• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.211-224
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• 2004

Distributing information on the internet is common in our daily life. In the past, e-mail has been the primary choice of exchanging information, but instant messengers are gaining popularity abroad and domestically because of their immediate responses. Instant messaging has become the fastest growing communication technology in recent years. Instant messaging is effectively a chat room for two people. Users that have accounts with the same provider are able to send messages via computer in real time. Instant messaging has exploded into the business world as companies now utilize the technology for everything from interoffice communication to client/customer communication. In this paper, we propose a method of instant messenger system design for effective collaboration of statistical data collection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.344-351
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• 2005

It was discussed to satellite based DCS (NOAA, Orbcomm, ADEOS-II, CBERS in polar satellite and GMS, GOES, METEOSAT, INSAT, FY-2 in geostationary satellite) with PTT (Platform Transmitter Terminal) and DCP (Data collection Platform) in order to application of real-time DCS (Data Collection System) in the ocean and fisheries. For covering ocean data link area in the eastern hemisphere, it was proposed to take DCS on the Korean geostationary satellite in the marine environments.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.101-108
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• 2017

The study proposed a system that filters the data that is entered when analyzing big data such as SNS and BLOG. Personal information includes impersonal personal information, but there is also personal information that distinguishes it from personal information, such as religious institution, personal feelings, thoughts, or beliefs. Define these personally identifiable information as sensitive information. In order to prevent this, Article 23 of the Privacy Act has clauses on the collection and utilization of the information. The proposed system structure is divided into two stages, including Big Data Processing Processes and Sensitive Information Filtering Processes, and Big Data processing is analyzed and applied in Big Data collection in four stages. Big Data Processing Processes include data collection and storage, vocabulary analysis and parsing and semantics. Sensitive Information Filtering Processes includes sensitive information questionnaires, establishing sensitive information DB, qualifying information, filtering sensitive information, and reliability analysis. As a result, the number of Big Data performed in the experiment was carried out at 84.13%, until 7553 of 8978 was produced to create the Ontology Generation. There is considerable significan ce to the point that Performing a sensitive information cut phase was carried out by 98%.

• Journal of Ecology and Environment
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• v.30 no.2
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• pp.201-207
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• 2007

Researchers have used a variety of methods to measure patterns of animal movement, including the use of spatial data (mapping the position of a moving animal at specified intervals) and direct estimation of travel path length by pacing under a moving animal or group. I collected movement data from five groups of siamangs (Symphalangus syndactylus) using two different methods concurrently to estimate the effects of the method of data collection on estimates of daily path length (DPL). Estimates of DPL produced from spatial data collected at 15-minute intervals were 12% lower than estimates of DPL produced by pacing under the traveling animal. The actual magnitude of the difference was correlated with the travel distance, but there was no correlation between the proportional difference and the travel distance. While the collection of spatial data is generally preferable, as spatial data permit additional analyses of patterns of movements in two or three dimensions, the relatively small difference between the DPL's produced using different methods suggests that pacing is an acceptable substitute where the collection of spatial data is impractical. I also subsampled the spatial data at increasing time intervals to assess the effect of sampling interval on the calculation of daily path lengths. Longer sampling intervals produced significantly shorter estimates of travel paths than shorter sampling intervals. These results suggest that spatial data should be collected at short time intervals wherever possible, and that sampling intervals should not exceed 30 minutes. Researchers should be cautious when comparing data generated using different methods.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.385-392
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• 2022

As energy-saving techniques based on human behavior patterns have recently become an issue, the occupant-centered control system is adopted for estimating personal preference of indoor environment and optimizing environmental comfort and energy consumption. Accordingly, IoT devices have been used to collect indoor environmental quality (IEQ) data and personal data. However, the need to safely collect and manage data has been emerged due to cybersecurity issues. Therefore, this paper aims to present a framework that can safely transmit occupant-centered data collected from IoT to a private blockchain server using Hyperledger fabric. In the case study, the minimum value product of the mobile application and smartwatch application was developed to evaluate the usability of the proposed blockchain-based occupant-centered data collection framework. The results showed that the proposed framework could collect data safely and hassle-free in the daily life of occupants. In addition, the performance of the blockchain server was evaluated in terms of latency and throughput when ten people in a single office participated in the proposed data collection framework. Future works will further apply the proposed data collection framework to the building management system to automatically collect occupant data and be used in the HVAC system to reduce building energy consumption without security issues.

• Journal of KIISE:Information Networking
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• v.35 no.1
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• pp.21-33
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• 2008

The wireless sensor nodes near to the fixed sink node suffer from the quickly exhausted battery energy. To address this problem, the mobile sink node has been applied to distribute the energy consumption into all wireless sensor nodes. However, since the mobile sink node moves, the data collection scheduling scheme is necessary for the sink node to receive the data from all sensor nodes as fair as possible. The application fields of wireless sensor network need the real-time processing. If the uneven data collection occurs in the wireless sensor network, the real-time processing for the urgent events can not be satisfied. In this paper, a new method is proposed to support the lair data collection between all sensor nodes. The proposed method performs the scheduling algorithm based on the resident time of the sink node staying in a radius of communication range and the amount of data transferred already. In this paper, the proposed method and existing data collection scheduling schemes are evaluated in wireless sensor network with the mobile sink node. The result shows that the proposed method provides the best fairness among all data collection schemes.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.131-139
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• 2019

From 2019, software education has become a required subject for all elementary school students. However, many teachers are still unfamiliar with how the classes should be instructed. So this paper presented the meaning, detailed competencies and achievement standard in order to help in the collection, analysis and representation of data among the computational thinking that are key to software education. And it also suggested the applicability of the classes. The full course of the paper is summarized as follows. First, existing studies have summarized the meaning, detail and achievement standard of data related competencies. Based on this, a preliminary investigation was instructed. Pilot study carried out both FGI and closed questions at the same time. This was done in response to the survey's questionnaire reflecting the opinions of experts. Second, the results of the questionnaire generated as a result of the above were verified for validity, stability, and reliability among the PhD, PhD courses, software education teachers, and software education workers. Third, I developed and applied the five lessons as a class objective as 'Choosing collection method-Select the collection method according to the problem situation.', 'Searching for meaning of data-Understand what the analyzed data mean..', 'Using various expression methods-Use a variety of expression tools.' using the backward design model to integrate education, class, and assessment. As a result, the detailed competencies of data collection, analysis, and representation and achievement standard were presented. This may help in setting specific and specific criteria for what direction classes are recommended when planning data-related classes in elementary schools.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.95-101
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• 2023

Globally, the importance of utilization and management of marine spatial information is being maximized, and analyzing such data is emerging as a major driving force for R&D. In Korea, it is expected that collecting marine data from the past to the present and extracting its value will play an important role in the development of science in Korea in the future. In particular, marine static data constitutes a huge big database, and it is necessary to store and store the collected data without loss as high data collection costs and high-level observation techniques are required. In addition, the Disaster Safety Intelligence Convergence Center's "Marine Digital Twin Establishment and Utilization-Based Technology Research" task requires collection and analysis of marine data, so this paper conducts a current status survey of static marine data. And we present a series of algorithms that collect and store them in a database.

• Smart Media Journal
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• v.12 no.5
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• pp.65-72
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• 2023

Smart Farm means creating new value in various fields related to agriculture, including not only agricultural production but also distribution and consumption through the convergence of agriculture and ICT. In Korea, a rental smart farm is created to spread smart agriculture, and a smart farm big data platform is established to promote data collection and utilization. It is pushing for digital transformation of agricultural products distribution from production areas to consumption areas, such as expanding smart APCs, operating online exchanges, and digitizing wholesale market transaction information. As such, although agricultural data is generated according to characteristics from various sources, it is only used as a service using statistics and standardized data. This is because there are limitations due to distributed data collection from agriculture to production, distribution, and consumption, and it is difficult to collect and process various types of data from various sources. Therefore, in this paper, we analyze the current state of domestic agricultural data collection and sharing for digital agriculture and propose a data collection and linkage method for artificial intelligence services. And, using the proposed data, we propose a deep learning-based environmental factor recommendation method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.1
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• pp.57-67
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• 2013

Lately, intrusive incidents (including system hacking, viruses, worms, homepage alterations, and data leaks) have not involved the distribution of an virus or worm, but have been designed to acquire private information or trade secrets. Because an attacker uses advanced intelligence and attack techniques that conceal and alter data in a computer, the collector cannot trace the digital evidence of the attack. In an initial incident response first responser deals with the suspect or crime scene data that needs investigative leads quickly, in accordance with forensic process methodology that provides the identification of digital evidence in a systematic approach. In order to an effective initial response to first responders, this paper analyzes the collection data such as user usage profiles, chronology timeline, and internet data according to CFFPM(computer forensics field triage process model), proceeds to design, and implements a collection application to deploy the client/server architecture on the Windows based computer.