• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.6
• /
• pp.165-171
• /
• 2022

Human heart rate can be used to measure exercise intensity as an important indicator. If heart rate can be predicted, exercise can be performed more efficiently by regulating the intensity of exercise in advance. In this paper, a FitRec-based prediction model is proposed for estimating running heart rate for users. Endomondo data is utilized for training the proposed prediction model. The processing algorithms for time-series data, such as LSTM(long short term memory) and GRU(gated recurrent unit), are employed to compare their performance. On the basis of simulation results, it was demonstrated that the proposed model trained with running exercise performed better than the model trained with several cardiac exercises.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.12
• /
• pp.1786-1793
• /
• 2022

Cyber-attacks such as smishing and hacking mail exploiting COVID-19, political and social issues, have recently been continuous. Machine learning and deep learning technology research are conducted to prevent any damage due to cyber-attacks inducing malicious links to breach personal data. It has been concluded as a lack of basis to judge the attacks to be malicious in previous studies since the features of data set were excessively simple. In this paper, nine main features of three types, "URL Days", "URL Word", and "URL Abnormal", were proposed in addition to lexical features of URL which have been reflected in previous research. F1-Score and accuracy index were measured through four different types of machine learning algorithms. An improvement of 0.9% in a result and the highest value, 98.5%, were examined in F1-Score and accuracy through comparatively analyzing an existing research. These outcomes proved the main features contribute to elevating the values in both accuracy and performance.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.549-555
• /
• 2023

Jacking force loss management inside the PSC Box girder of a common high-speed railway is a very important feature in girder performance, and requires detailed management during the maintenance of the girder. This study aimed to analyze the timing of re-tension prediction of PSC Box girder based on the reduction level of the packing force inside the girder and the results of the tension loss measured without the train load test. As a result of predicting the timing of re-tension according to the level of tension reduction of the PSC Box Girder, the Jacking Force Loss curve was gently analyzed before the structure reached 17 years after confirmed completion, and 17 years later, it was found that the jacking force loss curve progressed rapidly. The results confirmed that the tension of the structure decreases with the service life increase, but considerably decreases as the structure ages. Therefore, more data and research on tension loss of facilities over 20 years are much required.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.393-399
• /
• 2023

Upper limb amputees wear an upper limb prosthesis for both aesthetic purposes and functional necessity, and in particular, in the case of amputee with both hands, it is essential to wear a myoelectric prosthetic hand capable of gripping action. The prosthetic hand operated by the EMG signal of the remaining muscles is a public insurance benefit item of the Industrial Accident Compensation Insurance, and test method standards are needed to be developed for the safety of the user and the effectiveness of the product performance. In this study, we developed systems for measuring the gripping force of myoelectric hand prosthesis by a load cell and for durability test of the prosthesis over repeated use with a proximity sensor, and propose a test method standard. Since the international test method standard has not yet been established, it is expected that Korea will be able to play a leading role in this standardization field in the future.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.677-682
• /
• 2023

A large number of motors and sensors are used to drive a humanoid robot. In order to solve the wiring problem that occurs when connecting multiple actuators, a controller based on a communication network has been used, and CAN, which is advantageous in terms of cost and a highly reliable communication protocol, was mainly used. In terms of the structure of the controller, a torque control type structure that is easy to implement an advanced algorithm into the upper controller is preferred. In this case, the low communication bandwidth of CAN becomes a problem, and in order to obtain sufficient communication bandwidth, a communication network is configured by separating into a plurality of CAN networks. In this study, a stability analysis on transmission time delay is performed for a multi-motor control system in which high-speed FlexRay and low-speed CAN communication networks are hierarchically connected in order to obtain a high communication bandwidth, and sensor information and driving signals are delivered within the allowed transmission time. The proposed hierarchical network-based control system is expected to improve control performance because it can implement multiple motor control systems with a single network.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.701-706
• /
• 2023

The Korean government and industry have presented a roadmap for the commercialization of UAM services and are promoting it in earnest. In order to introduce full-scale UAM services, there are various issues to be solved, such as the development of high-performance aircraft, the design of network bases and corridors, the optimization of operation management, and the establishment of related laws and systems. In this study, in terms of optimizing operation management, we will examine research trends by field, focusing on Korea, and derive research topics that need to be solved in the future. Korean researchers have suggested that research is centered on UAM service usage fees, usage intentions and acceptance models, and vertiport location selection, but operational optimization studies such as service order acceptance, aircraft repositioning, and battery charging and maintenance scheduling are needed in the future.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.2
• /
• pp.319-325
• /
• 2023

This study investigates the impact of over-investment on the market value of cash holdings. In addition, this paper examines whether the effect of over-investment on the value of cash holdings differs depending on firms' ownership structure. The results show that increase in over-investment reduces the market value of cash holdings. This suggests that investors perceive that over-investment deteriorates future business performance and generates excessive burdens on future cash flows. As a result, they provide negative evaluation on the market value of cash holdings. In addition, the negative impact of over-investment on the market value of cash holdings is more significant for owner manager firms where managers hold a high level of equity. Such empirical results imply that owner manager firms are more likely to use their cash holdings for private interest, therefore, over-investment reduces the cash value to a greater extent. This study provides empirical evidence that the effect of over-investment on the market value of cash holdings varies depending on the characteristics of firms' ownership structure.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.4
• /
• pp.65-73
• /
• 2023

In this paper, we propose a data augmentation method based on CNN(Convolutional Neural Network) learning for efficiently obtaining concrete crack image datasets. Real concrete crack images are not only difficult to obtain due to their unstructured shape and complex patterns, but also may be exposed to dangerous situations when acquiring data. In this paper, we solve the problem of collecting datasets exposed to such situations efficiently in terms of cost and time by using vector and thickness-based data augmentation techniques. To demonstrate the effectiveness of the proposed method, experiments were conducted in various scenes using U-Net-based crack detection, and the performance was improved in all scenes when measured by IoU accuracy. When the concrete crack data was not augmented, the percentage of incorrect predictions was about 25%, but when the data was augmented by our method, the percentage of incorrect predictions was reduced to 3%.

• Geomechanics and Engineering
• /
• v.31 no.4
• /
• pp.339-352
• /
• 2022

Studying slope stability is an important branch of civil engineering. In this way, engineers have employed machine learning models, due to their high efficiency in complex calculations. This paper examines the robustness of various novel optimization schemes, namely equilibrium optimizer (EO), Harris hawks optimization (HHO), water cycle algorithm (WCA), biogeography-based optimization (BBO), dragonfly algorithm (DA), grey wolf optimization (GWO), and teaching learning-based optimization (TLBO) for enhancing the performance of adaptive neuro-fuzzy inference system (ANFIS) in slope stability prediction. The hybrid models estimate the factor of safety (F_S) of a cohesive soil-footing system. The role of these algorithms lies in finding the optimal parameters of the membership function in the fuzzy system. By examining the convergence proceeding of the proposed hybrids, the best population sizes are selected, and the corresponding results are compared to the typical ANFIS. Accuracy assessments via root mean square error, mean absolute error, mean absolute percentage error, and Pearson correlation coefficient showed that all models can reliably understand and reproduce the F_S behavior. Moreover, applying the WCA, EO, GWO, and TLBO resulted in reducing both learning and prediction error of the ANFIS. Also, an efficiency comparison demonstrated the WCA-ANFIS as the most accurate hybrid, while the GWO-ANFIS was the fastest promising model. Overall, the findings of this research professed the suitability of improved intelligent models for practical slope stability evaluations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.05a
• /
• pp.151-151
• /
• 2023

An accurate prediction of the hydrodynamic maneuvering darivatives is essential to desing a robust control system of a UUV(unmanned underwater vehicle). Typically, these derivatives were estimated by either the towing tank experiment or semi-empirical methods. With the enhancement of high performance computing capacity, a numerical analysis using computational fluid dynamics has reach the level of experiment. Therefore, the aims of the present research are to numerically develop a computational model for the vertical planar motion mechanism of a UUV and to estimate the hydrodynamics loads in 6-DOF. The target structure of the present study was manta type UUV (12meter length). The numerical model was developed in 1/ 6 model scale. Numerical results were compared with the results of the towing tank experiment for validation. In the present study, a commercial RANS-based viscous solver STARCCM+ (ver 17.06) was used.