• Journal of the Korean Society of Radiology
• /
• v.17 no.3
• /
• pp.423-431
• /
• 2023

The purpose of this study is to analyze the factors affecting the classification of the severity of contrast media side effects based on the patient's body information using artificial intelligence techniques to be used as basic data to reduce the degree of contrast medium side effects. The data used in this study were 606 examiners who had no contrast medium side effects in the past history survey among 1,235 cases of contrast medium side effects among 58,000 CT scans performed at a general hospital in Seoul. The total data is 606, of which 70% was used as a training set and the remaining 30% was used as a test set for validation. Age, BMI(Body Mass Index), GFR(Glomerular Filtration Rate), BUN(Blood Urea Nitrogen), GGT(Gamma Glutamyl Transgerase), AST(Aspartate Amino Transferase,), and ALT(Alanine Amiono Transferase) features were used as independent variables, and contrast media severity was used as a target variable. AUC(Area under curve), CA(Classification Accuracy), F1, Precision, and Recall were identified through AdaBoost, Tree, Neural network, SVM, and Random foest algorithm. AdaBoost and Random Forest show the highest evaluation index in the classification prediction algorithm. The largest factors in the predictions of all models were GFR, BMI, and GGT. It was found that the difference in the amount of contrast media injected according to renal filtration function and obesity, and the presence or absence of metabolic syndrome affected the severity of contrast medium side effects.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.356-361
• /
• 1998

Neural Networks, modeled succinctly from the real nervous system of a living body, can be categorized into two folds; artificial neural network(ANN) and biological neural network(BNN). While the former has been developed to solve practical problems using function approximation capability, pattern classification) clustering algorithm, etc, the latter has been focused on verifying the information processing capability to which brain research gives an impetus, by mimicking real biological systems. However, BNN suffers Iron severe nonlinearities dealt with. A bridge between two neural networks is chaotic neural network(CNN), which simply delineate the real nor-vous system and comprises almost all the ANN structures by selecting parameters. Main research theme of this area is to develop an explanation tool to clarify the information processing mechanism in biological systems and its extension to engineering applications. The CNN has a Gaussian-shaped refractory function with hysteresis effect and the chaotic responses of it have been observed fur a wide range of parameter space. Through the examination of the coupling effects of excitatory and inhibitory connections, the secrets of information processing and memory structure will appear.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.1
• /
• pp.53-64
• /
• 2009

For a realization of the ubiquitous society, applying IT to vehicle industry has recently been an attractive issue to make wireless communication in body area network possible to everywhere. In this paper, we propose the physical layer symbol structure based on PPM scheme of the IEEE 802.15.4a for the off-body high data rate WBAN system. We propose four symbol structures which is classified according to the number of the chip and whether the channel coding is used or not. We calculate the required SNR through the link budget calculation and the recently proposed off-body WBAN channel environment was applied in the simulation. The results of four systems show that small number of burst's chip enhances the performance and the system is capable to achieve the data rate of 10 Mbps.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.3
• /
• pp.353-359
• /
• 2020

In this study, the controller structure and control algorithm of medical robot bed developed for pressure ulcer prevention and healing are described. The existing pressure ulcer prevention mattress is operated manually and the remaining maximum body pressure exceeds the pressure of ulcer generation, so there is always room for pressure ulcers. However, the system developed in this study does not generate the pressure ulcers because the body pressure drops to zero when the keyboard of the bed descends using the active electric driving keyboard. In addition, even if the bed is raised and the pressure above the critical body ulcer pressure is abnormal, the device and the control algorithm are designed so that the lasting time is within the pressure ulcer generation critical time and the pressure ulcer itself is not generated. The bed key board motor is a motor designed with the BLDC servos suitable for medical use and these can communicate each other easily through CAN(Car Area Network). The system is new medical robot bed that is effective in preventing pressure ulcers and will be distributed to many patients suffering from pressure ulcers.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.6
• /
• pp.809-817
• /
• 2020

In the design and development process of Small-Sat power distribution and transmission module, the stability of dynamic resources was evaluated by a deep learning algorithm. The requirements for the stability evaluation consisted of the power distribution function of the power distribution module and demand module to the SAR radar in Small-Sat. To verify the performance of the switching power components constituting the power module PDM, the reliability was verified using a dynamic neural network. The adoption material of deep learning for reliability verification is the power distribution function of the payload to the power supplied from the small satellite main body. Modeling targets for verifying the performance of this function are output voltage (slew rate control), voltage error, and load power characteristics. First, to this end, the Coefficient Structure area was defined by modeling, and PCB modules were fabricated to compare stability and reliability. Second, Levenberg-Marquare based Two-Way NARX neural network Sigmoid Transfer was used as a deep learning algorithm.

• Journal of Internet Computing and Services
• /
• v.12 no.1
• /
• pp.27-38
• /
• 2011

In this paper, we propose a multiple access scheme using MHP(Modified Hermite Polynomial) pulse and ternary code for high-data and low-data rate for Out-body WBAN(Wireless Body Area Network). To satisfy the requirement of WBAN system, UWB-IR has been considered as a promising candidate for Out-body WBAN. The proposed multiple access scheme, using orthogonal MHP pulse and ternary code sets, reduces multi-user interference and distinguishes user signal from multi-user signals. We propose two algorithms for synchronous and asynchronous WBAN system. The symbol is constructed by MHP pulses and time hopping duration to reduce multi-user interference in the synchronous WBAN system. The symbol also is constructed by ternary code to avoid collision between pulse trains in the asynchronous WBAN system. The results of the proposed multiple access scheme show a clear improvement of BER.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.29 no.2
• /
• pp.35-56
• /
• 2018

This study examines the current state of library related data opened through public data portals, and analyzes how much data is being utilized according to the type of releasing organization, and open level. In addition, we analyzed the subject cluster of data and the centrality of data by performing PathFinder Network analysis using keywords assigned to data by dividing the releasing subject into local government and national/public institutions. Based on this, the subject area of library - related data disclosed by local governments and national/public organizations is understood. And identify the main open body that should be opened first by linking with data utilization analysis result and then suggest implications for future improvement in connection with library big data business.

• Journal of Korea Multimedia Society
• /
• v.19 no.12
• /
• pp.1981-1991
• /
• 2016

In recent, the advancement of wearable devices and wireless body area networking technologies motivate researchers to pay attention to remote healthcare system for monitoring patients health and disease progression effectively. However, in order to implement a practical remote healthcare system, we must consider the security and privacy of patient's personal health information transmitted to healthcare servers through the network. Hence, in this paper, we propose a secure health data transmission protocol in remote healthcare monitoring system to protect patient's health information and prevent privacy from eavesdropping on the network. To achieve our security goals, we design an efficient secure protocol based on the identity-based cryptography with key evolution technique, and then confirm the superiority and the efficiency of the proposed protocol as compared with the existing protocol of Yang et al.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.4
• /
• pp.23-29
• /
• 2012

Injured peoples usually care their body at medical institutions. But if they need some more rehabilitation to the affected area thus exist. These medical institutions according to the scale there are significant differences in rehabilitation programs, most of the small-scale rehabilitation program for medical doctors and patients to be progression of the conversation is an issue. In this paper, in a small medical facility rehabilitation to assist in the accuracy and reliability, physical contact and force sensors that can measure a combination of substitution and the tactile sensor and tactile sensor alternative with a similar function is proposed. Perceptron neural networks by applying the contact evaluation according to the algorithm to determine the pattern is applied.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.19 no.6
• /
• pp.37-45
• /
• 2011

As vehicles become more intelligent, in-vehicle networking (IVN) systems such as controller area network (CAN) or FlexRay are essential for convenience and safety of drivers. To expand the applicability of IVN systems, attention is currently being focused on the communication between heterogeneous networks such as body networking and chassis networking systems. A gateway based on message mapping method was developed to interconnect FlexRay and CAN networks. However, this type of gateways has the following shortcomings. First, when a message ID was changed, the gateway must be reloaded with a new mapping table reflecting the change. Second, if the number of messages to be transferred between two networks increase, software complexity of gateway increases very rapidly. In order to overcome these disadvantages, this paper presents FlexRay-CAN gateway based on node mapping method. More specifically, this paper presents a node mapping based FlexRay-CAN gateway operation algorithm along with the experimental evaluation for ID change.