• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.456-462
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• 2011

As the ARRA enacted recently in the United States, the interest in EHR systems have been increased in the field of medical industry. The passage of the ARRA presents a program that provides incentives to office-based physicians and hospitals adapting the EHR systems to guarantee interoperability with various medical standards. Thanks to the incentive program, a great number of EHR systems have been developed and lots of office-based physicians and hospitals have adapted the EHR systems certified by CCHIT. Keeping pace with the rapid changes in the market of healthcare, some enterprises try to push in to the United States healthcare market based on the experience acquired by developing EHR systems for hospitals in Korea. However, the developed system must be customized because of the different medical environment between Korea and the United States. In this paper, therefore, we design and develop an integrated EHR platform to guarantee the interoperability between different medical information systems based on medical standard technologies. In the developed platform, an integrated system has been composed by integrating various basic techniques such as data transmission standards and its methods, medical standard terminologies and its usage, and knowledge management for medical decision-making support. Moreover, medical data can be processed electronically by adapting an HL7 interface engine and the terminologies for exchanging medical information and the standardization of medical information. We develop SeniCare, an EHR system for supporting ambulatory care of the office-based physicians, based on the platform, and we verify the usability of the platform by confirming whether SeniCare satisfies the criteria of "meaningful use" issued by CMS or not.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.35-46
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• 2017

Recently, attackers using malicious code in cyber security have been increased by attaching malicious code to a mail and inducing the user to execute it. Especially, it is dangerous because it is easy to execute by attaching a document type file. The author analysis is a research area that is being studied in NLP (Neutral Language Process) and text mining, and it studies methods of analyzing authors by analyzing text sentences, texts, and documents in a specific language. In case of attack mail, it is created by the attacker. Therefore, by analyzing the contents of the mail and the attached document file and identifying the corresponding author, it is possible to discover more distinctive features from the normal mail and improve the detection accuracy. In this pager, we proposed IADA2(Intelligent Attack mail Detection based on Authorship Analysis) model for attack mail detection. The feature vector that can classify and detect attack mail from the features used in the existing machine learning based spam detection model and the features used in the author analysis of the document and the IADA2 detection model. We have improved the detection models of attack mails by simply detecting term features and extracted features that reflect the sequence characteristics of words by applying n-grams. Result of experiment show that the proposed method improves performance according to feature combinations, feature selection techniques, and appropriate models.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.495-501
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• 2015

Abroad warships are confronted with various menaces. The most critical threat of the warship is an Anti-Ship Missile (ASM). The ASM is able to be launched at a variety of environments and platforms. The ASM can evades conventional naval radar systems and electronic countermeasure techniques for providing a fatal damage to the warship. To cope with the ASM, an active decoy is an effective method to minimize the direct damage to the warship. The active decoy increases survivability of the warship because the ASM can lure pursuit of the active decoy instead of the warship. In this paper, our proposed method verifies an available response time of the active decoy to deal with the ASM using the active decoy of the warship in marine environments. We defined models of the warship, the ASM, and the active decoy, and executed simulation by combining the models. By the simulation result, the proposed method demonstrated the superiority of the mobile active decoy of the response time decoy among various active decoys, and estimated a protection area to prevent the ASM according the response time of the mobile active decoy against the ASM.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.11-23
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• 2011

The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.59-73
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• 2003

As a means of overcoming the linguistic barrier between different languages in the Internet, a new sign-language communication system with CG animation techniques has been developed and proposed. In the system, the joint angles of the arms and the hands corresponding to the gesture as a non-verbal communication tool have been considered. The emotional expression, however, could as play also an important role in communicating each other. Especially, a comic expression is more efficient than real facial expression, and the movements of the cheeks and the jaws are more important AU's than those of the eyebrow, eye, mouth etc. Therefore, in this paper, we designed a 3D emotion editor using 2D model, and we extract AU's (called as PAU, here) which play a principal function in expressing emotions. We also proposed a method of generating the universal emotional expression with Avatar models which have different vertex structures. Here, we employed a method of dynamically adjusting the AU movements according to emotional intensities. The proposed system is implemented with Visual C＋＋ and Open Inventor on windows platforms. Experimental results show a possibility that the system could be used as a non-verbal communication means to overcome the linguistic barrier.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.47-65
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• 2014

VMS(Variable Message Sign) helps drivers to choose their path to destinations on roadways. Some types of VMS often provide traffic information with clearly visible and comprehensible graphical route diagrams. Currently many diagramed types of VMS are installed on urban arterial and highways. This type of VMS surely enhances drivers' ability to comprehend traffic route information while they are driving on the roadway. Nevertheless, some of them are presented with so much information and design elements and they sometimes lead to decline of drivers' comprehensible level for traffic information. Drivers would fail to decide their preferable route in this state of information overflow. The purpose of this paper is to develop a drivers preference model for effective design principle including size and height of displaying font, and the amount of information in the route diagram considering driving speed, sex and age of the driver. This model is developed using structural equation modeling techniques. This model considers driver's emotional factor and, human factor and design component of route diagram. To collect data, we built driving simulator which is able to replicate real driving condition. 72 people who participated in the simulation were selected considering gender and age. The developed model showed that the amount of information, and visibility are more influential factors to the drivers' preference of the route diagram on VMS than design elements such as the shape and the font of the diagram.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.90-100
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• 2017

The purpose of this study is to detect and label the vehicles using the drone images as a way to overcome the limitation of the existing point and section detection system and vehicle gap estimation on Arterial road. In order to select the appropriate time zone, position, and altitude for the acquisition of the drone image data, the final image data was acquired by shooting under various conditions. The vehicle was detected by applying mixed Gaussian, image binarization and morphology among various image analysis techniques, and the vehicle was labeled by applying Kalman filter. As a result of the labeling rate analysis, it was confirmed that the vehicle labeling rate is 65% by detecting 185 out of 285 vehicles. The gap was calculated by pixel unitization, and the results were verified through comparison and analysis with Daum maps. As a result, the gap error was less than 5m and the mean error was 1.67m with the preceding vehicle and 1.1m with the following vehicle. The gaps estimated in this study can be used as the density of the urban roads and the criteria for judging the service level.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.126-132
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• 2015

Technology forecasting is about understanding a status of a specific technology in the future, based on the current data of the technology. It is useful when planning technology management strategies. These days, it is common for countries, companies, and researchers to establish R&D directions and strategies by utilizing experts' opinions. However, this qualitative method of technology forecasting is costly and time consuming since it requires to collect a variety of opinions and analysis from many experts. In order to deal with these limitations, quantitative method of technology forecasting is being studied to secure objective forecast result and help R&D decision making process. This paper suggests a methodology of technology forecasting based on quantitative analysis. The methodology consists of data collection, principal component analysis, and technology forecasting by logistic regression, which is one of the data mining techniques. In this research, patent documents related to autonomous vehicle are collected. Then, the texts from patent documents are extracted by text mining technique to construct an appropriate form for analysis. After principal component analysis, logistic regression is performed by using principal component score. On the basis of this result, it is possible to analyze R&D development situation and technology forecasting.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.456-462
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• 2008

The classification is that a new data is classified into one of given classes and is one of the most generally used data mining techniques. Memory-Based Reasoning (MBR) is a reasoning method for classification problem. MBR simply keeps many patterns which are represented by original vector form of features in memory without rules for reasoning, and uses a distance function to classify a test pattern. If training patterns grows in MBR, as well as size of memory great the calculation amount for reasoning much have. NGE, FPA, and RPA methods are well-known MBR algorithms, which are proven to show satisfactory performance, but those have serious problems for memory usage and lengthy computation. In this paper, we propose DPA (Dynamic Partition Averaging) algorithm. it chooses partition points by calculating GINI-Index in the entire pattern space, and partitions the entire pattern space dynamically. If classes that are included to a partition are unique, it generates a representative pattern from partition, unless partitions relevant partitions repeatedly by same method. The proposed method has been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory and FPA, and RPA.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.155-175
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• 2003

In context of e-commerce, negotiation is a procedure to help negotiate between buyer and seller by adjusting their negotiation issues such as price and in terms of payment. We used intelligent agent and mobile device to promote new framework of e-commerce. Moreover, this framework can help buyers and sellers to carry their commercial transactions effectively. In regard to that issue, we need to carry out the research of negotiation agent that can be used in e-commerce fields. In this paper, we modeled the negotiation using CSP for the performance of agent in m-commerce environment. Furthermore we implemented interface for mobile device to extract buyer's requirement and preference easily Besides that we used utility function to make a decision for various evaluation functions and suggestions that are used for evaluation of negotiation issues. A difficulty of generating offer is dependent on the number of negotiation issues and the range of the values. Therefore, if any offer has a number of negotiation issues and the range of values are wide, the search space will be exponentially expanded. There have been many studies fur solving this problem, we applied those techniques to improve the agent's ability of negotiation. For example, a contract can be accomplished by exchanging seller and buyer's offer that is generated by agent to adjust the requisite profit for each party. Finally, we show the improvement of satisfaction as the negotiation is processed.