• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.26 no.3
• /
• pp.291-314
• /
• 2015

This study aims to look at overall adolescents' and college students' perceptions of library and explore the sources and their related variables as well as find out related issues of perceptions of library and information use of them. The data for this study were collected through survey and analyzed descriptive statistics and correlation analysis using the data. The result shows the population users preferred search engine so much over library as their information search tool even if they trust library information sources more, also, they tend to seek information sources when it has easiness and fastness to get. Correlation analysis such as ${\chi}^2$ and Spearman were implemented and the result of the correlation shows that many factors of this study covered-such as comparison of information sources-have significant differences each other.

• The Journal of Industrial Distribution & Business
• /
• v.8 no.6
• /
• pp.7-16
• /
• 2017

Purpose - Today's world revolves around search engines which are the driving force behind any marketer. The thirst for marketing has led to the evolution of online 'Pay per click' over last few years and is the most widely used instrument. Research design, data, and methodology - Exploratory research design highlights many marketing variables getting affected by pay per click marketing. To analyze the said phenomenon, the data was gathered through questionnaire from the sample of 338 respondents which were selected by simple random sampling method mostly from the National Capital Region (NCR) of Delhi in India. The data collected from the respondents was loaded on SAS base for exploratory factor analysis and multiple regression analysis. Results - Pay per click as a marketing tool has significant impact on the consumers. The most prominent factors of pay per click marketing identified in the research are Ad quality, Competition, Targeting, Trend and Budget. Conclusions - Organic as well as inorganic ads, keeping in mind the end goal to gage the exchange of these two postings in the marked look territory. Additionally, here we dissected supported pursuit promotions in all. It would be beneficial to break down the impact of promotion position on the pay per click marketing.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.2
• /
• pp.14-24
• /
• 2020

Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade's biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.2
• /
• pp.92-98
• /
• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

• Journal of dental hygiene science
• /
• v.21 no.2
• /
• pp.104-110
• /
• 2021

Background: Regardless of countries, the myth that rain makes the body ache has been worded in various forms, and a number of studies have been reported to investigate this. However, these studies, which depended on the patient's experience or memory, had obvious limitations. Google Trends is a big data analysis service based on search terms and viewing videos provided by Google LLC, and attempts to use it in various fields are continuing. In this study, we endeavored to introduce the 'value as a research tool' of the Google Trends, that has emerged along with technological advancements, through research on 'whether toothaches really occur frequently on rainy days'. Methods: Keywords were selected as objectively as possible by applying web crawling and text mining techniques, and the keyword "bi" meaning rain in Korean was added to verify the reliability of Google Trends data. The correlation was statistically analyzed using precipitation and temperature data provided by the Korea Meteorological Agency and daily search volume data provided by Google Trends. Results: Keywords "chi-gwa", "chi-tong", and "chung-chi" were selected, which in Korean mean 'dental clinic', 'toothache', and 'tooth decay' respectively. A significant correlation was found between the amount of precipitation and the search volume of tooth decay. No correlation was found between precipitation and other keywords or other combinations. It was natural that a very significant correlation was found between the amount of precipitation, temperature, and the search volume of "bi". Conclusion: Rain seems to actually be a cause of toothache, and if objective keyword selection is premised, Google Trends is considered to be very useful as a research tool in the future.

• Journal of Korean Society of Forest Science
• /
• v.96 no.5
• /
• pp.510-514
• /
• 2007

The main purpose of this study was to develop Mountain Search and Rescue System for enhancing search and rescue operations in the mountains. This study also focused on presenting an alternative to using a cellular phone for requesting rescue due to their unreliability in remote areas. This system is designed to help in the search and rescue of people in emergency situations in the mountains. It is composed of buzzer sensors, environmental information sensors, and a statistical analysis program. A key feature of this system is that it does not require an infrastructure of internet or CDMA networks for its operation in the mountains. The measure for the study was conducted by using a zigbee protocol analyzer, RF module and 433MHz Helical antenna to analyze the rate of data reception in relation to the distance between nodes. This system is applicable to mountains provided the distance between nodes is over 100 m and under 150 m.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.2
• /
• pp.179-184
• /
• 2024

Franchise are now a red ocean in Food industry and they need to find other options to appeal for their product, the uprising content, food tech. The franchises are working on R&D to help franchisees with the operations. Through this paper, we analyze the franchise interest on food tech and to help find the necessity of development for franchisees who are in needs with hand, not of human, but of technology. Using Textom, a big data analysis tool, "franchise" and "food tech" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 01 January, 2023 to 31 December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "food tech" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, a total of 10,049 words were derived, and among them, the top 50 keywords with the highest relevance and search frequency were selected and applied to this study. The top 50 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. By using big data analysis, it was found out that franchise do have interest on food tech. "technology", "franchise", "robots" showed many interests and keyword "R&D" showed that franchise are keen on developing food tech to seize competitiveness in Franchise Industry.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.75-78
• /
• 1997

In this paper we present new sound spectral analysis methods or prosthetic heart valve sounds. Phonocardiograms(PCG) of prosthetic heart valve were analyzed in order to derive frequency domain feature suitable or the classification of the valve state. The fast orthogonal search method and MUSIC (MUltiple SIgnal Classification) method are described or finding the significant frequencies in PCG. The fast orthogonal search method is effective with short data records and cope with noisy, missing and unequally-spaced data. MUSIC method's key to the performance is the division of the information in the autocorrelation matrix or the data matrix into two vector subspaces, one a signal subspace and the other a noise subspace.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.44-49
• /
• 2020

Recently, one of the major issues of shipbuilding and marine is the reduction of air and marine pollution emission to ships. In response, the International Maritime Organization (IMO) has concluded an international convention (MARPOL) to prevent pollution from ships. A Annex Six of The Convention restricts and regulates air and marine pollution of ship from exhausting gases. To this end, it is required to apply EEDI (Energy Efficiency Design Indicators) to the construction of new ships, and to minimize the emission of environmental pollutants by recommending the application of EEOI (Energy Efficiency Operation Indicators) to operational ships. Therefore, in this study, we propose to calculate the grade of operating efficiency (EG) of ships based on actual operational data for transport ships and to provide energy-efficient optimal path search information through analysis of marine environment data.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.36 no.1
• /
• pp.57-68
• /
• 2011

This paper examines how multiple performance feedbacks influence firm's technological search, using two types of indicators : accounting-based performance and market-based performance. Also we investigate how CEO's attention shift depends on firm specific factors such as firm size and outsider ownership. For empirical analysis, we utilized financial data on 675 manufacturing firms in Korea during the period between 1998 and 2009. The results show that technological search based on accounting-based performance feedback is moderated by focal firm's size. However, as outsider ownership increases, technological search increases in response to market-based performance feedback.