• Journal of Digital Convergence
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• v.19 no.11
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• pp.351-357
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• 2021

IoT devices, which are used in various ways in distributed environments, are becoming more important in data transmitted and received from IoT devices as fields of use such as medical, environment, transportation, bio, and public places are diversified. In this paper, as a method to ensure the reliability of IoT data, an autoencoder-based IoT-linked processing technique is proposed to classify and process numerous data by various important attributes. The proposed technique uses correlation indices for each IoT data so that IoT data is grouped and processed by blockchain by characteristics for IoT linkage processing based on autoencoder. The proposed technique expands and operates into a blockchain-based n-layer structure applied to the correlation index to ensure the reliability of IoT data. In addition, the proposed technique can not only select IoT data by applying weights to IoT collection data according to the correlation index of IoT data, but also reduce the cost of verifying the integrity of IoT data in real time. The proposed technique maintains the processing cost of IoT data so that IoT data can be expanded to an n-layer structure.

• 한국가시화정보학회:학술대회논문집
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• 2002.04a
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• pp.51-78
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• 2002

A number of research groups worldwide are studying electronic implants that can be mounted on retinal optic nerve/visual cortex to restore vision of patients suffering from retinal degeneration. The implants consist of a neural interface made of biocompatible materials, one or more integrated circuits for stimuli generation, a camera, an image processor, and a telemetric channel. The realization of these classes of neural prosthetic devices is largely due to the explosive development of micro- and nano-electronics technologies in the late $20^{th}$ century and biotechnologies more recently. Animal experiments showed promise and some human experiments are in progress to indicate that recognition of images can be obtained and improved over time. We, at NBS-ERC of SNU, have started our own retinal implant project in 2000. We have selected polyimide as the biomaterial for an epi-retinal stimulator. In-vitro and in-vivo biocompatibility studies have been performed on the electrode arrays. We have obtained good affinity to retinal pigment epithelial cells and no harmful effect. The implant also showed very good stability and safety in rabbit eye for 12 weeks. We have also demonstrated that through proper stimulation of inner retina, meaning vision can be obtained.

• Journal of radiological science and technology
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• v.38 no.4
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• pp.451-461
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• 2015

In megavoltage (MV) radiotherapy, delivering the dose to the target volume is important while protecting the surrounding normal tissue. The purpose of this study was to evaluate the modulation transfer function (MTF), the noise power spectrum (NPS), and the detective quantum efficiency (DQE) using an edge block in megavoltage X-ray imaging (MVI). We used an edge block, which consists of tungsten with dimensions of 19 (thickness) ${\times}$ 10 (length) ${\times}$ 1 (width) $cm^3$ and measured the pre-sampling MTF at 6 MV energy. Various radiation therapy (RT) devices such as TrueBeam$^{TM}$ (Varian), BEAMVIEW$^{PLUS}$ (Siemens), iViewGT (Elekta) and Clinac$^{(R)}$iX (Varian) were used. As for MTF results, TrueBeam$^{TM}$(Varian) flattening filter free(FFF) showed the highest values of $0.46mm^{-1}$ and $1.40mm^{-1}$ for MTF 0.5 and 0.1. In NPS, iViewGT (Elekta) showed the lowest noise distribution. In DQE, iViewGT (Elekta) showed the best efficiency at a peak DQE and $1mm^{-1}DQE$ of 0.0026 and 0.00014, respectively. This study could be used not only for traditional QA imaging but also for quantitative MTF, NPS, and DQE measurement for development of an electronic portal imaging device (EPID).

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.3-12
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• 2015

Recently, various studies have been attempted to provide a biological information monitoring service through integrating with the web service. The medical information transmission standard ISO/IEEE 11073 PHD defines the optimized exchange protocol ISO/IEEE 11073-20601 based on the No-IP to exchange the biometric information between the ISO/IEEE 11073 agent and the manager. It's system structure based on the No-IP using ISO/IEEE 11073-20601 is not suitable for providing a remote biological information monitoring services. That is because it is difficult to provide to control and manage the biological information measurement devices, which have installed IP protocol stack at the remote. Furthermore, ACSE and CMDISE in ISO/IEEE 11073-20601 are not suitable to provide U-healthcare services based on IoT because they are complicated and difficult to implement it caused by the structural complexity. In order to solve the problems, in this paper, we propose the biological information monitoring architecture based on ISO/IEEE 11073 DIM/REST of IoT environment to provide the biological information monitoring service based on IoT. To do this, we designed biological information monitoring system architecture based on IoT and the message exchange protocol of ISO/IEEE 11073 DIM/REST between the ISO/IEEE 11073 agent and the ISO/IEEE 11073 manager. In order to verify the realistic possibility of the proposed system architecture, we developed the service prototype.

• Journal of radiological science and technology
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• v.39 no.1
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• pp.99-105
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• 2016

The noise power spectrum (NPS) is one of the most general methods for measuring the noise amplitude and the quality of an image acquired from a uniform radiation field. The purpose of this study was to compare different NPS methodologies by using megavoltage X-ray energies. The NPS evaluation methods in diagnostic radiation were applied to therapy using the International Electro-technical Commission standard (IEC 62220-1). Various radiation therapy (RT) devices such as TrueBeam$^{TM}$(Varian), BEAMVIEW$^{PLUS}$(Siemens), iViewGT(Elekta) and Clinac$^R$ iX (Varian) were used. In order to measure the region of interest (ROI) of the NPS, we used the following four factors: the overlapping impact, the non-overlapping impact, the flatness and penumbra. As for NPS results, iViewGT(Elekta) had the higher amplitude of noise, compared to BEAMVIEW$^{PLUS}$ (Siemens), TrueBeam$^{TM}$(Varian) flattening filter, Clinac$^{R}$iXaS1000(Varian) and TrueBeam$^{TM}$(Varian) flattening filter free. The present study revealed that various factors could be employed to produce megavoltage imaging (MVI) of the NPS and as a baseline standard for NPS methodologies control in MVI.

• Journal of radiological science and technology
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• v.35 no.2
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• pp.119-124
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• 2012

Recently, Glass Dosimeter (GD) with thermoluminescent Dosimeter (TLD) are comprehensively used to measure absorbed dose from diagnostic field to therapy field that means from low energy field to high energy field. However, such studies about dose characteristics of GD, such as reproducibility and energy dependency, are mostly results in high energy field. Because characteristic study for measurement devices of radiation dose and radiation detector is performed using 137Cs and 60Co which emit high energy radiations. Thus, this study was evaluated the linearity according to Piranha dose which measured by changing tube voltage (50kV, 80kV and 100kV which are low energy radiations), reproducibility and reproducibility according to delay time using GD. Measurement of radiation dose is performed using internal detector of Piranha 657 which is multi-function QA device (RTI Electronic, Sweden). Condition of measurement was 25mA, 0.02sec, 2.5mAs, SSD of 100 cm and exposure area with $10{\times}10cm^2$. As above method, GD was exposed to radiation. Sixty GDs were divided into three groups (50kV, 80kV, 100kV), then measured. In this study, GD was indicated the linearity in low energy field as high energy existing reported results. The reproducibility and reproducibility according to delay time were acceptable. In this study, we could know that GD can be used to not only measure the high energy field but also low energy field.