• International journal of advanced smart convergence
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• v.12 no.2
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• pp.56-66
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• 2023

The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.649-652
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• 2009

Now Broadcasting system of TV has been developed from analogue to digital we call that IPTV(Internet Protocol Television) or DCATV(Digital Cable Television). But, The characteristics of digital broadcasting is the high-quality contents of easily and almost no damage piracy, and Copyright loss is increasing by Internet, P2P(Peer to Peer) and personal path. Nevertheless user's permissions that recorded and reuse of broadcasting can't restraint, And Training Materials etc. use of fair program needs to be separated from illegality. In this paper using a digital certificate permit the use of stored program to authorized user and user of fair purpose, And illegal distribution of restriction design and implement a distribution system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.137-144
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• 2010

Cyber lectures have been popular with students as they are more accessible. In this thesis we also created a personal identification confirmation system with RFID as it is quite difficult to confirm who is taking a lecture. In the process of developing the confirmation system, an algorithm enabling real-time identification confirmation, as well as interactive virtual questioning system, was also developed. After the computer simulation test we proved the duplex on-line lecturing system is more effective than the current one-way cyber lecturing system which does not take into consideration students with less/no degree of understanding.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.3
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• pp.9-14
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• 2008

In this paper, we propose the channel sounding scheme which is made for ideal communication between some application as well as the short distance of high speed data transmission in MIMO-OFDM system for Wireless PAN. This method is able to perceive the duration of the impulse response through the delaying of power delay profile, modeled a power delay profile which has an attenuate characteristic, and obtained the coefficient of channel response by ML (maximum likelihood). Through the amplitudes, phases and delays associated with each multipath component which were acquired from this channel sounding scheme, we can describe the wave propagation characteristics of channels between the transmitter and receiver so that the receiver could enhance not only the reliability but also the ability of communication link.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.113-118
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• 2011

This paper has analyzed recognizing performance depending on the size of iris codes extracting by iris recognition algorithm using scale-space filtering. The iris images were created through pre-processing, the features were extracted by scale-space filtering, and the codes of 16 sizes were generated. The generated code's performance was compared for each code to calculate FAR and FRR by matching method utilizing Hamming distance. Every code had little overlapping portion between same person and other persons group so that the proposed algorithm's superiority was proved, and the performance of iris codes was analyzed for each size focused on convenience to use when implementing in realization. In addition, the iris codes suitable to iris recognition system that is high-reliable and is able to reduce user's inconvenience due to mis-rejection has been presented considering for commercialization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.133-139
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• 2014

Nowadays, telemedicine and remote prescription has been operating as a pilot basis. However, in case of remote hospitals without encrypting the biometric data transmission and its contents, the patient prescription data hacked from hackers who changed prescription medications can be serious obstacles to the patient. Therefore, in this paper, to solve this problem, password encryption, personal identification information, biometric data security on the patient's prescription and remote medical information system, and implementation of the encryption algorithm are proposed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.6
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• pp.1-7
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• 2008

In this paper, we introduce a new technology to extract the unique features from an iris image, which uses scale-space filtering. Resulting iris code can be used to develop a system for rapid and automatic human identification with high reliability and confidence levels. First, an iris part is separated from the whole image and the radius and center of the iris are evaluated. Next, the regions that have a high possibility of being noise are discriminated and the features presented in the highly detailed pattern are then extracted. In order to conserve the original signal while minimizing the effect of noise, scale-space filtering is applied. Experiments are performed using a set of 272 iris images taken from 18 persons. Test results show that the iris feature patterns of different persons are clearly discriminated from those of the same person.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.93-100
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• 2018

The electronic acupuncture has the advantage of treating the patient with acupuncture by simultaneously analyzing the patient's physical condition and treatment condition. In this paper, it is proposed and developed an electronic acupuncture algorithm embedded in a multi pad. Especially, it is implemented the control algorithm using the optimal electronic dipstick calculation, sensing pad and DSP system for the patient's body condition. Moreover, in this paper, it is developed SW and HW prototypes that can receive personal information by patient and can receive multi-array type electronc needle guiding procedure based on WEB.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.55-60
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• 2020

Adaptive recommendation systems have been developed with big data processing as a system that provides services tailored to users based on user information and usage patterns. Deep learning can be used in these adaptive recommendation systems to handle big data, providing more efficient user-friendly recommendation services. In this paper, we propose a system that uses deep learning to categorize and recommend tourism types to suit the user's personality. The system was divided into three layers according to its core role to increase efficiency and facilitate maintenance. Each layer consists of the Service Provisioning Layer that real users encounter, the Recommendation Service Layer, which provides recommended services based on user information entered, and the Adaptive Definition Layer, which learns the types of tourism suitable for personality types. The proposed system is highly scalable because it provides services using deep learning, and the adaptive recommendation system connects the user's personality type and tourism type to deliver the data to the user in a flexible manner.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.255-264
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• 2016

Due to the development of information and communication technology, the great change on economics has grown and the biggest change is the e-commerce. With the methods of electronic financial frauds becoming advanced, reported phishing incidents have greatly increased. The Fraud Detection System(hereafter FDS) has taken effect to prevent electronic financial frauds, but economic losses still occurring. This Paper aims to analyze the financial environment, financial information technology environment, financial information technology security environment and some features of the institutional changes. In order to supplement the defect of FDS, it gives some recommendations for the improvement of the effective FDS Management System and information sharing on frauds with some public institution and a major consideration for collection or utilization of personal information.