• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.120-130
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• 2012

As long span and complex bridges are constructed often recently, safety estimation became a big issue. Various types of measuring instruments are installed in case of long span bridge. New wireless technologies for long span bridges such as sending information through a gateway at the field or sending it through cables by signal processing the sensing data are applied these days. However, The case of occurred accidents related to bridge in the world have been reported that serious accidents occur due to lack of real-time proactive, intelligent action based on recognition accidents. To solve this problem in this study, the idea of "communication among things", which is the basic method of RFID/USN technology, is applied to the bridge monitoring system. A sensor node module for USN based intelligent bridge system in which sensor are utilized on the bridge and communicates interactively to prevent accidents when it captures the alert signals and urgent events, sends RF wireless signal to the nearest traffic signal to block the traffic and prevent massive accidents, is designed and tested by performing TinyOS based middleware design and sensor test free Space trans-receiving distance.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Korean Security Journal
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• no.18
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• pp.169-190
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• 2009

Today, the rapid advance of scientific technologies has brought about fundamental changes to the types and levels of terrorism while the war against the world more than one thousand small and big terrorists and crime organizations has already begun. A method highly likely to be employed by terrorist groups that are using 21st Century state of the art technology is cyber terrorism. In many instances, things that you could only imagine in reality could be made possible in the cyber space. An easy example would be to randomly alter a letter in the blood type of a terrorism subject in the health care data system, which could inflict harm to subjects and impact the overturning of the opponent's system or regime. The CIH Virus Crisis which occurred on April 26, 1999 had significant implications in various aspects. A virus program made of just a few lines by Taiwanese college students without any specific objective ended up spreading widely throughout the Internet, causing damage to 30,000 PCs in Korea and over 2 billion won in monetary damages in repairs and data recovery. Despite of such risks of cyber terrorism, a great number of Korean sites are employing loose security measures. In fact, there are many cases where a company with millions of subscribers has very slackened security systems. A nationwide preparation for cyber terrorism is called for. In this context, this research will analyze the current status of Korea's cyber security systems and its laws from a policy perspective, and move on to propose improvement strategies. This research suggests the following solutions. First, the National Cyber Security Management Act should be passed to have its effectiveness as the national cyber security management regulation. With the Act's establishment, a more efficient and proactive response to cyber security management will be made possible within a nationwide cyber security framework, and define its relationship with other related laws. The newly passed National Cyber Security Management Act will eliminate inefficiencies that are caused by functional redundancies dispersed across individual sectors in current legislation. Second, to ensure efficient nationwide cyber security management, national cyber security standards and models should be proposed; while at the same time a national cyber security management organizational structure should be established to implement national cyber security policies at each government-agencies and social-components. The National Cyber Security Center must serve as the comprehensive collection, analysis and processing point for national cyber crisis related information, oversee each government agency, and build collaborative relations with the private sector. Also, national and comprehensive response system in which both the private and public sectors participate should be set up, for advance detection and prevention of cyber crisis risks and for a consolidated and timely response using national resources in times of crisis.

• The Korean Society of Law and Medicine
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• v.21 no.2
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• pp.75-103
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• 2020

There is a growing voice that medical information should be shared because it can prepare for genetic diseases or cancer by analyzing and utilizing medical information in big data or artificial intelligence to develop medical technology and improve patient care. The utilization and protection of patients' personal information are the same as two sides of the same coin. Medical institutions or medical personnel should take extra caution in handling personal information with high environmental distinct characteristics and sensitivity, which is different from general information processors. In general, the patient's personal information is processed by medical personnel or medical institutions through the processes of collection, creation, and destruction. Still, the use of terms related to personal information in the Medical Service Act is jumbled, or the scope of application is unclear, so it relies on the interpretation of precedents. For the medical personnel or the founder of the medical institution, in the case of infringement of Article 24(4), it cannot be regarded that it means only medical treatment information among personal information, whether or not it should be treated the same as the personal information under Article 23, because the sensitive information of patients is recorded, saved, and stored in electronic medical records. Although the prohibition of information leakage under Article 19 of the Medical Service Act has a revision; 'secret' that was learned in business was revised to 'information', but only the name was changed, and the benefit and protection of the law is the same as the 'secret' of the criminal law, such that the patient's right to self-determination of personal information is not protected. The Privacy Law and the Local Health Act consider the benefit and protection of the law in 'information learned in business' as the right to self-determination of personal information and stipulate the same penalties for personal information infringement such as leakage, forgery, alteration, and damage. The privacy regulations of the Medical Service Act require that the terms be adjusted uniformly because the jumbled use of terms can confuse information subjects, information processors, and shows certain limitations on the protection of personal information because the contents or scope of the regulations of the Medical Service Law for special corporations and the Privacy Law may cause confusion in interpretation. The patient's personal information is sensitive and must be safely protected in its use and processing. Personal information must be processed in accordance with the protection principle of Privacy Law, and the rights such as privacy, freedom, personal rights, and the right to self-determination of personal information of patients or guardians, the information subject, must be guaranteed.