• Journal of Mushroom
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• v.9 no.1
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• pp.34-38
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• 2011

In this study, temperature and relative humidity during growth of fruit body were applied to oyster mushroom (Pleurotus ostrestus) to elucidate the prolongation effect of storage. Although there were not big differences among conditions of cultivation, weight loss and change of pileus color were slight increased and hardness and springness of fruit body were little decreased with storage period. When whole mushrooms (250~300g) were packaged with wrap and stored at $4{\pm}1^{\circ}C$, the shelf life of the oyster mushrooms were cultivated at $16^{\circ}C$ and at $13^{\circ}C$ was 18 day and 24days, respectively. Therefore, it was elucidated that the treatment of low-temperature at the step of fruit body development affected extension of shelf life in oyster mushroom.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.4
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• pp.386-392
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• 2009

This paper reports on the research which investigates acoustic signals acquired in progressive compressing, hole blanking, shearing and burr compacting process. The work piece is the head pin of the electric connector, whose raw material is the preformed steel bar. An acoustic sensor was set on the bed of hydraulic press. Because the acquired signals include the dynamic characteristics generated for all the processes, it is required to investigate signal characteristics corresponding to unit process. The corresponding dynamic characteristics to the respective process were first studied by analyzing the signals respectively acquired from compressing, blanking and compacting process. The combined signals were then periodically analyzed from the grinding to the grinding in the sound frequency domain and in the ultrasonic wave. The frequency of around 9 kHz in the sound frequency domain was much correlated to the tool wear. The characteristic frequency in the acoustic emission domain between 100 kHz and 500 kHz was not only clearly observed right after tool grinding but its amplitude was also related to the wear. The frequency amplitudes of 160 kHz and 320 kHz were big enough to be classified by the noise. The noise amplitudes are getting bigger, and their energy was much bigger as coming to the next regrinding. The signal analysis was based on the real time data and its frequency spectrum by Fourier Transform. As a result, the acousto-ultrasonic signals were much related to the tool wear progression.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.413-433
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• 2010

The purpose of this study is to portray the current condition of digital reading rooms in public libraries in specific terms of information resource constituencies. With the growth in numbers of public libraries in Korea, emphasis was also put on digital information services using digital reading rooms in public libraries. However, it is also recognized that these digital reading rooms are merely traditional reading rooms with equipment. In this regard, the objective for the study was to identify and describe the types of electronic information resources in order to determine the rationale for the development of digital information resource management in public libraries. The focus was especially put on investigating the quality and the degree of perceived importance of electronic resources. Data for this case study was collected from four relatively big public libraries in three cities. The investigation was conducted by the document reviews and surveys and interviews with librarians and patrons. The study found that digital resource management should be put on a new stage, especially in terms of education and reliable information for the regional community. The study also added some suggestions for the future development and refinement of electronic resource management in public libraries.

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.26-31
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• 2017

The current autonomous vehicle competitions are dominated by a few leading research institutions and universities. Since the leading research groups have been able to accumulate their knowledge and to develop their own algorithms for autonomous vehicle for many years, the technology gap seems too big for other followers to catch up with. On the other hand, recent researches predict that there would be a sharp rise in demand for engineers with background in autonomous vehicle technology. Therefore, it would be warranted to further expand the base of the academia and autonomous vehicle industry. In an effort to achieve this goal, it would be beneficial to hold a new format of autonomous vehicle competition event where undergraduate students can play a leading role. So, this study is to analyze the current autonomous vehicle competitions and thus to establish a strategic plan to develop a unique and improved competition event. This study investigates the pros and cons of the domestic and international autonomous vehicle competitions. Based on the analysis for the current autonomous vehicle competitions, the authors suggest a strategic plan to initiate an autonomous vehicle competition. To implement the aforementioned strategic plan, it is necessary to develop a systematic environment where the education and communication are actively available. Through the strategic plan the authors propose, the newly launching autonomous vehicle competition will able to encourage the undergraduate students and professors to dive in the cutting-edge technology thereby increasing technology competitiveness.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.1-14
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• 2016

Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.247-258
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• 2017

Since 2016 when the regulations related to vehicle structure and device modification were drastically revised, the car tuning market has been growing rapidly. Particularly, many drivers are showing interest in changing the interior and exterior according to their preference, or improving the specifications of their cars by changing the engine and powertrain, among others. Also, as the initial engine settings such as horse power and torque of the vehicle are made for stable driving of the vehicle, it is possible to change the engine performance, via Engine Control Unit (ECU) mapping, to the driver's preference. However, traditionally, ECU mapping could be only performed by professional car engineers and the settings were also decided by them. Therefore, this study proposed a system that collects data related to the driver's driving habits for a certain period and sends them to a cloud server in order to analyze them and recommend ECU mapping values. The traditional mapping method only aimed to improve the car's performance and, therefore, if the changes were not compatible with the driver's driving habits, could cause problems such as incomplete combustion or low fuel efficiency. However, the proposed system allows drivers to set legally permitted ECU mapping based on analysis of their driving habits, and, therefore, different drivers can set it differently according to the vehicle specifications and driving habits. As a result, the system can optimize the car performance by improving output, fuel efficiency, etc. within the range that is legally permitted.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.13-29
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• 2020

Automobiles have long been an essential part of daily life, but the social costs of car traffic accidents exceed 9% of the national budget of Korea. Hence, it is necessary to establish prevention and response system for car traffic accidents. In order to present a model that can classify and predict the degree of injury in car traffic accidents, we used big data analysis techniques of K-nearest neighbor, logistic regression analysis, naive bayes classifier, decision tree, and ensemble algorithm. The performances of the models were analyzed by using the data on the nationwide traffic accidents over the past three years. In particular, considering the difference in the number of data among the respective injury severity levels, we used down-sampling methods for the group with a large number of samples to enhance the accuracy of the classification of the models and then verified the statistical significance of the models using ANOVA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.111-118
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• 2012

When broadcasters want immediately a variety of VOD files in a distributed server of them data centers and away contents provider, CPs of different platform to exchange high-quality HD, 3DTV video and other video files over the IP networks of high-performance that can be transferred quickly and must be configured quickly. This paper, by using an optional encryption method to complement a QoS and security of public network, suggests high speed and secure content transmission protocol such as VPN(Virtual Private Network) for large video files and big data. As configured high performance VPN, end to end devices use the best of available resources over public network by parallel transfer protocol and the secure content delivery network.

• Journal of Industrial Convergence
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• v.17 no.4
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• pp.33-38
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• 2019

Regional tourism is an effective means of revitalizing the local economy and improving the image of the region. In order to revitalize this, efforts should be made to create regionally specialized tourism products and to preserve the unique culture and traditions. Among them, gathering information about visitors and securing the quality competitiveness of the contents of tourism contents are very important to increase the potential of cultural tourism festival. This paper collects, refines, and processes the festival-related data in a specific area in order to enhance the visitor's tourism needs and satisfaction. In particular, negative words and positive words raised during the festival were analyzed through big data visualization using word cloud.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.235-241
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• 2011

A large number of industry and trade circulation enterprises integrate logistics resource. They give links of product transport to some professional logistics enterprises in order to reduce costs. We call these professional logistics enterprises as the Third-party Logistics. As the development of the computer and internet, the suppliers, buyers and the Third-party Enterprises connect each other with internet. And different company use different management software, so heterogeneous data become a big problem of the information system for Third-party Enterprises. We built the logistics ontology with prot$\'{e}$g$\'{e}$, and translate it in OWL. We also built the rules for Logistics Ontology to improve the limitations of the OWL. Then we design the intelligent system for 3PL Enterprises Distribution Center based on Logistics Ontology and Logistics Rules. At final, we give an example to show the workflow visually.