• Journal of Korean Association for Spatial Structures
• /
• v.11 no.3
• /
• pp.95-103
• /
• 2011

Among structural systems for complex-shaped tall buildings, diagrid system is widely used because of its structural efficiency and beauty of form. Recently, mega frame is favorably employed as a suitable structural system for skyscrapers because this structural system has sufficient stiffness against the lateral forces by combination of mega members which consist of many columns and girders. Diagrid mega frame system is expected to be promising structural system for future super tall buildings. However, it takes tremendous analysis times and engineer's efforts to predict the structural behavior of tall buildings applied with diagrid mega frame system because the diagrid mega frame structure has significant numbers of elements and nodes. Therefore, efficient analytical method for all buildings applied with diagrid mega frame system has been proposed in this study to reduce the efforts and time required for the analysis and design of diagrid mega frame structure. To this end, an efficient modelling technique using the characteristics of diagrid mega frame structures and an efficient analytical model using minimal DOFs by the matrix condensation method were proposed in this study. Based on the analysis of an example structure, the effectiveness and accuracy of the proposed method have been verified by the comparison between the results of the proposed method and the conventional method.

• Science of Emotion and Sensibility
• /
• v.14 no.4
• /
• pp.627-636
• /
• 2011

The purpose of this study is to develop the multi-modal interaction system. This system provides realistic and an immersive experience through multi-modal interaction. The system recognizes user behavior, intention, and attention, which overcomes the limitations of uni-modal interaction. The multi-modal interaction system is based upon gesture interaction methods, intuitive gesture interaction and attention evaluation technology. The gesture interaction methods were based on the sensors that were selected to analyze the accuracy of the 3-D gesture recognition technology using meta-analysis. The elements of intuitive gesture interaction were reflected through the results of experiments. The attention evaluation technology was developed by the physiological signal analysis. This system is divided into 3 modules; a motion cognitive system, an eye gaze detecting system, and a bio-reaction sensing system. The first module is the motion cognitive system which uses the accelerator sensor and flexible sensors to recognize hand and finger movements of the user. The second module is an eye gaze detecting system that detects pupil movements and reactions. The final module consists of a bio-reaction sensing system or attention evaluating system which tracks cardiovascular and skin temperature reactions. This study will be used for the development of realistic digital entertainment technology.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.1
• /
• pp.82-96
• /
• 2024

While analyzing traffic flow, speed, traffic volume, and density are important macroscopic indicators, and acceleration and spacing are the important microscopic indicators. The speed and traffic volume can be collected with the currently installed traffic information collection devices. However, acceleration and spacing data are necessary for safety and autonomous driving but cannot be collected using the current traffic information collection devices. 'You Look Only Once'(YOLO), an object recognition technique, has excellent accuracy and real-time performance and is used in various fields, including the transportation field. In this study, to measure acceleration and spacing using YOLO, we developed a model that measures acceleration and spacing through changes in vehicle speed at each interval and the differences in the travel time between vehicles by setting the measurement intervals closely. It was confirmed that the range of acceleration and spacing is different depending on the traffic characteristics of each point, and a comparative analysis was performed according to the reference distance and screen angle to secure the measurement rate. The measurement interval was 20m, and the closer the angle was to a right angle, the higher the measurement rate. These results will contribute to the analysis of safety by intersection and the domestic vehicle behavior model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.3
• /
• pp.622-628
• /
• 2016

As the suction pad-supporting bike carrier attached to a car may be subject to an excessive dynamic load due to random vibrations and centrifugal forces during driving, its structural safety is of great concern. To examine this, the finite-element method with a fluid-structure interaction should be used because the pressure on the pad bottom is changed in real time according to the fluctuations of the force or the moment applied on the pad. This method, however, has high computing costs in terms of modeling efforts and software expense. Moreover, the accuracy of computation is not easily guaranteed. Therefore, a new method combining the experiment and computation is proposed in this paper: the bottom pressure and contact area of the pad under varying loads was measured in real time and the acquired data are then used in the nonlinear elastic finite-element calculations. The computational and experimental results obtained with the product under development showed that the safety margin of the pad under the axial loading is relatively sufficient, whereas with an excessive rotational loading, the pad is vulnerable to separation or a local surface damage; hence, the safety margin may not be secured. The predicted contact behavior under the variation of the magnitude and type of the loading were in good agreement with the one from the experiment. The proposed analysis method in this study could be used in the design of similar vacuum pad systems.

• Journal of Music and Human Behavior
• /
• v.1 no.1
• /
• pp.47-71
• /
• 2004

Students with learning disability have difficulty with attention and academic achievement Music can be an effective tool to enhance level of participation. The purpose of this study is to examine how much can be structured to enhance the attention span and related academic skills needed to achieve educational goals. The study has implemented structured music therapy sessions for three middle school students with learning disability. They participated in 20 sessions which were 30 minutes in length for ten weeks. The implemented music therapy sessions were designed using songs, playing, and listening to music. In order to test their level of attention, Frankfurter Aufmerksamkeits-Inventar(FAIR) Attention Test is implemented and Conners' Comprehensive Teacher's Rating Scale(CTRS-10) are used on the week before and after music activities. Also videotaping is used so as to analyze how correctly they do their task and how the correctness is changed period by period and to evaluate how often for ten minutes they make an eye contact with their teacher. The conclusions of this study are as follows: Firstly, the organized music activities have a positive affection on improving the attention of three middle school students who have learning disabilities. Fair Attention Test shows that they can do their task with more accuracy than in the previous period. Secondly, three students of this study improved their attention and made an eye contact more often than before this study, which is revealed through the analysis of the pre and post test results evaluated by CTRS-10. The results of the study indicate that structured use of music in various level of activities can help students to enhance attention span and the related academic skills.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.12
• /
• pp.491-498
• /
• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.2B
• /
• pp.279-288
• /
• 2004

Rapidly emerging P2P(Peer to Peer) applications generate very bursty traffic, which gives a lot of burden to network, and the amount of such traffic is increasing rapidly. Thus it is becoming more important to understand the characteristics of such traffic and reflect it when we design and analyze the network. To do that we measured the traffic in a campus network and present flow statistics and traffic models of the measured traffic, and compare them with those of the web traffic. The results indicate that P2P traffic is much burstier than web traffic and as a result it negatively affects network performance. We modeled P2P traffic using self-similar traffic model to predict packet delay and loss occurred in network which are very important to evaluate network performance. We also predict queue length distribution and loss probability in SSQ(Single Sewer Queue). To assess accuracy of traffic model, we compare the SSQ statistics of traffic models with that of the traffic trace. The results show that self-similar traffic models we use can predict P2P traffic behavior in network precisely. It is expected that the traffic models we derived can be used when we design network capacity and predict network performance and QoS of the P2P applications.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.35 no.6
• /
• pp.375-380
• /
• 2022

High-speed railway bridges carry a risk of dynamic response amplification due to resonance caused by train loads, and running safety and riding comfort must therefore be reviewed through dynamic analysis in accordance with design codes. The running safety and ride comfort calculation procedure, however, is time consuming and expensive because dynamic analyses must be performed for every 10 km/h interval up to 110% of the design speed, including the critical speed for each train type. In this paper, a deep-learning-based prediction system that can predict the running safety and ride comfort in advance is proposed. The system does not use dynamic analysis but employs a deep learning algorithm. The proposed system is based on a neural network trained on the dynamic analysis results of each train and speed of the railway bridge and can predict the running safety and ride comfort according to input parameters such as train speed and bridge characteristics. To confirm the performance of the proposed system, running safety and riding comfort are predicted for a single span, straight simple beam bridge. Our results confirm that the deck vertical displacement and deck vertical acceleration for calculating running safety and riding comfort can be predicted with high accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.2
• /
• pp.193-202
• /
• 2018

This paper proposed a crack spacing calculation formulation which is an important parameter for calculating the crack width, that is the main factor for verification of serviceability limit states and durability performance evaluation of reinforced concrete members. The basic equation of average crack spacing is derived by considering the bond characteristics which is the governing equation for the analysis of cracking behavior in reinforced concrete members. In order to consider the effect of the cover thickness and concrete compressive strength, the crack spacing measured in 124 direct tensile tests performed by several researchers was analyzed and each coefficient was proposed. And, correlation analysis was performed from 80 specimen data where the maximum and average crack spacing were simultaneously measured, and a correlation coefficient that can easily predict the maximum crack spacing from the average crack spacing was proposed. The results of the proposed average crack spacing equation and maximum crack spacing correlation were compared with those current design code specification. The comparisons of proposed equations and the Korean design codes show that the proposed formulation for the average crack spacing and the maximum crack spacing improves the accuracy and reliability of prediction compared to the corresponding provisions of the Korean Concrete Structural Design Code and Korean Highway Bridge Design Code (Limit States Design).

• Journal of Korean Society of Transportation
• /
• v.21 no.3
• /
• pp.15-22
• /
• 2003

In general, the linear regression model has been used to estimate trip generation in the travel demand forecasting procedure. However, the model suffers from several methodological limitations. First, trips as a dependent variable with non-negative integer show discrete distribution but the model assumes that the dependent variable is continuously distributed between -$\infty$ and +$\infty$. Second, the model may produce negative estimates. Third, even if estimated trips are within the valid range, the model offers only forecasted trips without discrete probability distribution of them. To overcome these limitations, a poisson model with a assumption of equidispersion has frequently been used to analyze count data such as trip frequencies. However, if the variance of data is greater than the mean. the poisson model tends to underestimate errors, resulting in unreliable estimates. Using overdispersion test, this study proved that the poisson model is not appropriate and by using Vuong test, zero inflated negative binomial model is optimal. Model reliability was checked by likelihood test and the accuracy of model by Theil inequality coefficient as well. Finally, marginal effect of the change of socio-demographic characteristics of households on trips was analyzed.