• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.82-89
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• 2016

And by entering into an aging society with economic growth "beautiful and healthy desire to live', aesthetics industry as promote interest in 'Anti-aging' is emerging as a promising business increased significantly the skin care market. However, the management of the hospital or the temporal order to receive professional care providers, spatial, and cost constraints caused many companies to solve this problem began to approach the Home Care Area. Global trends in personal skin care market has been activated, the domestic has been activated at low cost, private market due to the recession. We have performed this test in order to develop a skin care device for home in order to compensate for this point.In this paper, we develop a low-level laser to create a personal skin care products and sought to incorporate them into the skin cosmetic.Expand the pores by using the low-level laser to the skin by to the dermal layer of the skin was penetrated aim experiment the ampoule, and by a comparison of the medical low-level laser reliability and determine the effectiveness or absence of the performance and efforts to commercialize.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.404-412
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• 2011

More recently, variety RFID (Radio Frequency Identification) readers are produced by RFID equipment manufactures. Although a transmission standard instituted by EPCglobal is proposed for data transmission between the RFID readers and tags, other RFID reader protocols and the communication connection methods are be in use in other RFID companies. To replace or add the RFID readers of an RFID system, the developers should make changes to the core of the application and/or middleware. In this paper, we propose an RFID reader framework which can manage RFID readers without having to make changes the code of the application in environment with the growing number of heterogeneous RFID readers.This framework that sits on the layer between the RFID readers and the applications provides transparency to the RFID readers. Additionally, it can be used for monitoring the state and the property of all connected RFID, and for recording the RFID tag event logs and system logs. By using this framework, heterogeneous readers can be replaced and added without writing additional code in the applications. Consequently the readers can be easily managed and controlled by the RFID system administrator.

• Smart Media Journal
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• v.6 no.2
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• pp.42-49
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• 2017

It is important to realize automation services by communicating in IoT with humans, objects & objects, and forming a common network. People used web like the most powerful network way to sharing things and communication. Therefore the efficiency method communication between each device and the web in IoT could be different from ones. The best method for high quality software product in web applications is software reuse ; Modules, classes, patterns, frameworks, and business components are reusable elements of various perspectives. Components is plugged with others through well-defined interfaces, which can overcome the operation and complexity of application development. A web-based distributed environment for IoT applications is a standard architecture use information collected from various devices for developing and using applications. For that reason, the network management which manages the constituent resources for the best service control in IoT application is required as a sub-layer support service in most applications as well as individual applications. In this paper, we measure to develop a network management system based not only by components but on heterogeneous internetworks. For procedure this, we clarify a component architecture for classifying and classify also the component needed in the IOT and network domain or order the type of real network management system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.366-372
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• 2019

In this paper, we fabricated a capacitive humidity sensor with an IDT(Interdigitated) electrode using commercial polyimide containing fluorine, and its properties were measured and analyzed. First, in order to analyze the composition of commercial polyimide, EDS analysis was performed after patterning process on a silicon wafer. The area of the humidity sensor was $1.56{\times}1.66mm^2$, and the width of the electrode and the gap between the electrodes were $3{\mu}m$ each. The number of electrodes was 166 and the length of the electrode was 1.294mm for the sensitivity of the sensor. The fabricated sensor showed that the sensitivity was 24 fF/%RH, linearity <${\pm}2.5%RH$ and hysteresis <${\pm}4%RH$. As a result of measuring the capacitance value according to the frequency change, the capacitance vlaue decreased with increasing frequency. Capacitance deviations with 10kHz and 100kHz were measured as 0.3pF on average.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.336-342
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• 2019

With the entry of an aging society, the average life span of accreditation has been extended. Therefore, interest in the appearance of men and women in modern society has increased. It is the wrinkles of the face that can judge the most outwardly. People tend to have various kinds of treatments to have a clean, wrinkle-free and resilient healthy skin regardless of sex. There is a lot of practice of lifting procedures in one of the procedures. A suture using a melting thread is a method of lifting by squeezing it into the skin as a non-incision type centering on a region where the thread can be fixed in the skin by injecting it into the subcutaneous fat layer. To evaluate the lifting efficacy of Cog - type suture for the improvement of skin wrinkles, preclinical experiments were conducted. We developed a wrinkle evaluation program using Labview. Data from preclinical experiments were used at 8 weeks after suturing. The average wrinkle depth was 415.6 mm in the control group. At 8 weeks, the depth of wrinkles was deepened to 888.3mm due to the aging process of the control group. On the other hand, the depth of the wrinkles before surgery was 640.3 mm in the suture group. It was confirmed that the depth of wrinkles decreased to 566.5mm at 8th week after the suture operation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.467-474
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• 2019

In this paper, we propose a novel method to improve FPS while maintaining the accuracy of YOLO v2 model in NVIDIA Jetson TX1. In general, in order to reduce the amount of computation, a conversion to an integer operation or reducing the depth of a network have been used. However, the accuracy of recognition can be deteriorated. So, we use methods to reduce computation and memory consumption through adjustment of the filter size and integrated computation of the network The first method is to replace the $3{\times}3$ filter with a $1{\times}1$ filter, which reduces the number of parameters to one-ninth. The second method is to reduce the amount of computation through CBR (Convolution-Add Bias-Relu) among the inference acceleration functions of TensorRT, and the last method is to reduce memory consumption by integrating repeated layers using TensorRT. For the simulation results, although the accuracy is decreased by 1% compared to the existing YOLO v2 model, the FPS has been improved from the existing 3.9 FPS to 11 FPS.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.443-450
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• 2021

After selecting a PES substrate with excellent thermal stability and optical properties among plastic substrates, a SiO₂ thin film was deposited as a buffer layer to a thickness of 20nm by plasma-enhanced chemical vapor deposition to compensate for the high moisture absorption. Then, the ITZO thin film was deposited by a RF magnetron sputtering method to investigate electrical and optical properties according to RF power. The ITZO thin film deposited at 50W showed the best electrical properties such as a resistivity of 8.02×10^-4 Ω-cm and a sheet resistance of 50.13Ω/sq.. The average transmittance of the ITZO thin film in the visible light region(400-800nm) was relatively high as 80% or more when the RF power was 40 and 50W. Figure of Merits (Φ_TC and FOM) showed the largest values of 23.90×10^-4 Ω^-1 and 5883 Ω^-1cm^-1, respectively, in the ITZO thin film deposited at 50W.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1095-1100
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• 2021

In this study, ITZO thin films were deposited on glass, sapphire, and PEN substrates by RF magnetron sputtering, and their electrical and optical properties were investigated. The resistivity of the ITZO thin film deposited on the glass and sapphire substrates was 3.08×10-4 and 3.21×10-4 Ω-cm, respectively, showing no significant difference, whereas the resistivity of the ITZO thin film deposited on the PEN substrate was 7.36×10-4 Ω-cm, which was a rather large value. Regardless of the type of substrate, there was no significant difference in the average transmittance of the ITZO thin film. Figure of Merits of the ITZO thin film deposited on the glass substrate obtained using the average transmittance in the absorption region of the amorphous silicon thin film solar cell and the absorption region of the P3HT : PCBM organic active layer were 10.52 and 9.28×10-3 Ω-1, respectively, which showed the best values. Through XRD and AFM measurements, it was confirmed that all ITZO thin films exhibited an amorphous structure and had no defects such as pinholes or cracks, regardless of the substrate type.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.343-350
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• 2022

It is worth verifying the effectiveness of data integration between data with different features. This study investigated whether the data integration affects the accuracy of deep neural network (DNN), and which integration method shows the best improvement. This study used two different public datasets. One public dataset was taken in an actual farm in India. And another was taken in a laboratory environment in Korea. Leaf images were selected from two different public datasets to have five classes which includes normal and four different types of plant diseases. DNN used pre-trained VGG16 as a feature extractor and multi-layer perceptron as a classifier. Data were integrated into three different ways to be used for the training process. DNN was trained in a supervised manner via the integrated data. The trained DNN was evaluated by using a test dataset taken in an actual farm. DNN shows the best accuracy for the test dataset when DNN was first trained by images taken in the laboratory environment and then trained by images taken in the actual farm. The results show that data integration between plant images taken in a different environment helps improve the performance of deep neural networks. And the results also confirmed that independent use of plant images taken in different environments during the training process is more effective in improving the performance of DNN.