• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.77-86
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• 2018

For the past few years, KISTI has been servicing an online simulation execution platform, called EDISON, allowing users to conduct simulations on various scientific applications supplied by diverse computational science and engineering disciplines. Typically, these simulations accompany large-scale computation and accordingly produce a huge volume of output data. One critical issue arising when conducting those simulations on an online platform stems from the fact that a number of users simultaneously submit to the platform their simulation requests (or jobs) with the same (or almost unchanging) input parameters or files, resulting in charging a significant burden on the platform. In other words, the same computing jobs lead to duplicate consumption computing and storage resources at an undesirably fast pace. To overcome excessive resource usage by such identical simulation requests, in this paper we introduce a novel framework, called IceSheet, to efficiently manage simulation data based on execution metadata, that is, provenance. The IceSheet framework captures and stores each provenance associated with a conducted simulation. The collected provenance records are utilized for not only inspecting duplicate simulation requests but also performing search on existing simulation results via an open-source search engine, ElasticSearch. In particular, this paper elaborates on the core components in the IceSheet framework to support the search and reuse on the stored simulation results. We implemented as prototype the proposed framework using the engine in conjunction with the online simulation execution platform. Our evaluation of the framework was performed on the real simulation execution-provenance records collected on the platform. Once the prototyped IceSheet framework fully functions with the platform, users can quickly search for past parameter values entered into desired simulation software and receive existing results on the same input parameter values on the software if any. Therefore, we expect that the proposed framework contributes to eliminating duplicate resource consumption and significantly reducing execution time on the same requests as previously-executed simulations.

• Korean Journal of Oriental Medicine
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• v.11 no.2
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• pp.53-66
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• 2005

This study is concerned with the patentability and protection of intellectual property rights in Traditional Korea Medicine Paper. The results analyzed significance of patentability by investigated for many kinds of Traditional Korea Medicine Paper. It provide extension of intellectual property rights protection and further research region of TKM field by analysing information of patentability. Recently, In the protection of intellectual property rights, the importance of traditional knowledge resource in many country is increased. It will predict the number of apply for the patent increased annually This study will be provide judging guideline and strategy of intellectual property rights protection by search to detect all existing similar patents in Patent Office (Korea, Japan, U.S.A. EPO) about Traditional Korea Medicine Paper. As a result, It can not be investigated about 33% because of paper research or theoretical study or question investigation etc. But the case of 'The Korea Association of Herbology' and 'The Korean Oriental Medical Ophthalmology & Otolaryngology & Dematology Society' have about 10% rate. If it will be constructed DB system, they will be protected by national treatment.

• Journal of Korean Library and Information Science Society
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• v.32 no.3
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• pp.397-417
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• 2001

The purpose of this study is to suggest the guidelines for developing the effective classification scheme of woman studies on the Internet. In order to do that, fuve search engines and three subject web databases are analyzed based on the characteristics, problems of their classification schemes. In addition their classification schemes are measured in terms of coverage of subject fields and systematic logic. The results suggest the guidelines far classification scheme reflecting the characteristics of women's studies that ice interdisciplinary and multidisciplinary fields.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.2 s.332
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• pp.1-8
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• 2005

We have implemented a Jini-Agent system which enables resource-limited mobile devices to utilize the Jini connection service. The Jini-Agent system supports Jini connection technologies to mobile devices without additional client program installation in it. It also supports a dynamic service list which helps the mobile devices to search and to utilize the services through web browser in real time. A couple of examples such as a file search service and a print service with mobile devices have been demonstrated by using the Jini-Agent system.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1310-1317
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• 2014

In our daily life, the need of energy increases day by day. However, the amount of natural resources on the earth is limited and thus gaining renewable energy as an energy resource is one of the important and urgent problems. Solar energy is one of the most popular available energy sources that can be converted into electricity by using solar panels. In order for solar panels to produce maximal output power, the incident angle of the sunlight needs to be persistently perpendicular to the solar panel. By the way, most of the solar panels are installed at fixed position and direction. Therefore, as the sun's position changes, it is impossible to produce maximal output power inevitably. To improve this problem, in this paper, a sun tracking system using two degree-of-freedom (DOF) active sensor array is proposed so that the solar panel may always direct sunlight perpendicularly. And also a series of software, such as a search mode and a holding mode, which can control the developed sun tracking system is developed. Several experiments using the implemented sun tracking system are executed and the effectiveness of the system is verified from the experimental results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.639-640
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• 2006

Many companies in mechanical engineering fields have accumulated information of design and manufacturing. The Enterprise Resource Planning (ERP) and Product Data Management (PDM) systems help information gathering and data managing. However, these systems are not flexible to support suitable functionality for specific product because these systems deal with entire enterprise resources. To cope with this issue, a web-based design support system was constructed for the design process of automotive steel pulley. This system provided 1) search service for part design with key word and clustering map, and 2) estimation service of maximum stress. These services reduced design time by reducing iterative jobs with Computer Aided Design (CAD) and Computer Aided Engineering (CAE) for stress analysis, and by enhancing search for existing data of steel pulley.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.6-11
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• 2020

In today's world, the design industry is becoming more complex, with the development of networks such as the internet and revolutionary changes in information and telecommunications. As the demand for designers to cope with various situations occurring in these industrial sites or solve problems in practice promptly is required, a capstone design program was developed in collaboration with the industry. Capstone design classes have positive effects on creative problem solving ability, academic achievement and learning satisfaction by allowing students to think and experience the practical problems of the industrial field. It is also effective in improving communication, creative thinking and critical thinking. The purpose of this study is to search for talent training methods needed in the fashion industry and to develop effective programs through capstone design class studies conducted in the fourth grade of fashion design majors from 2017 to 2019 (6 semesters). Through these studies, the aim is to search for talent training methods needed in the fashion industry and to develop effective programs. If the capstone design learning method is used as a method of solving problems through close communication between the company and the educational field as an industry-academia cooperation system, it is expected to be positioned as a field-type human resource education method that is required in the industrial field.

• Geomechanics and Engineering
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• v.18 no.5
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• pp.493-502
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• 2019

Internal stability is an important safety issue for levees, embankments, and other earthen structures. Since a large part of the world's population lives near oceans, lakes and rivers, floods resulting from breaching of dams can lead to devastating disasters with tremendous loss of life and property, especially in densely populated areas. There are some main factors that affect the internal stability of dams, levees and other earthen structures, such as the erodibility of the soil, the water velocity inside the soil mass and the geometry of the earthen structure, etc. Thus, the mechanism of internal erosion and stability of soils is very complicated and it is vital to investigate the assessment methods of internal stability of soils in embankment dams and their foundations. This paper presents an improved support vector machine (SVM) model to predict the internal stability of soils. The grid search algorithm (GSA) is employed to find the optimal parameters of SVM firstly, and then the cross - validation (CV) method is employed to estimate the classification accuracy of the GSA-SVM model. Two examples of internal stability of soils are presented to validate the predictive capability of the proposed GSA-SVM model. In addition to verify the effectiveness of the proposed GSA-SVM model, the predictions from the proposed GSA-SVM model were compared with those from the traditional back propagation neural network (BPNN) model. The results showed that the proposed GSA-SVM model is a feasible and efficient tool for assessing the internal stability of soils with high accuracy.

• ETRI Journal
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• v.44 no.5
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• pp.746-758
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• 2022

This paper focuses on a mobile edge-computing-enabled heterogeneous network. A battery level-aware task-scheduling framework is proposed to improve the energy efficiency and prolong the operating hours of battery-powered mobile devices. The formulated optimization problem is a typical mixed-integer nonlinear programming problem. To solve this nondeterministic polynomial (NP)-hard problem, a decomposition-based task-scheduling algorithm is proposed. Using an alternating optimization technology, the original problem is divided into three subproblems. In the outer loop, task offloading decisions are yielded using a pruning search algorithm for the task offloading subproblem. In the inner loop, closed-form solutions for computational resource allocation subproblems are derived using the Lagrangian multiplier method. Then, it is proven that the transmitted power-allocation subproblem is a unimodal problem; this subproblem is solved using a gradient-based bisection search algorithm. The simulation results demonstrate that the proposed framework achieves better energy efficiency than other frameworks. Additionally, the impact of the battery level-aware scheme on the operating hours of battery-powered mobile devices is also investigated.