• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.3-8
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• 2014

We consider a limited feedback based hybrid beamforming which reduces the energy of feedback information. In the millimeter wave channel, some rays with large ray gain dominate energy of the channel. Using this point, we propose a channel feedback scheme that employs limited number of channel rays. Also, we provide a hybrid beamforming scheme for the limited feedback system. Based on the simulation results, the proposed scheme shows a comparable data rate performance with conventional schemes, while it remarkably reduces energy of channel feedback.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.548-551
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• 2003

The adaptive filter is proposed for removing EOG from measured EEG on the frontal lobe. The proposed adaptive filter has been implemented and the feedback output control algorithm has been employed to control the alpha wave ratio on the basis of TMS320C31 DSP board with the on-line and real time performance. The feedback algorithm controls the input voltage of stimulating devices on the portable bio-feedback system. The EEG data are acquired at the $F_{p1}$ and $F_{p2}$ localization and are processed by the proposed adaptive filter. We demonstrated that the proposed adaptive filter could effectively remove EOG from the measured EEG on the frontal lobe and the feedback algorithm is proper to control the output voltage of DSP board using the ratio of the alpha wave.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.54-60
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• 2014

The equipment of SCARA robot in processing and assembly lines has rapidly increased. In order to achieve high productivity and flexibility, it becomes very important to develop the visual feedback control system with Off-Line Programming System(OLPS). We can save much efforts and time in adjusting robots to newly defined workcells by using OLPS. A proposed visual calibration scheme is based on position-based visual feedback. The calibration program firstly generates predicted images of objects in an assumed end-effector position. The process to generate predicted images consists of projection to screen-coordinates, visible range test, and construction of simple silhouette figures. Then, camera images acquired are compared with predicted ones for updating position and orientation data. Computation of error is very simple because the scheme is based on perspective projection, which can be also expanded to experimental results. Computation time can be extremely reduced because the proposed method does not requirethe precise calculation of tree-dimensional object data and image Jacobian.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.90-104
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• 2020

It is difficult for non-experts to build machine learning (ML) models at the level that satisfies their needs. Deep learning models are even more challenging because it is unclear how to improve the model, and a trial-and-error approach is not feasible since training these models are time-consuming. To assist these novice users, we examined how interactive and explainable feedback while training a deep learning network can contribute to model performance and users' satisfaction, focusing on the data preparation process. We conducted a user study with 31 participants without expertise, where they were asked to improve the accuracy of a deep learning model, varying feedback conditions. While no significant performance gain was observed, we identified potential barriers during the process and found that interactive and explainable feedback provide complementary benefits for improving users' understanding of ML. We conclude with implications for designing an interface for building ML models for novice users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.489-497
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• 2009

In the 3GPP LTE and IEEE 802.16m standardizations for IMT-Advanced, the efficient transmission of multicast and broadcast data is one of the important issues to improve system performance. Especially, to guarantee each user's QoS in the multicast group, H-ARQ or adaptive modulation are considered to be adoption, however, reduction of feedback overhead is one of the most important issues. In this paper, performance of the previously proposed OOK (On-Off Keying) based common ACK/NACK feedback channel is analyzed through theoretical analysis and simulation. Based on the results, system parameter optimization methods for common feedback channel are proposed. In addition, through computer simulation, it is shown that the common feedback method according to the proposed feedback parameter optimization can feedback ACK/NACK information for multicast H-ARQ transmission, more reliably than the conventional user dedicated feedback method in 3GPP LTE systems, and can reduce the feedback overhead as well.

• Journal of The Korean Society of Integrative Medicine
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• v.11 no.2
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• pp.207-219
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• 2023

Purpose : This study was conducted to investigate the changes in trunk movement and ground reaction during sit to stand motion using visual feedback. Methods : Fifteen adults (average age: 23.53±1.77 years) participated in this study. An infrared reflective marker was attached to the body each participant for motion analysis, and the participants performed sit to stand motion while wearing a hat attached with a laser pointer, which provided visual feedback. First, the sit to stand action was repeated thrice without obtaining any visual feedback, followed by a three minute break. Next, the laser pointers attached to hats were irradiated on a whiteboard, located at a distance of 5 m in front of the chairs, on which the participants sat; a baseline was set, and the participants performed stand up movements three times under this condition. A visual feedback was provided to the participants to prevent the laser pointers from crossing the set baseline. During each stand-up movement, the position of the reflective marker attached to the subject's body was recorded in real time using an infrared camera for motion analysis. The trunk movement and ground reaction force were extracted through recorded data and analyzed according to the presence or absence of visual feedback. Results : The results indicated that in the presence of a visual feedback during the sit-to-stand movements, the range of motion of the trunk and hip joints decreased, whereas that of the knee and ankle joints increased in the sagittal plane. The rotation angle of the trunk in the horizontal plane decreased. The left and right movement speed of the center of pressure increased, the pressing force decreased, and the forward and backward movement speed of the trunk decreased. Conclusion : The results suggest that the efficiency and stability of the stand up movement of a body increase when a visual feedback is provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3730-3744
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• 2020

This study proposes a deep learning-based evolutionary recommendation model for heterogeneous big data integration, for which collaborative filtering and a neural-network algorithm are employed. The proposed model is used to apply an individual's importance or sensory level to formulate a recommendation using the decision-making feedback. The evolutionary recommendation model is based on the Deep Neural Network (DNN), which is useful for analyzing and evaluating the feedback data among various neural-network algorithms, and the DNN is combined with collaborative filtering. The designed model is used to extract health information from data collected by the Korea National Health and Nutrition Examination Survey, and the collaborative filtering-based recommendation model was compared with the deep learning-based evolutionary recommendation model to evaluate its performance. The RMSE is used to evaluate the performance of the proposed model. According to the comparative analysis, the accuracy of the deep learning-based evolutionary recommendation model is superior to that of the collaborative filtering-based recommendation model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1040-1046
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• 2022

In this paper, we consider a system with massive user equipments (UEs) in a cell and assume path loss and Rayleigh fading channels between the base station (BS) and UEs. In addition, it is assumed that the system bandwidth consists of multiple identical frequency subchannels. Under such assumptions, we propose a channel state information (CSI) feedback scheme and a resource allocation scheme for non-orthogonal multiple access (NOMA) transmission in order to reduce the feedback overhead of CSI generated by massive UEs and to reduce the complexity of resource allocation. In particular, for the proposed schemes, we analyze the sum data rate achievable by massive UEs in a cell and the outage probability with which the UEs in a cell do not meet the target data rate. Through the simulation results, we show that the proposed schemes can provide the superior outage probability, although it degrades the average sum data rate.

• The Journal of Korean Association of Computer Education
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• v.20 no.6
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• pp.1-15
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• 2017

The purpose of this study is to design a LMS(Learning Management System) dashboard for instructor feedback support based on learning analytics and to apply a LMS dashboard incorporating such taxonomy which allows an instructor to give a student personalized feedback according to the class content and a student's traits. In the dashboard design phase, usable instructional data were selected from LMS based on feedback taxonomy in terms of learning analytics. Two validity tests were conducted with 8 instructional technologists over 8 years of experience, and were revised accordingly. The final dashboard screen has three parts: A comprehensive analysis screen to provide appropriate feedback based on instructor feedback taxonomy analysis, a summary screen for learner analysis, and a recommended feedback guide screen. Detailed analysis information are provided through other dashboards that are displayed in eight screens: login analysis, learning information confirmation analysis, teaching materials learning analysis, assignment/tests, and posts analysis. All of these dashboards were represented by analysis information and data based on learner analytics through visualization methods including graphs and tables. The implications of educational utilization of the dashboard for instructor feedback support based on learning analytics and the future researches were suggested based on these results.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.5
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• pp.7-13
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• 1997

A X-band 3-stage monolithic LNA (low noise amplifier) with series feedback has been successfully desined and demonstrated by suign 0.5-$\mu\textrm{m}$ GaAs MESFET. In the design of the 3-stage LNA, the effects of series feedback to the noise figure, the gain, and the stability have been investigated ot find the optimal short stub length. As a result, the inductive series feedback topology which has 10degree short stub in the GaAs MESFET source lead, has been employed in the 1-st stage. The fabricated MMIC LNA's chip size is only 1mm$^{2}$/stage, which is smaller than the previously reported X-band MMIC input/output return losses are less than -10dB and -15dB, respectively. The noise figure (NF) is less than 2.6dB. The measured data show good agreement with the simulated values.