• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.181-186
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• 2019

In order to reduce the fossil fuels consumed in conventional commercial independent diesel generators in the same environment as the island area, it is necessary to develop a photovoltaic system that will bear more than 40% of the independent system capacity. For this development, it is necessary to develop a high-capacity inverter that can improve the stability of the independent system installed in the island area and supply high-quality power to the load. In addition, the EMS power generation control system for the independent grid photovoltaic power generation system is a parallel operation power control system of the diesel generator connected with the solar power generation system. It controls the output of the diesel generator according to the load ratio and the solar power generation, A stable supply system is needed. This independent grid photovoltaic generation system can increase the solar power supply to the independent system area and increase the power stability of the independent system and further reduce the use of fossil fuel due to the ineffective power control of the independent system. It is expected that the economy will be secured early.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.401-406
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• 2021

Recently, mean-teacher models based on convolutional recurrent neural networks are popularly used in audio event detection. The mean-teacher model is an architecture that consists of two parallel CRNNs and it is possible to train them effectively on the weakly-labelled and unlabeled audio data by using the consistency learning metric at the output of the two neural networks. In this study, we tried to improve the performance of the mean-teacher model by using additional derivative features of the log-mel spectrum. In the audio event detection experiments using the training and test data from the Task 4 of the DCASE 2018/2019 Challenges, we could obtain maximally a 8.1% relative decrease in the ER(Error Rate) in the mean-teacher model using proposed derivative features.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1145-1154
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• 2018

In order to prevent interference and interference of the frequency, it is required to convert the regulatory standard into the center of the radiation power radiated to the actual public. Since the radiation power regulation is related to general radio management such as technical standards, permits, and inspections, it is gradually introduced in consideration of applicability and urgency, and the radiation power related laws of major countries And a method of controlling the output of the radio equipment such as measurement, inspection, and authentication. In Korea, the proportion of antenna power supply is high, and in Europe, radiation power is high. Since the number of radio stations will increase and diversify in the future, institutional improvement should be made so that it can be measured in parallel with the radiocommunication infrastructure of the space manager. In order to convert to the radiative power management system, the system for the related radio system needs(Technical standards, certification, inspection of radio stations, post-management, etc.) to be improved.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.467-474
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• 2019

In this paper, we studied a method for a broadband stacked patch antenna structure which is widely used for bandwidth improvement. The characteristics according to the distance between the two patches were analyzed and the impedance matching was optimized by connecting parallel open stubs to the main patch feed line. The shunt matching stub is inserted underneath the parasitic patch and so it does not require additional space, which enables the proposed antenna structure to be advantageous in miniaturizing antenna. The effects of the various parameters on the antenna performance are examined, and we introduced the design procedure for the proposed antenna to operate in the frequency range of 2.3~2.7GHz. Experimental results show that the bandwidth of the proposed antenna is about 480MHz with 2.27~2.75GHz bandwidth. And the antenna gain was 5.8dBi at 2.3GHz and 7.8dBi at 2.6GHz within the bandwidth.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.247-252
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• 2019

The diffraction properties of optical signals by multi-layered periodic structures is formulated in two-dimensional space by using Fourier expansions associated with basic grating profile. The fields in each layer are then expressed in terms of characteristic modes, and the complete solution is found rigorously by using a modal transmission-line theory(MTLT) to address the pertinent boundary-value problems. Such an approach can treat periodic arbitrary gratings containing arbitrarily shaped dielectric components, which may generally have optical properties along directions that are parallel or perpendicular to the multi-layers. This paper illustrates the present approach by comparing our numerical results with data reported in the past for simple periodic circular 2D structures. In addition, this proposed theory can apply easily for more complex configurations, which include multiple periodic regions with several possible canonic shapes and high dielectric constants.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.117-126
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• 2019

The data generated in the IoT environment is very diverse. Especially, the development of the fourth industrial revolution has made it possible to increase the number of fixed and unstructured data generated in manufacturing facilities such as Smart Factory. With Big Data related solutions, it is possible to collect, store, process, analyze and visualize various large volumes of data quickly and accurately. Therefore, in this paper, we will directly generate data using Raspberry Pi used in IoT environment, and analyze using various Big Data solutions. Collected by using an Sqoop solution collected and stored in the database to the HDFS, and the process is to process the data by using the solutions available Hive parallel processing is associated with Hadoop. Finally, the analysis and visualization of the processed data via the R programming will be used universally to end verification.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.417-424
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• 2019

This paper presents the design of a JPEG-LS codec for lossless image compression from AR/VR device. The proposed JPEG-LS(: LosSless) codec is mainly composed of a context modeling block, a context update block, a pixel prediction block, a prediction error coding block, a data packetizer block, and a memory block. All operations are organized in a fully pipelined architecture for real time image processing and the LOCO-I compression algorithm using improved 2D approach to compliant with the SBT coding. Compared with a similar study in JPEG-LS, the Block-RAM size of proposed STB-FLC architecture is reduced to 1/3 compact and the parallel design of the predication block could improved the processing speed.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.229-237
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• 2021

Among the elderly and patients with mild brain diseases (such as dementia and stroke), when there is a certain degree of self-acting ability and cognitive ability, exercise and cognitive rehabilitation are often required. However, since most of the existing rehabilitation systems are separated or specialized in exercise or cognitive rehabilitation, there is a need for a form linking both. In this paper, we propose a game-type rehabilitation system that enables both exercise and cognitive rehabilitation using CAN communication protocol, one of ICT technologies. This system uses the CAN BUS structure to separate and combine each individual module constituting the rehabilitation system in various forms. A prototype of the proposed system was actually produced to show that various types of rehabilitation environments can be implemented according to the degree of cognitive ability and motor ability of the patient (or the elderly). In addition, through several experiments using this system, it is possible to implement exercise/cognitive parallel rehabilitation applicable to various environments.

• Journal of Hospice and Palliative Care
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• v.24 no.2
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• pp.130-134
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• 2021

In the era of coronavirus disease 2019 (COVID-19), social distancing and strict visitation policies at hospitals have made it difficult for medical staff to provide high-quality end-of-life (EOL) care to dying patients and their families. There are various issues related to EOL care, including psychological problems of patients and their families, difficulties in EOL decision-making, the complicated grief of the bereaved family, moral distress, and exhaustion of medical staff. In relation to these issues, we aimed to discuss practical considerations in providing high-quality EOL care in the COVID-19 pandemic. First, medical staff should discuss advance care planning as early as possible and use the parallel planning strategy. Second, medical staff should play a role in facilitating patient-family communication. Third, medical staff should actively and proactively evaluate and alleviate dying patients' symptoms using non-verbal communication. Lastly, medical staff should provide care for family members of the dying patient, who may be particularly vulnerable to post-bereavement problems in the COVID-19 era. Establishing a system of screening high-risk individuals for complicated grief and connecting them to bereavement support services might be considered. Despite the challenging and limited environment, providing EOL care is essential for patients to die with dignity in peace and for the remaining family to return to life after the loved one's death. Efforts considering the practical issues faced by all medical staff and healthcare institutions caring for dying patients should be made.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.57-62
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• 2021

As the parallel computing capability for artificial intelligence improves, the field of artificial intelligence technology is expanding in various industries. In particular, artificial intelligence is being introduced to process data generated from IoT sensors that have enoumous data. However, the limitation exists when applying the AI techniques on IoT network because IoT has time series data, where the importance of data changes over time. In this paper, we propose time-weighted and user-state based artificial intelligence processing techniques to effectively process IoT sensor data. This technique aims to effectively classify IoT sensor data through a data pre-processing process that personalizes time series data and places a weight on the time series data before artificial intelligence learning and use status of personal data. Based on the research, it is possible to propose a method of applying artificial intelligence learning in various fields.