• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.6
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• pp.1586-1589
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• 2007

This study aims to construct Constitution Information Bank to objectification of Sasang Constitution Diagnosis and Treatment. 422 cases clinically confirmed their Constitution by experts are collected retrospectively and 219 cases for constitution-family study are also collected in Constitution Information Bank from Nov. 2006 to Sept. 2007. The information include their physique, appearance, character, temper, symptom and treatment records. Their DNA cell lines also included in Constitution Information Bank for constitution-genome study. Constitution Information Bank is composed of constitution-clinical information -physique, appearance, character, temper, symptom and treatment records- and biological information -DNA genotyping data-. Total of 550 cases are collected in Constitution Information Bank from Nov. 2006 to Sept. 2007. Among these, 219 cases are for constitution-family study, especially, 74 cases are collected from Han's large family.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.107-112
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• 2018

Smart livestock has been proposed as a solution to increase farmers' income and new recruitment of livestock farmers. In this paper, a standardization Plan of breeding management device and collected information for smart livestock cattle was proposed. l Sophisticatedly, basic information will be established for all six types of livestock breeding management device: military automatic feeder, calf automatic feeder, smart milk cooler, feed bin to be able to measure feed residue, smart scale, and biometric information collection device. The standardization, common use, and stabilization of major livestock management device and collected information were suggested to solve the problems caused by in existing breeding management device.

• Informatization Policy
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• v.26 no.1
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• pp.25-45
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• 2019

With the advent of the data economy, interest in using big data has increased, but conflicts with protecting personal information have been also steadily raised. In this regard, major countries are accelerating use of big data by exempting de-identified, pseudonymous personal information from protection. However, these policies have been made without the understanding that the economic value of personal information has been actually changing slowly. This paper presents the concept of 'collected information' and defines it as having public interest and therefore, not the exclusive property of the collector of such information. The paper shows the collected information has public interest in terms of personal information protection, connectivity, and universal service and public goods. It also specifies that the 'data governance' cannot be applied to the current data utilization framework that depends upon the holder's consent; rather, it raises the need to improve the practices of information provision consent or provide the beneficiary right of information use to the information holder in order to ensure the proper 'data governance' that will turn market failure into success.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.138-145
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• 2010

In this paper, we consider the information processing system, which organizes the collected data to meaningful information when the number of data collected from multiple sources reaches to a predetermined number, and performs any action by processing the collected data, or transmits to other devices or systems. We derive an analytical model to calculate the time until it takes to process information after starting to collect data. Therefore, in order to complete the processing data within certain time constraints, we develop some design criteria to control various parameters of the information processing system. Also, we analyze the discrete time model for packet switching networks considering data with no particular arrival nor drop pattern. We analyze the relationship between the number of required packets and average information processing time through numerical examples. By this, we show that the proposed model is able to design the system to be suitable for user's requirements being complementary the quality of information and the information processing time in the system with time constraints.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.17-24
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• 2017

In the medical field, augmented reality is being used for surgical and medical education. However, augmented reality technology is not applied to emergency patients. In this paper, we propose a medical service support model that can support rapid medical service to emergency patients through an augmented reality - based IT device. The proposed model has the function of collecting the information necessary for the first aid simply through the IT equipment based on the reality of reality, and also receiving the first aid method appropriate for the emergency situation to the medical staff and supporting the service. In addition, the proposed model hierarchically collects information related to emergency patient information inquiry, emergency patient status and emergency treatment based on Analytic Hierarchy Process (AHP). The collected information uses a pair of comparison matrices to compensate for the ambiguity between the information. In particular, the collected information is stored in the server of the medical staff, and in addition to the unique information of the collected information, the collected information can be reflected in the medical service of the medical staff.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1051-1059
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• 2014

In this paper, we propose an intelligent situation recognition model by collecting and analyzing multiple sensor signals. Multiple sensor signals are collected for fixed time window. A training set of collected sensor data for each situation is provided to K2-learning algorithm to generate Bayesian networks representing causal relationship between sensors for the situation. Statistical characteristics of sensor values and topological characteristics of generated graphs are learned for each situation. A neural network is designed to classify the current situation based on the extracted features from collected multiple sensor values. The proposed method is implemented and tested with UCI machine learning repository data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.4
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• pp.149-162
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• 2004

Until now the study of computer forensics has been focused only system forensics which carried on keeping, processing and collecting the remained evidence on computer. Recently the trend of forensic study is proceeding about the network forensics which analyze the collected information in entire networks instead of analyzing the evidence on a victim computer. In particular network forensics is more important in Automated Computer Emergency Response System because the system deals with the intrusion evidence of entire networks. In this paper we defined the information of network forensics that have to be collected in Automated Computer Emergency Response System and verified the defined information by comparing with the collected information in experimental environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4909-4926
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• 2020

Cyberattacks penetrate the server and perform various malicious acts such as stealing confidential information, destroying systems, and exposing personal information. To achieve this, attackers perform various malicious actions by infecting endpoints and accessing the internal network. However, the current countermeasures are only anti-viruses that operate in a signature or pattern manner, allowing initial unknown attacks. Endpoint Detection and Response (EDR) technology is focused on providing visibility, and strong countermeasures are lacking. If you fail to respond to the initial attack, it is difficult to respond additionally because malicious behavior like Advanced Persistent Threat (APT) attack does not occur immediately, but occurs over a long period of time. In this paper, we propose a technique that detects an unknown attack using an event log without prior knowledge, although the initial response failed with anti-virus. The proposed technology uses a combination of AutoEncoder and 1D CNN (1-Dimention Convolutional Neural Network) based on semi-supervised learning. The experiment trained a dataset collected over a month in a real-world commercial endpoint environment, and tested the data collected over the next month. As a result of the experiment, 37 unknown attacks were detected in the event log collected for one month in the actual commercial endpoint environment, and 26 of them were verified as malicious through VirusTotal (VT). In the future, it is expected that the proposed model will be applied to EDR technology to form a secure endpoint environment and reduce time and labor costs to effectively detect unknown attacks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1567-1574
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• 2017

In this paper, we analyzed the stereotyped and non - stereotyped data in order to analyze the drama 's ratings. The formalized data collection collected 19 items from the four areas of drama information, person information, broadcasting information, and audience rating information of each broadcasting company. Atypical data were collected from bulletin boards, pre - broadcast blogs and post - broadcast blogs operated by each broadcasting company using a crawling technique. As a result of comparing the differences according to the four areas for each broadcaster from the collected regular data, the results were similar to each other. And we derived seven related words by analyzing the correlation of occurrence frequencies from unstructured data collected from bulletin boards and blogs of each broadcasting company. The derived associations were obtained through reliability analysis.

• The Journal of Information Systems
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• v.31 no.2
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• pp.1-18
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• 2022

Purpose Customer review is a major factor in choosing certain restaurants. This study investigates the key factors affecting customer's evaluation about restaurants. With the recent intensification of competition among restaurants in the service industry, the analysis results are expected to provide in-depth insights for enhancing customer experiences. Design/methodology/approach We collected information and reviews provided at the restaurants in the Kakao Map platform. The information collected is based on the information of 3,785 restaurants in Daegu registered on Kakao Map. Based on the information collected, seven independent variables, including number of rating registered, number of reviews, presence or absence of safe restaurants, presence or absence of a posting about holding facilities, presence or absence of a posting about business hours, presence or absence of a posting about hashtags, and presence or absence of break times, were used. Dependent variable is restaurant rating. Multiple regression between independent variables and restaurant rating was carried out. Findings The results of the study confirmed that number of rating registered, presence or absence of a posting about business hours, and presence or absence of a posting about hash tags have an positive effects on the restaurant rating. The number of reviews had a negative effect on the restaurant rating. In addition, in order to confirm the role of customer's reviews, we carried out LDA topic modeling. We divided the topics into the positive review and the negative reviews.