• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.853-862
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• 2003

Many more use e-mail purely on a personal basis and the pool of e-mail users is growing daily. Also, the amount of mails, which are transmitted in electronic commerce, is getting more and more. Because of its convenience, a mass of spam mails is flooding everyday. And yet automated techniques for learning to filter e-mail have yet to significantly affect the e-mail market. This paper suggests Web Mail Filtering Agent for Personalized Classification, which automatically manages mails adjusting to the user. It is based on web mail, which can be logged in any time, any place and has no limitation in any system. In case new mails are received, it first makes some personal rules in use of the result of observation ; and based on the personal rules, it automatically classifies the mails into categories according to the contents of mails and saves the classified mails in the relevant folders or deletes the unnecessary mails and spam mails. And, we applied Bayesian Algorithm using Dynamic Threshold for our system's accuracy.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.2
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• pp.131-136
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• 2011

The furrow calculation and traffic measurement of sailing ship using computer vision are useful methods to prevent maritime accident by predicting the possibility of an accident occurrence in advance. In this paper, sailing ships are recognized using image erosion, differential operator and minimax value, which can be verified directly because the calculated coordinates are displayed on electronic navigation chart. The developed algorithm based on area information of this paper has the advantage which is compared to the conventional radar system focused on point information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.714-720
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• 2021

The ITL (information theoretic learning) based on the kernel density estimation method that has successfully been applied to machine learning and signal processing applications has a drawback of severe sensitiveness in choosing proper kernel sizes. For the maximization of correntropy criterion (MCC) as one of the ITL-type criteria, several methods of adapting the remaining kernel size ( ) after removing the term have been studied. In this paper, it is shown that the main cause of sensitivity in choosing the kernel size derives from the term and that the adaptive adjustment of in the remaining terms leads to approach the absolute value of error, which prevents the weight adjustment from continuing. Thus, it is proposed that choosing an appropriate constant as the kernel size for the remaining terms is more effective. In addition, the experiment results when compared to the conventional algorithm show that the proposed method enhances learning performance by about 2dB of steady state MSE with the same convergence rate. In an experiment for channel models, the proposed method enhances performance by 4 dB so that the proposed method is more suitable for more complex or inferior conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.1-16
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• 2007

The use of information on natural resources is indispensable to most agricultural activities to avoid disasters, to improve input efficiency, and to increase lam income. Most information is prepared and managed at a spatial scale called the "Hydrologic Unit" (HU), which means watershed or small river basin, because virtually every environmental problem can be handled best within a single HU. South Korea consists of 840 such watersheds and, while other watershed-specific information is routinely managed by government organizations, there are none responsible for agricultural weather and climate. A joint research team of Kyung Hee University and the Agriculture, forestry and Fisheries Information Service has begun a 4-year project funded by the Ministry of Agriculture and forestry to establish a watershed-specific agricultural weather information service based on "high definition" digital climate maps (HD-DCMs) utilizing the state of the art geospatial climatological technology. For example, a daily minimum temperature model simulating the thermodynamic nature of cold air with the aid of raster GIS and microwave temperature profiling will quantify effects of cold air drainage on local temperature. By using these techniques and 30-year (1971-2000) synoptic observations, gridded climate data including temperature, solar irradiance, and precipitation will be prepared for each watershed at a 30m spacing. Together with the climatological normals, there will be 3-hourly near-real time meterological mapping using the Korea Meteorological Administration's digital forecasting products which are prepared at a 5 km by 5 km resolution. Resulting HD-DCM database and operational technology will be transferred to local governments, and they will be responsible for routine operations and applications in their region. This paper describes the project in detail and demonstrates some of the interim results.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.185-197
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• 2022

Recently, deep learning networks with high performance for object recognition are emerging. In the case of object recognition using deep learning, it is important to build a training data set to improve performance. To build a data set, we need to collect and label the images. This process requires a lot of time and manpower. For this reason, open data sets are used. However, there are objects that do not have large open data sets. One of them is data required for license plate detection and recognition. Therefore, in this paper, we propose an artificial license plate generator system that can create large data sets by minimizing images. In addition, the detection rate according to the artificial license plate arrangement structure was analyzed. As a result of the analysis, the best layout structure was FVC_III and B, and the most suitable network was D2Det. Although the artificial data set performance was 2-3% lower than that of the actual data set, the time to build the artificial data was about 11 times faster than the time to build the actual data set, proving that it is a time-efficient data set building system.

• Korean Security Journal
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• no.27
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• pp.129-159
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• 2011

Physical security has always been an extremely important facet within the security arena. A comprehensive security plan consists of three components of physical security, personal security and information security. These elements are interrelated and may exist in varying degrees defending on the type of enterprise or facility being protected. The physical security component of a comprehensive security program is usually composed of policies and procedures, personal, barriers, equipment and records. Human beings kept restless struggle to preserve their and tribal lives. However, humans in prehistoric ages did not learn how to build strong house and how to fortify their residence, so they relied on their protection to the nature and use caves as protection and refuge in cold days. Through the history of man, human has been establishing various protection methods to protect himself and his tribe's life and assets. Physical security methods are set in the base of these security methods. Those caves that primitive men resided was rounded with rock wall except entrance, so safety was guaranteed especially by protection for tribes in all directions. The Great Wall of China that is considered as the longest building in the history was built over one hundred years from about B.C. 400 to prevent the invasion of northern tribes, but this wall enhanced its protection function to small invasions only, and Mongolian army captured the most part of China across this wall by about 1200 A.D. European lords in the Middle Ages built a moat by digging around of castle or reinforced around of the castle by making bascule bridge, and provided these protections to the resident and received agricultural products cultivated. Edwin Holmes of USA in 20 centuries started to provide innovative electric alarm service to the development of the security industry in USA. This is the first of today's electrical security system, and with developments, the security system that combined various electrical security system to the relevant facilities takes charging most parts of today's security market. Like above, humankind established various protection methods to keep life in the beginning and its development continues. Today, modern people installed CCTV to the most facilities all over the country to cope with various social pathological phenomenon and to protect life and assets, so daily life of people are protected and observed. Most of these physical security systems are installed to guarantee our safety but we pay all expenses for these also. Therefore, establishing effective physical security system is very important and urgent problem. On this study, it is suggested methods of establishing effective physical security system by using system integration on the principle of security design about effective security system's effective establishing method of physical security system that is increasing rapidly by needs of modern society.

• Korean Security Journal
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• no.21
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• pp.75-94
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• 2009

Since mechanical security systems are mostly composed of electronic, information and communication devices, they have effects in the aspects of overall social environment and crime-oriented environment. Also, the importance is increasing for wireless recognition of RFID and tracing function, which will be usefully utilized in controlling the incomings and outgoings of people/vehicles or allowance, surveillance and control. This is resulting from the increase in the care for the elderly according to the overall social environment, namely, the aging society, and the number of women entering, as well as the increase in the number of heinous crimes. The purpose of this study is to examine the theoretical considerations on ubiquitous sensor network and present a direction for securities companies for their development by focusing on the technological and application areas. To present strategies of response to a new environment for security companies, First, a diversification strategy is needed for security companies. The survival of only high level of security companies in accordance with the principle of liberal market competition will bring forth qualitative growth and competitiveness of security market. Second, active promotion by security companies is needed. It is no exaggeration to say that we are living in the modern society in the sea of advertisements and propaganda. The promotional activities that emphasize the areas of activity or importance of security need to be actively carried out using the mass media to change the aware of people regarding security companies, and they need to come up with a plan to simultaneously carry out the promotional activities that emphasize the public aspect of security by well utilizing the recent trend that the activities of security agents are being used as a topic in movies or TV dramas. Third, technically complementary establishment of ubiquitous sensor network and electronic tag is needed. Since they are used in mobile electronic tag services such as U-Home and U-Health Care, they are used throughout our lives by forming electronic tag environment within safe ubiquitous sensor network based on the existing privacy guideline for the support of mobile electronic tag terminal commercialization, reduction in communication and information usage costs, continuous technical development and strengthening of privacy protection, and the system of cooperation of academic-industrial-research needs to be established among the academic world and private research institutes for these parts.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.29-37
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• 1999

In general, the information processing capability of a neural network is determined by its architecture and efficient training patterns. However, there is no systematic method for designing neural network and selecting effective training patterns. Evolutionary Algorithms(EAs) are referred to as the methods of population-based optimization. Therefore, EAs are considered as very efficient methods of optimal system design because they can provide much opportunity for obtaining the global optimal solution. In this paper, we propose a new method for finding the optimal structure of neural networks based on competitive co-evolution, which has two different populations. Each population is called the primary population and the secondary population respectively. The former is composed of the architecture of neural network and the latter is composed of training patterns. These two populations co-evolve competitively each other, that is, the training patterns will evolve to become more difficult for learning of neural networks and the architecture of neural networks will evolve to learn this patterns. This method prevents the system from the limitation of the performance by random design of neural networks and inadequate selection of training patterns. In co-evolutionary method, it is difficult to monitor the progress of co-evolution because the fitness of individuals varies dynamically. So, we also introduce the measurement method. The validity and effectiveness of the proposed method are inspected by applying it to the visual servoing of robot manipulators.

• Database Research
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• v.34 no.3
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• pp.124-136
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• 2018

There have been active research activities to use neural networks to analyze OCT images and make medical decisions. One requirement for these approaches to be promising solutions is that the trained network must be generalized to new devices without a substantial loss of performance. In this paper, we use a deep convolutional neural network to distinguish AMD from normal patients. The network was trained using a data set generated from an OCT device. We observed a significant performance degradation when it was applied to a new data set obtained from a different OCT device. To overcome this performance degradation, we propose an image normalization method which performs segmentation of OCT images to identify the retina area and aligns images so that the retina region lies horizontally in the image. We experimentally evaluated the performance of the proposed method. The experiment confirmed a significant performance improvement of our approach.