiny bridge crack discovery by UAV-based machine vision, a novel method combining deep learning and tensor voting is proposed. Firstly, the grid images of crack are detected and descripted based on SE-ResNet50 to generate feature points. Then, the probability significance map of crack image is calculated by tensor voting with feature points, which can define the direction and region of crack. Further, the crack detection anchor box is formed by non-maximum suppression from the probability significance map, which can improve the robustness of tiny crack detection. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method in the Xiangjiang-River bridge inspection. Compared with the original tensor voting algorithm, the proposed method has higher accuracy in the situation of only 1-2 pixels width crack and the existence of edge blur, crack discontinuity, which is suitable for UAV-based bridge crack discovery.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Cartoon and Animation Studies
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• s.39
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• pp.261-295
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• 2015

Cyber singer appeared in the late 1990s has disappeared briefly appeared. although a few attempts in the 2000s, it did not show significant successes. cyber singer was born thanks to the technical development of the IT industry and the emergence of an idol training system in the music industry. It was developed by Vocaloid 'Seeyou' starting from 'Adam'. cyber singer that differenatiated typical digital characters in a cartoon or game may be subject to idolize to the music as a medium. They also feature forming a plurality of fandom. therefore, such attempts and repeated failures, this could be considered a fashion, but it flew content creation and ongoing attempts to take advantage of the new media, such as Vocaloid can see that there are expectations for a true Cyber-born singer. Early-Cyber singer is made only resemble human appearance, but 'Sciart' and 'Seeyou' has been evolving to becoming more like the human capabilities. in this paper, stylized cyber singer had disappeared in the past in the process of developing the technology to evolve into own artificial life does not end in failure cases, gradually led to a change in public perceptions of the image look looking machine was an attempt in that sense. With the direction of the evolution of the mechanical function to obtain a human, fun and human exchanges and mutual feelings. And it is equipped with an artificial life form that evolved with it only in appearance and function. in order to support this logic, I refer to the study of the coevolution of man and machine at every Bruce Mazlish. And, I have analyzed the evolution of cyber singer Bruce research from the perspective of the development process since the late 1990s, the planning of the eight singers who have appeared and design of the cyber character and important voices to be evaluated as a singer (vocal). The machine has been evolving coevolution with humans. cyber singer ambivalent development targets are recognized, but strive to become the new artificial creatures of horror idea of human desire and death continues. therefore, the new Cyber-organisms are likely to be the same style as 'Seeyou'. because, cartoon forms and whirring voice may not be in the form of a signifier is the real human desires, but this is because the contemporary public's desire to be desired and the technical development of this type can be created at the point where the cross-signifier.

• The korean journal of orthodontics
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• v.34 no.3 s.104
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• pp.219-227
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• 2004

The purpose of this study was to evaluate the spatial changes of mesial-in rotated maxillary molar and opposite anchor tooth during derotation by the precision transpalatal arch (TPA) with the use of a new typodont simulation system, the Calorific machine system, which was designed to observe the whole process of tooth movement. The maxillary right first molar was used for the anchor tooth and the maxillary left first molar was used for the mesial-in rotated tooth, and the angle of rotation was increased to 20,40, and 60. A passive precision TPA was fabricated and then activated by bending the left arm to 20, 40, and 60. Each experiment was repeated five times under the same conditions and analyzed by ANOVA and Tucky's Studentized Range (HSD) test. In the occlusal plane, when the bending angle of precision TPA was increased, the mesiobuccal cusp of the rotated molar moved more buccally (p<0.001) and less distally (p<0.001) while the distolingual cusp moved in the mesiopalatal direction. In the sagittal plane, the palatal roots of the derotated molar moved mesially (p<0.001). In the traverse plane, the derotated molar showed slight extrusion (p<0.001). The upper right first molar, which was used as an anchor tooth, showed clinically insignificant movement across all three planes.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.11
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• pp.445-452
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• 2017

Electric pole is a supporting beam used for power transmission/distribution which accelerometer are used for measuring a external force. The meteorological condition has various effects on the external forces of electric pole. One of them is the elasticity change of the aerial wire. It is very important to perform modelling. The acceleration sensor is converted into a pitch and a roll angle. The meteorological condition has a high correlation between variables, and selecting significant explanatory variables for modeling may result in the problem of over-fitting. We constructed high deviance explained model considering multicollinearity using the Generalized Additive Model which is one of the machine learning methods. As a result of the Variation Inflation Factor Test, we selected and fitted the significant variable as temperature, precipitation, wind speed, wind direction, air pressure, dewpoint, hours of daylight and cloud cover. It was noted that the Hours of daylight, cloud cover and air pressure has high explained value in explonatory variable. The average coefficient of determination (R-Squared) of the Generalized Additive Model was 0.69. The constructed model can help to predict the influence on the external forces of electric pole, and contribute to the purpose of securing safety on utility pole.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1040-1047
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• 2015

This study is investigated for M2M Communication Network Standard based on 3GPP. The environment of M2M communication, we can predict the new mobile service that gathering, handling, controlling, transferring of the data for Intelligence, so that we can consider new direction for a lot of subject of study development issue. This study is shown three types of M2M network structure and four types of use cases on 3GPP International Standard. In Addition, we can introduce the future M2M communication network model, it can be propagate the industry and academic cooperation with 3GPP standards. The suggestion develops multiple applications and multiple devices for industry and academic. With the deployment of network provider, this environment support our current communication market that the standard devices of M2M network and service requirement. We are suggest this study for grasp the initial market with the intellectual property right (IPR) based on International Standards. In the future, we wish the success that grap the initial market or initial academic study with helpful issue.