• Journal of Service Research and Studies
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• v.10 no.1
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• pp.85-96
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• 2020

In Asia, where the aging population is growing rapidly, as the funeral service industry develops and the market grows. The economic value and interest of funeral services is increasing. However, Korea's funeral services are being developed in a biased direction, focusing only on funeral services, after death. Compared to the case of advanced funeral services in the United States, the United Kingdom, and Japan, not only the funeral but also the care of the deceased's family and acquaintances around us are developing. It is appropriate to use a method based on ethnography and User eXperience. For this purpose, the method of collecting and analyzing the ethnography and user experience data of actual resident and visitor was deduced in persona method in the next ten years, and funeral service centered on resident and visitor. In this study, qualitative data centered on the future direction of funeral services, focusing on the resident (family) and the guest who are the principals of services from the perspective of service science. It is difficult to derive meaningful results from the process of collecting, processing, and interpreting big data in general, and in this case, the data analysis method is based on ethnography and user eXperience.) Is appropriate. For this purpose, the method of collecting and analyzing the ethnography and user experience data of the actual resident and the visitor was deduced in the persona method in detail after 10 years. In addition, the future direction of funeral services centered on residence and visitor was presented.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.229-241
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• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1515-1527
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• 2016

With the growth of big data, machine learning, and cloud computing, the importance of storage that can store large amounts of unstructured data is growing recently. So the commodity hardware based distributed file systems such as MAHA-FS, GlusterFS, and Ceph file system have received a lot of attention because of their scale-out and low-cost property. For the data fault tolerance, most of these file systems uses replication in the beginning. But as storage size is growing to tens or hundreds of petabytes, the low space efficiency of the replication has been considered as a problem. This paper applied erasure coding data fault tolerance policy to MAHA-FS for high space efficiency and introduces VDelta technique to solve data consistency problem. In this paper, we compares the performance of two file systems, MAHA-FS and GlusterFS. They have different IO processing architecture, the former is server centric and the latter is client centric architecture. We found the erasure coding performance of MAHA-FS is better than GlusterFS.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.557-564
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• 2006

Information is used effectively and contributes in profit creation and not only support management judgment quick but important resource to be possible recycled. The recent information systems improve enterprise's competitive power by reflection of user's various requirements and becoming big and complex for adaptation of rapidly circumstance change. Also it is trend that importance of information quality is emphasized gradually. The biggest problem in user requirement that is based on low quality data support. In case of business management is achieved by low quality information, company can not help dropping their competitive power such as company's strategy establishment, strategy achievement and management concentration breakup against competitor. Information of low quality increase time and expense to improve inaccurate data or revise and it is hard to accept correct information from specific situation. To solve these problems, we have to gain high quality data through definite comprehension, data management system establishment, and systematic data management achievement etc. Up to now, information quality and connected study were developed partially, but systematic methodology of information quality management's whole condition was not existed. Therefore, in this paper can show you how to extract process for information quality management & related evaluate factor with CMM (Capacity Maturity Mode]) 5 steps that is information warranty of quality process step. This paper whishes to contributes in competitive company or organization activity through information quality improvement management process.

• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.151-155
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• 2021

The application of environmental DNA in the domestic ecosystem is also accelerating, but the processing and analysis of the produced data is limited, and doubts are raised about the reliability of the analyzed and produced biological taxa identification data, and the sample medium (target sample, water, air, sediment, Gastric contents, feces, etc.) and quantification and improvement of analysis methods are also needed. Therefore, in order to secure the reliability and accuracy of biodiversity research using the environmental DNA of the domestic ecosystem, it is a process of actively using the database accumulated through ecological taxonomy and undergoing verification procedures, and experts verifying the resolution of the data increased by gene sequence analysis. This is absolutely necessary. Environmental DNA research cannot be solved only by applying molecular biology technology, and interdisciplinary research cooperation such as ecology-taxa identification-genetics-informatics is important to secure the reliability of the produced data, and researchers dealing with various media can approach it together. It is an area in desperate need of an information sharing platform that can do this, and the speed of development will proceed rapidly, and the accumulated data is expected to grow as big data within a few years.

• Journal of the Korean Society of Safety
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• v.34 no.4
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• pp.22-31
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• 2019

The flammable liquid conductivity is an important factor in determining the generation of electrostatic in fire and explosion hazardous areas, so it is necessary to study the physical properties of flammable liquids. In particular, the relevant liquid conductivity in the process of handling flammable liquids in relation to the risk assessment and risk control in fire and explosion hazard areas, such as chemical plants, is classified as a main evaluation item according to the IEC standard, and it is necessary to have flammable liquid conductivity measuring devices and related data are required depending on the handling conditions of the material, such as temperature and mixing ratio for preventing the fire and explosion related to electrostatic. In addition, IEC 60079-32-2 [Explosive Atmospheres-Part 32-2 (Electrostatic hazards-Tests)] refers to the measuring device standard and the conductivity of a single substance. It was concluded that there is no measurement data according to the handling conditions such as mixing ratio of flammable liquid and temperature together with the use and measurement examples. We have developed the measurement reliability by improving the structure, material and measurement method of measuring device by referring to the IEC standard. We have developed a measurement device that is developed and manufactured by itself. The test results of flammable liquid conductivity measurement and the data of the NFPA 77 (Recommended Practice on Static Electricity) Annex B Table B.2 Static Electric Characteristic of Liquids were compared and verified by conducting the conductivity measurement of the flammable liquid handled in the fire and explosion hazardous place by using Measuring / Data Acquisition / Processing / PC Communication. It will contribute to the prevention of static electricity related disaster by taking preliminary measures for fire and explosion prevention by providing technical guidance for static electricity risk assessment and risk control through flammable liquid conductivity measurement experiment. In addition, based on the experimental results, it is possible to create a big data base by constructing electrostatic physical characteristic data of flammable liquids by process and material. Also, it is analyzed that it will contribute to the foundation composition for adding the specific information of conductivity of flammable liquid to the physical and chemical characteristics of MSDS.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.334-343
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• 2023

Purpose: In this study, the cavity data found through ground cavity exploration was combined with underground facilities to derive a correlation, and the ground subsidence prediction map was verified based on the AI algorithm. Method: The study was conducted in three stages. The stage of data investigation and big data collection related to risk assessment. Data pre-processing steps for AI analysis. And it is the step of verifying the ground subsidence risk prediction map using the AI algorithm. Result: By analyzing the ground subsidence risk prediction map prepared, it was possible to confirm the distribution of risk grades in three stages of emergency, priority, and general for Busanjin-gu and Saha-gu. In addition, by arranging the predicted ground subsidence risk ratings for each section of the road route, it was confirmed that 3 out of 61 sections in Busanjin-gu and 7 out of 68 sections in Sahagu included roads with emergency ratings. Conclusion: Based on the verified ground subsidence risk prediction map, it is possible to provide citizens with a safe road environment by setting the exploration section according to the risk level and conducting investigation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.243-262
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• 2018

Database schema integration is a significant issue in information systems. Because schema integration is a time-consuming and labor-intensive task, many studies have attempted to automate it. Researchers typically use XML as the source schema and leave much of the work to be done through DBA intervention, e.g., there are various naming conflicts related to relationship names in schema integration. In the past, the DBA had to intervene to resolve the naming-conflict name. In this paper, we introduce an algorithm that automatically generates relationship names to resolve relationship name conflicts that occur during schema integration. This algorithm is based on an Internet collocation and English sentence example dictionary. The relationship between the two entities is generated by analyzing examples extracted based on dictionary data through natural language processing. By building a semi-automated schema integration system and testing this algorithm, we found that it showed about 90% accuracy. Using this algorithm, we can resolve the problems related to naming conflicts that occur at schema integration automatically without DBA intervention.