• The Journal of Korean Academy of Prosthodontics
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• v.59 no.1
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• pp.79-87
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• 2021

The digital workflow of optical impressions by the intraoral scanner and CADCAM manufacture of dental prostheses is actively developing. The complex process of traditional impression taking, definite cast fabrication, wax pattern making, and casting has been shortened, and the number of patient's visits can also be reduced. Advances in intraoral scanner technology have increased the precision and accuracy of optical impression, and its indication is progressively widened toward the long span fixed dental prosthesis. This case report describes the long span implant case, and the operator fully utilized digital workflow such as computer-guided implant surgical template and CAD-CAM produced restoration after the digital impression. The provisional restoration and customized abutments were prepared with the optical impression taken on the same day of implant surgery. Moreover, the final prosthesis was fabricated with the digital scan while utilizing the same customized abutment from the provisional restoration. During the data acquisition step, stl data of customized abutments, previously scanned at the time of provisional restoration delivery, were imported and automatically aligned with digital impression data using an 'A.I. abutment matching algorithm' the intraoral scanner software. By using this algorithm, it was possible to obtain the subgingival margin without the gingival retraction or abutment removal. Using the digital intraoral scanner's advanced functions, the operator could shorten the total treatment time. So that both the patient and the clinician could experience convenient and effective treatment, and it was possible to manufacture a prosthesis with predictability.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.248-255
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• 2021

The main causes of the July 2013 OZ 214 accident were poorly performed approach and the failure to recognize the autothrottle in the HOLD position which the automated speed control was not provided. The pilots late decision for go-around was also a critical factor leading to the accident. The B777 POM restricts the use of FLCH mode beyond the FAF. This research utilized the QAR data of an airline's B777 fleet in the period of two years where 44 cases were found. In many cases, the FLCH mode was used for rapid descent from an higher than normal situation. In addition, in the base turn, continuous use of FLCH mode even when the path was below the glide path were observed. Airports with elevation above 500 ft MSL had a higher rate of occurrence. In this research, the proper descent planning and vertical path monitoring, and the adherence to the limitation set in the manuals and the stabilized approach criteria were re-emphasized as mitigation to reduce event occurences.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.183-191
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• 2021

The advanced development of the world's economies requires a detailed study of the impact of factors on the level of digitalization, to ensure economic growth and promote the use of information and communication technologies in the digital economy. Digitalization of the world's economies is ensured through the implementation of relevant regulations and policy decisions to implement public policy and strategy of the digital economy. The purpose of the study is to establish the pattern of the impact of factors on the level of digitalization of world economies by conducting a regression analysis to reflect the dependence of the impact of factors on the level of digitalization in 25 economies (by IMD digital competitiveness), to check the level of digitalization of the world's economies. It is necessary to analyze the ranking of countries in the world according to the DiGiX Index, IMD, and DESI Digital Competitiveness Rating. Research methods: information synthesis method; regression analysis; systematization, and generalization. Results. It was found that because of regression analysis, the value of the coefficient of determination indicates that the regression model by 78% explains the relationship between future readiness of countries to implement digital technologies and information and communication technologies, but there are still a small number of other factors not included in the regression model. It is determined that the greatest progress among EU member states for the period 2015-2020 according to the DESI index belongs to Ireland, the Netherlands, Malta, and Spain. It is established that Estonia, Spain, and Denmark are in the lead in the DESI rating, in terms of e-government implementation. The study found that the impact of factors on the level of digitalization of world economies contributes to solving current economic problems through further implementation of information and communication technologies and improving legislation in the digital economy, which will ensure the implementation of effective digital policy. It is established that ensuring the appropriate level of digitalization of the world's economies should solve the problems in the digital economy sector faced by governments and businesses, which requires the implementation of measures to regulate and ensure the continued operation of the digital economy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.845-856
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• 2020

This study proposes a bridge evaluation system for indivisible permit vehicles such as hydraulic cranes. The permit loads for the bridge evaluation are divided into three categories: routine permit loads, special permit 1 loads, and special permit 2 loads. Routine permit and special permit 1 vehicles are allowed to cross a bridge with normal traffic. For these two permits, the standard lane model in the Korean Highway Bridge Design Code was adopted to consider normal traffic in the same lane. Special permit 2 vehicles are assumed to cross a bridge without other traffic. Structural analyses of two prestressed-beam bridges and two steel box girder bridges were conducted for the proposed permit loads. The rating factors of the four bridges for all permit loads were calculated as sufficiently large values for the moment and shear force so that crossing the bridges can be permitted. A reliability assessment of the bridges was performed to identify the reliability levels for the permit vehicles. It was confirmed that the reliability level of the minimum required strength obtained by the load-resistance factors yields the target reliability index of the design code for the permit vehicles.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.1-13
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• 2020

With the advent of an intelligent information society, research toward artificial intelligence education was conducted. In previous studies, the subject of research is biased, and studies that analyze attitudes toward artificial intelligence are insufficient. So, in this study developed a test tool to measure the artificial intelligence of high school students and analyze their attitudes toward artificial intelligence. To develop the test tool, 229 high school students completed a preliminary test, of which the results were analyzed via exploratory factor analysis. To analyze the students' attitudes toward artificial intelligence, the resulting test tool was applied to 481 high school students, and their test results were analyzed according to factors. From the study's results, there was no difference according to gender in the students' attitudes toward artificial intelligence, but there was a significant difference per grade. In addition, there was a significant difference in attitudes according to artificial intelligence-related experiences: the high school students who had direct and indirect experience with artificial intelligence, programming, and more frequently used it had more positive attitudes toward artificial intelligence than students without this experience. However, artificial intelligence education experience negatively influenced the students' attitudes toward artificial intelligence. Overall, the higher their interest in artificial intelligence, the more positive the high school students' attitudes toward artificial intelligence.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.53-59
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• 2021

The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.1-7
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• 2021

Detect and avoid (DAA) system, which is essential for the operation of UAS, detects intruding aircraft and offers the ranges of turn and climb/descent maneuver that are required to avoid the intruder. This paper uses detect and avoid alerting logic for unmanned systems (DAIDALUS) developed at NASA as a DAA algorithm. Since DAIDALUS offers ranges of avoidance maneuvers, the actual avoidance maneuver must be decided by the UAS pilot as well as the timing and method of returning to the original route. It can be readily used in real-time human-in-the-loop (HiTL) simulations where a human pilot is making the decision, but a pilot decision model is required in fast-time simulations that proceed without human pilot intervention. This paper proposes a pilot decision model that maneuvers the aircraft based on the DAIDALUS avoidance maneuver range. A series of tests were conducted using test vectors from radio technical commission for aeronautics (RTCA) minimum operational performance standards (MOPS). The alert levels differed by the types of encounters, but loss of well clear (LoWC) was avoided. This model will be useful in fast-time simulation of high-volume traffic involving UAS.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.68-77
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• 2021

In this paper, a GPS/MEMS IMU integrated navigation receiver module capable of operating in a high dynamic environment is designed and fabricated, and the results is confirmed. The designed module is composed of RF receiver unit, inertial measurement unit, signal processing unit, correlator, and navigation S/W. The RF receiver performs the functions of low noise amplification, frequency conversion, filtering, and automatic gain control. The inertial measurement unit collects measurement data from a MEMS class IMU applied with a 3-axis gyroscope, accelerometer, and geomagnetic sensor. In addition, it provides an interface to transmit to the navigation S/W. The signal processing unit and the correlator is implemented with FPGA logic to perform filtering and corrrelation value calculation. Navigation S/W is implemented using the internal CPU of the FPGA. The size of the manufactured module is 95.0×85.0×.12.5mm, the weight is 110g, and the navigation accuracy performance within the specification is confirmed in an environment of 1200m/s and acceleration of 10g.