• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6034-6056
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• 2018

This paper describes two user studies in remote collaboration between two users with a video conferencing system where a remote user can draw annotations on the live video of the local user's workspace. In these two studies, the local user had the control of the view when sharing the first-person view, but our interfaces provided instant control of the shared view to the remote users. The first study investigates methods for assisting drawing annotations. The auto-freeze method, a novel solution for drawing annotations, is compared to a prior solution (manual freeze method) and a baseline (non-freeze) condition. Results show that both local and remote users preferred the auto-freeze method, which is easy to use and allows users to quickly draw annotations. The manual-freeze method supported precise drawing, but was less preferred because of the need for manual input. The second study explores visual notification for better local user awareness. We propose two designs: the red-box and both-freeze notifications, and compare these to the baseline, no notification condition. Users preferred the less obtrusive red-box notification that improved awareness of when annotations were made by remote users, and had a significantly lower level of interruption compared to the both-freeze condition.

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.285-292
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• 2000

A new method for the 3D automatic registration of the multiple range images has been developed for the 3D scanners(non-contact coordinates measurement systems). In the existing methods, the user usually has to input more than 3 pairs of corresponding points for the iterative registration process. The major difficulty of the existing systems lies in that the input corresponding points must be selected very carefully because the optimal searching process and the registration results mostly depend upon the accuracy of the selected points. In the proposed method, this kind of difficulty is greatly mitigated even though it needs only 2 pairs of the corresponding input points. Several registration examples on the 3D measured data have been presented and discussed with the introduction to the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.675-683
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• 1996

CAC, UPC, NPC, cell level QoS and congestion control is required to assign efficiently channels's BW and to prevent networks from congestion. In the CAC algorithm, each user defines characteristics of input traffic when channels are set up and network based on this parameters determines the acception or rejection of the required BW. The CAC control mechanism is classified into the centralized BW allocation mechanism and the distributed BW Allocation mechanism according to the function and position of CAC processor allocating BW. In this paper, in contrast with esisted the distributed BW allocation mechanism which assumes the required BW of input traffic as constant, we assume input traffic & serices as bulk probability distribution in order to analyze performance more precisely.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.378-386
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• 1999

The integrated system for the structural analysis of space frame is made up 4 modules ; pre-process module, structural analysis module, optimum member design module and post-process module. Re-process module of these 4 modules involves data input module and structure modeling module. This study is to develope an efficient modeling program as a basic for development of pre-process module. This modeling program generates geometric information of space frame and performs the input fie form for structure analysis only by input general data. User can mode1 space frame efficiently within shut time by using this program.

• Journal of Electrical Engineering and Technology
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• v.2 no.1
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• pp.29-34
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• 2007

The input and output impedances in a low voltage distribution system is one of the most important matters for power line communication because from the viewpoint of communication, the attenuation characteristic of the high frequency signals is greatly caused by impedance mismatch during sending and receiving. The frequency range is from 1MHz to 30MHz. Therefore, this paper investigates the input and output impedances in order to understand the characteristic of high frequency signals in the low voltage distribution system between a pole transformer and an end user. For power line communication, the model of Korea's low voltage distribution system is proposed in a residential area and then the low voltage distribution system is set up in a laboratory. In the low voltage distribution system, S parameters are measured by using a network analyzer. Finally, input and output impedances are calculated using S parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of the Korea Computer Graphics Society
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• v.28 no.2
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• pp.29-41
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• 2022

In this paper, we introduce a novel real-time, interactive animation system which uses real-time motion inputs from a low-cost motion-sensing device Kinect. Our system generates interaction motions between the user character and the counterpart character in real-time. While the motion of the user character is generated mimicking the user's input motion, the other character's motion is decided to react to the user avatar's motion. During a pre-processing step, our system analyzes the reference motion data and generates mapping model in advance. At run-time, our system first generates initial poses of two characters and then modifies them so that it could provide plausible interacting behavior. Our experimental results show plausible interacting animations in that the user character performs a modified motion of user input and the counterpart character properly reacts against the user character. The proposed method will be useful for developing real-time interactive animation systems which provide a better immersive experience for users.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.507-512
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• 2005

There is a limitation of using a small number of input buttons for writing Hangul words on hand-held devices. As a quick and convenient way of implementing Hangul vowels by small number of buttons, we propose a vowel input system in which vowels are fabricated from eight vowels. Our input system supports a fast input speed by making all the diphthong from one or two strokes. It also adopts a multiple input method for diphthong that users can make a diphthong in a user-friendly way of vowel writing formation or pronunciation similarity. Furthermore, we added an error correction functionality for the similar vowels that are caused by vowel harmony rules. When the proposed method is compared to the previous ones, our method outperformed in the input speed and error correction.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.98-99
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• 2004

• Water Engineering Research
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• v.1 no.2
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• pp.137-146
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• 2000

A windows-based software package, named DREDGE, is developed for estimating sediment resuspension and contaminant release during dredging operations. DREDGE allows user to enter the necessary dredge information, site characteristics, operational data, and contaminant characteristics, then calculates an array of concentration using the given values. The program mainly consists of the near-field models, which are obtained empirically, for estimating sediment resuspension and the far-field models, which are obtained analytically, for suspended sediment transport. A linear equilibrium partitioning approach is applied to estimate particulate and dissolved contaminant concentrations. This software package which requires only a minimal amount of data consists of three components; user input, tabular output, and graphical output. Combining the near-field and far-field models into a user-friendly windows-based computer program can greatly save dredge operator's, planners', and regulators' efforts for estimating sediment transports and contaminant distribution.