• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.571-576
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• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.19-38
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• 2021

This study empirically analyzed the effect of media literacy on the formation of the smart divide, which is a multi-faceted digital divide that occurs in the context of the use of smart devices. As a result, most of the factors of media literacy affect the establishment of social relations and social network through the use of smart devices, which, in turn, leads to the expansion of the range of informational and social activities. In addition, media literacy has a significant effect on the competence to evaluate the value of information acquired through the use of smart devices. Based on these results, there can be social disparity between those who have secured media literacy and those who do not from the perspective of informational and social benefits through the use of smart devices, which can function as a mechanism to generate the smart divide.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.299-304
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• 2021

Existing human activity recognition systems detect activities through devices such as wearable sensors and cameras. However, these methods require additional devices and costs, especially for cameras, which cause privacy issue. Using WiFi signals that are already installed can solve this problem. In this paper, we propose a CNN-based human activity recognition system using channel state information of WiFi signals, and present results of designing and implementing accelerated hardware structures. The system defined four possible behaviors during studying in indoor environments, and classified the channel state information of WiFi using convolutional neural network (CNN), showing and average accuracy of 91.86%. In addition, for acceleration, we present the results of an accelerated hardware structure design for fully connected layer with the highest computation volume on CNN classifiers. As a result of performance evaluation on FPGA device, it showed 4.28 times faster calculation time than software-based system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.897-906
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• 2022

In this paper, we propose a novel MAC protocol based on the harmonic transmission of ACK, called HAT-LoRa, for improving the reliability and the utilization in multiple gateway LoRa Networks. LoRa is basically vulnerable to collision due to the primitive pure ALOHA-like MAC. Whereas data frame delivery can be guaranteed by the transparent bridge of multiple receiving gateways, ACK is still transmitted by a single gateway in LoRa Network. HAT-LoRa provides the augmented reception opportunity of ACK via the simultaneous transmissions of identical ACK in multiple spreading factors. The proposed method reduces the expected transmission times of ACK double gateway environment as well as single gateway environment, by 55 and 60% in maximum, by 35% and 40% in average, in a single- and double-gateway environment, respectively. Especially, it outperforms under the environment where the distance between end device and gateways are similar to each other.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.111-116
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• 2022

In this study, the applicability of machine learning for the development of a simulator for general X-ray examination education is evaluated. To this end, k-nearest neighbor(kNN), support vector machine(SVM) and neural network(NN) classification models are analyzed to present the most suitable model by analyzing the results. Image data was obtained by taking 100 photos each corresponding to Posterior anterior(PA), Posterior anterior oblique(Obl), Lateral(Lat), Fan lateral(Fan lat). 70% of the acquired 400 image data were used as training sets for learning machine learning models and 30% were used as test sets for evaluation. and prediction model was constructed for right-handed PA, Obl, Lat, Fan lat image classification. Based on the data set, after constructing the classification model using the kNN, SVM, and NN models, each model was compared through an error matrix. As a result of the evaluation, the accuracy of kNN was 0.967 area under curve(AUC) was 0.993, and the accuracy of SVM was 0.992 AUC was 1.000. The accuracy of NN was 0.992 and AUC was 0.999, which was slightly lower in kNN, but all three models recorded high accuracy and AUC. In this study, right-handed PA, Obl, Lat, Fan lat images were classified and predicted using the machine learning classification models, kNN, SVM, and NN models. The prediction showed that SVM and NN were the same at 0.992, and AUC was similar at 1.000 and 0.999, indicating that both models showed high predictive power and were applicable to educational simulators.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.1-6
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• 2022

This paper presents a regionalized time slotted channel hopping (TSCH) slotframe-based aerial data collection using wake-up radio. The proposed scheme aims to minimize the delay and energy consumption when an unmanned aerial vehicle (UAV) collects data from sensor devices in the large-scale service area. To this end, the proposed scheme divides the service area into multiple regions, and determines the TSCH slotframe length for each region according to the number of cells required by sensor devices in each region. Then, it allocates the cells dedicated for data transmission to the TSCH slotframe using the ID of each sensor device. For energy-efficient data collection, the sensor devices use a wake-up radio. Specifically, the sensor devices use a wake-up radio to activate a network interface only in the cells allocated for beacon reception and data transmission. The simulation results showed that the proposed scheme exhibited better performance in terms of delay and energy consumption compared to the existing scheme.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.361-368
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• 2022

The purpose of this study was to develop a hand rehabilitation training system for hemiplegic patients. We also tried to find out five hand postures (WF: Wrist Flexion, WE: Wrist Extension, BG: Ball Grip, HG: Hook Grip, RE: Rest) in real-time using multi-channel EMG-based deep learning. We performed a pre-processing method that converts to Spider Chart image data for the classification of hand movement from five test subjects (total 1,500 data sets) using Convolution Neural Networks (CNN) deep learning with an 8-channel armband. As a result of this study, the recognition accuracy was 92% for WF, 94% for WE, 76% for BG, 82% for HG, and 88% for RE. Also, ten physical therapists participated for the usability evaluation. The questionnaire consisted of 7 items of acceptance, interest, and satisfaction, and the mean and standard deviation were calculated by dividing each into a 5-point scale. As a result, high scores were obtained in immersion and interest in game (4.6±0.43), convenience of the device (4.9±0.30), and satisfaction after treatment (4.1±0.48). On the other hand, Conformity of intention for treatment (3.90±0.49) was relatively low. This is thought to be because the game play may be difficult depending on the degree of spasticity of the hemiplegic patient, and compensation may occur in patient with weakened target muscles. Therefore, it is necessary to develop a rehabilitation program suitable for the degree of disability of the patient.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.133-139
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• 2021

Due to the rapid progress in network technology, many research on content security technologies is also being conducted in the mobile digital content sector. In the meantime, content protection has been immersed in preventing illegal copying, certifying, and issuance/management certificates, but still have many vulnerabilities in managing or authenticating confidential information. This study aims to strengthen confidential information about content based on dual management of content download rights through mobile phone numbers or device numbers. It also protect replay-attack by building a secure mobile DRM system where digital content is safely distributed based on a three-stage user authentication process. In addition, blockchain-based content security enhancements were studied during the primary/secondary process for user authentication for the prevention of piracy and copyright protection. In addition, the client authentication process was further improved through three final stages of authorization in the use of illegal content, considering that legitimate users redistributed their content to third-party.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.57-65
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• 2020

The purpose of this study is to analyze the problem solving ability of occupational therapy students by applying PBL classes using social networks. Data were collected from 35 students in the third year of occupational therapy at K University from March to June 2019. The results were as follows: First, PBL application using social networks showed a significant improvement in problem solving ability. Seconds, there was a significant difference in problem solving ability according to the preference of mobile device use and major satisfaction. Therefore, as a learning tool for improving the problem-solving ability of occupational therapy students, we proposed a way to increase satisfaction with learning by activating PBL using social networks.

• Korean Journal of Optics and Photonics
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• v.33 no.3
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• pp.106-112
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• 2022

A two-dimensional optical code division multiple access (OCDMA) encoder/decoder, which is composed of add/drop filters and all-pass filters for delay operation, is proposed. An example design is presented, and its feasibility is illustrated through numerical simulations. The chip area of the proposed OCDMA encoder/decoder could be about one-third that of a previous OCDMA device employing delay waveguides. Its performance is numerically investigated using the transfer-matrix method combined with the fast Fourier transform. The autocorrelation peak level over the maximum cross-correlation level for incorrect wavelength hopping and spectral phase code combinations is greater than 3 at the center of the correctly decoded pulse, which assures a bit error rate lower than 10^-3, corresponding to the forward error-correction limit.