• Journal of Information Management
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• v.36 no.1
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• pp.125-154
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• 2005

Due to the development of Internet and the collection and usage of the individual information, the infringements of the personal data have been increased rapidly. Regarding the personal data protection in the medical industry, it is clearly described in 'Act on Promotion of Information and Communication Network Utilization and information Protection, etc.'. the law is ratified on the basis of the service provider, therefore, it has its own limitation to be applied to medical industry. Therefore, this paper is to set the security standard and to discuss the range of legal application and considerations on its basis for the domestic medical institution at the electronic medical record system. We exemplify specific applicable content of the electronic signature in the electronic medical record also, present a security assessment item in electronic medical system and set the criteria for the security standard in the medical industry.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.8-16
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• 2019

Customized sleep care service needs to be provided differently for individuals since individual has different degree of sleep disorder. Because the brainwave data shows unique waveform characteristics for each person, this characteristic can be used to identify individuals. Personal identification provides an important role in enabling customized services. When you blink, you can obtain brain wave characteristics by measuring the area of the frontal lobe. Therefore, a real-time personal identification algorithm based on blinking EOG for customized sleep care service is proposed in this paper. For evaluation, 10 individuals were tested for personal identification accuracy. The results of the experiment confirmed that a maximum accuracy of 93% were taken. Algorithms can be developed by reflecting characteristics such as changes in the external environment in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.153-162
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• 2009

When a private information security incident occurs, the people who own the information are not acknowledged about their information leakage until those affairs appear in public media. This research aims at developing a mobile alarm system for acknowledging suspicious events to the information owners. The mobile alarm system was designed considering the limited user interface of mobile terminal and concept of "personal information leakage message tree" is deployed. The message tree contains every possible situation about personal information leakage and the leaves of the tree has several choices that the information owner can select. This message tree concept enables each information owner to manager his or her information leakage situation by just pushing a few buttons of mobile device. The contribution of this paper is in design of a comprehensive alarm message tree and development of mobile alarm system containing the message tree concept.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1724-1729
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• 1991

This paper gives an overview of HIGIPS design concepts and prototype HIGIPS configuration, and discusses its application to recognition of the 3-D motion of a human arm. HIGIPS which employs the combination of pipeline architecture and multiprocessor architecture, is a high-speed, high-performance and low cost N * M multimicroprocessor parallel machine, where N is the number of pipeline stages and M is the number of processors in each stage. The algorithm to recognize the motion of a human arm with a single TV camera was developed on personal computer (NEC PC9801 series). As a constraint condition, some simple ring marks are used. Each joint of the arm is attached with a ring mark to obtain its centroid position when the arm moves. These centroid positions in the three-dimensional space are linked at each of the successive pictures of the moving arm to recover its overall motion. This algorithm takes about 2 seconds to process one image frame on the general-purpose personal computer. This paper mainly discuses how to partition this algorithm and execute on HIGIPS, and shows the speed up. From this application, it is clear that HIGIPS is an efficient machine for image processing and recognizing.

• Management & Information Systems Review
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• v.2
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• pp.311-334
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• 1998

By decreasing in CPU price and development of computer assembling technology, personal computer fake a good chance to accelerate its supply. Recently, as being introduced new computing technology so called multi media, teaming assist system which is based on single media such as studying book, cassette tape, video tape, or something else is rapidly being replaced by new assist education system based on multi media in which it is operated by the personal computer. In the computer assist education system, there is an evaluation module which appraise learner's study level into the next study strategy. At the view of this point, this part is very important. In this part, there are some factors like Importance, complexity, or difficulty which commonly include fuzzy factors in our surrounding. But until now, we are still out of the level to handle the evaluation module adequately among the some studies. In this study, we would like to suggest a new module that evaluate learning achievement of ICAI which have a variety of fuzzy environment. We combine Independent fuzzy environment like importance, complexity, difficulty into making total evaluation of learner's achievement. By the result, with expressing by linguistic form, this study can provide the theoretical basis in which we will be able to carry out sentence toward evaluation among elementary school.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.560-574
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• 2011

In this paper, we propose a hybrid method of Machine Learning (ML) algorithm and a rule-based algorithm to implement a lightweight Named Entity (NE) extraction system for Korean SMS text. NE extraction from Korean SMS text is a challenging theme due to the resource limitation on a mobile phone, corruptions in input text, need for extension to include personal information stored in a mobile phone, and sparsity of training data. The proposed hybrid method retaining the advantages of statistical ML and rule-based algorithms provides fully-automated procedures for the combination of ML approaches and their correction rules using a threshold-based soft decision function. The proposed method is applied to Korean SMS texts to extract person's names as well as location names which are key information in personal appointment management system. Our proposed system achieved 80.53% in F-measure in this domain, superior to those of the conventional ML approaches.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.81-88
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• 2023

In the present scenario, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In Perturbation, datasets are perturbed in order to preserve personal information. Both data accuracy and data privacy are addressed by it. This paper will explore and compare several perturbation strategies that may be used to protect data privacy. For this experiment, two perturbation techniques based on random projection and principal component analysis were used. These techniques include Improved Random Projection Perturbation (IRPP) and Enhanced Principal Component Analysis based Technique (EPCAT). The Naive Bayes classification algorithm is used for data mining approaches. These methods are employed to assess the precision, run time, and accuracy of the experimental results. The best perturbation method in the Nave-Bayes classification is determined to be a random projection-based technique (IRPP) for both the cardiovascular and hypothyroid datasets.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.425-430
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• 1986

This paper introduces the program to develop graphics-oriented, interactive, computer-aided design modules for machine elements which are developing in Mechanical Engineering Department of The Ohio State University in U.S.A. The CAD modules are developed to be efficiently performed within the arena of minicomputer- and personal computer-based computer-aided design. In addition, this paepr deals with the state-of-the-art in computer-aided design.

• 한국기계연구소 소보
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• s.16
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• pp.53-61
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• 1986

This paper introduces the program to develop graphics-oriented, interactive, computer-aided design modules for machine elements which are developing in both of CAD/CAM Lab., Numerical Control Department of KIMM in Korea and Mechanical Engineering Department of the Ohio State University in U.S.A. The CAD modules are developed to be efficiently performed within the arena of minicomputer-and personal computer-based computer-aided design. In addition, this paper deals with the state-of-the-art in computer-aided design.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2217-2220
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• 2003

It is known that an EEG is characterized by the unique and personal characteristics of an individual. Little research has been done to take into account these personal characteristics when analyzing EEG signals. Often the EEG has frequency components which can describe most of the significant characteristics. These combinations are often unique like individual human beings and yet they have an underlying basic characteristics as well. We think that these combinations are the personal characteristics frequency components of the EEG. In this seminar, the EEG analysis method by using the Genetic Algorithms (GA), Factor Analysis (FA), and the Neural Networks (NN) is proposed. The GA is used for selecting the personal characteristic frequency components. The FA is used for extracting the characteristics data of the EEG. The NN is used for estimating the characteristics data of the EEG. Finally, in order to show the effectiveness of the proposed method, classifying the EEG pattern is carried out via computer simulations. The EEG pattern is evaluated under 4 conditions: listening to Rock music, Schmaltzy Japanese ballad music, Healing music, and Classical music. The results, when personal characteristics frequency components are NOT used, gave over 80 % accuracy versus a 95 % accuracy when personal characteristics frequency components are used. This result of our experiment shows the effectiveness of the proposed method.