• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.1-6
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• 2016

Many studies have been carried out for the development of big data utilization and analysis technology recently. There is a tendency that government agencies and companies to introduce a Hadoop of a processing platform for analyzing big data is increasing gradually. Increased interest with respect to the processing and analysis of these big data collection technology of data has become a major issue in parallel to it. However, study of the collection technology as compared to the study of data analysis techniques, it is insignificant situation. Therefore, in this paper, to build on the Hadoop cluster is a big data analysis platform, through the Apache sqoop, stylized from relational databases, to collect the data. In addition, to provide a sensor through the Apache flume, a system to collect on the basis of the data file of the Web application, the non-structured data such as log files to stream. The collection of data through these convergence would be able to utilize as a basic material of big data analysis.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.481-489
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• 2010

Due to the increase of the attention on relation extraction systems, the construction of test collections for assessing their performance has emerged as an important task. In this paper, we propose semi-automatic framework capable of constructing test collections for relation extraction on a large scale. Based on this framework, we develop a test collection which can assess the performance of various approaches to extracting relations between technical terminologies in scientific literatures. This framework can minimize the cost of constructing this kind of collections and reduce the intrinsic fluctuations which may come from the diversity in characteristics of collection developers. Furthermore, we can construct balanced and objective collections by means of controlling the selection process of seed documents and terminologies using the proposed framework.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.644-649
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• 2000

A new cyclone system for the vacuum cleaner to collect dusts has been studied experimentally and numerically to meet the constant suction power, hygienic exhaust and a reduction of maintenance cost. The cyclone system of the vacuum cleaner consists of twin cyclones for improving dust collection efficiency. The first. cyclone catches large dust particles and the second one having two separated flows to decrease pressure drop collects small dust particles. The optimal design factors such as dust collection efficiency, pressure drop, and cut-size are investigated from the experimental results by the Taguchi method. Cyclone cleaner systems designed in this study has a good Performance taking into account the dust collection efficiency of 93% and the cut-size of $1.6{\mu}m$ in mass median diameter at the flow rate of 1 CMM. The cyclone vacuum cleaner showed the potential to be an effective method to collect dusts generated in the household.

• Mycobiology
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• v.45 no.4
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• pp.401-408
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• 2017

Colletotrichum gloeosporioides is an economically important fungal pathogen causing substantial yield losses indifferent host plants. To understand the genetic diversity and molecular epidemiology of this fungus, we have developed a novel, high-resolution multi-locus microsatellite typing (MLMT) method. Bioinformatic analysis of C. gloeosporioides unannotated genome sequence yielded eight potential microsatellite loci, of which five, CG1 $(GT)_n$, CG2 $(GT1)_n$, CG3 $(TC)_n$, CG4 $(CT)_n$, and CG5 $(CT1)_n$ were selected for further study based on their universal amplification potential, reproducibility, and repeat number polymorphism. The selected microsatellites were used to analyze 31 strains of C. gloeosporioides isolated from 20 different host plants from India. All microsatellite loci were found to be polymorphic, and the approximate fragment sizes of microsatellite loci CG1, CG2, CG3, CG4, and CG5 were in ranges of 213-241, 197-227, 231-265, 209-275, and 132-188, respectively. Among the 31 isolates, 55 different genotypes were identified. The Simpson's index of diversity (D) values for the individual locus ranged from 0.79 to 0.92, with the D value of all combined five microsatellite loci being 0.99. Microsatellite data analysis revealed that isolates from Ocimum sanctum, Capsicum annuum (chili pepper), and Mangifera indica (mango) formed distinct clusters, therefore exhibited some level of correlation between certain genotypes and host. The developed MLMT method would be a powerful tool for studying the genetic diversity and any possible genotype-host correlation in C. gloeosporioides.

• Journal of Fashion Business
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• v.23 no.5
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• pp.1-18
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• 2019

The purpose of this study is to analyze the Muslim fashion that has recently appeared in the global fashion collection to see how the global fashion brand expresses Muslim's traditional costumes so as to provide references in design development to prepare for the larger Muslim fashion market in the future. In order to analyze Muslim fashion, keywords related to Muslims such as "Muslim," "Islamic fashion" and "hijab" were searched on Google, Samsung Design Net and Vogue websites, and a total of 370 fashion photos were selected for the final data, which was judged to reflect Muslim fashion styles after a review by four clothing experts. Muslim fashion styles have the following characteristics: Above all, the use of veils was most noticeable, with many T-shaped loose long tunic dresses. The hijab, which had the highest proportion of veils, was used to produce various images with wide range of materials and colors. Achromatic colors were the most common, but more than three colors were used to create an exotic image. There have also been cases of using direct religious images such as arabesque patterns and mosques and Muslim priests. As a final, Muslim fashion styles were studied follow: first, a unique style using a veil. Second, conservative style with minimal exposure, third, restrained long-and-lose fit style, fourth, exotic style by elaborate pattern. The domestic fashion industry is also expected to generate economic demand if it is designed with reference to such collection trends along with market research on Muslim consumers.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.27-54
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• 2021

This study examines the overall contents of robots, drones, and autonomous driving that can be applied to libraries among autonomous objects, and proposes a plan that can be introduced and applied to libraries in the future based on this. As a result of the study, in the case of the building, robots and drones can be used to apply from collection inspection, collection transport, collection arrangement, collection classification, book location guidance, book recommendation, loan/return, library general guidance, and reference information service. Outside of the building, robots, drones, and autonomous vehicles can be used for book delivery service, book return service, and unmanned mobile libraries. This study is a basic research for the introduction and application of autonomous objects in the library, and follow-up studies such as perception survey and application model development for systematic introduction should be conducted in the future.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• 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.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.1
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• pp.45-53
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• 2017

The Internet of Things (IoT) technology allows devices connected to the Internet to exchange information without human intervention, and to provide useful services to people. Currently, garbage trucks are regularly dispatched to collect garbage. In such a case, garbage may be less than half of the garbage collection capacity in some area, and garbage may be exceeded in another area so that garbage trucks can not collect all at once. In this paper, we have studied the method of estimating the amount of garbage to be collected and describe the development contents of the product and management system. The prediction of garbage volume was made possible by using IoT technology to measure the volume of garbage in real time. In addition, the measurement values are visibly displayed through the dashboard, so that the amount of garbage generated can be predicted and managed. This will allow IoT technology to help keep street hygiene.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.