• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.59-66
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• 2002

The rapid change of industrial structure causes to increase distribution cost and requires necessity of physical distribution system urgently. Traffic situation is getting extremely worse and traffic jam has led to increasing expense of physical distribution delivery which dominates 20% of distribution cost. In this situation, the shortest and most suitable path search system is required by modern people who must waste a lot of time for moving with a car or on the street as well as many companies. for these reasons, we developed the shortest-path-searching system applying the dijkstra algorithm which is one of the effective shortest path algorithm to GIS, and it was constructed by considering realistic urban traffic and the pattern of street in a physical situation. Also, this system was developed to be updated weight data automatically, considering the dynamic change of traffic situation such as a traffic information service which will be served in real time. Finally, we designed this system to serve on web by using MapObjects IMS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.146-147
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• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• Journal of Biomedical Engineering Research
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• v.27 no.5
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• pp.250-259
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• 2006

The information of eye movement is used in various fields such as psychology, ophthalmology, physiology, rehabilitation medicine, web design, HMI(human-machine interface), and so on. Various devices to detect the eye movement have been developed but they are too expensive. The general methods of eye movement tracking are EOG(electro-oculograph), Purkinje image tracker, scleral search coil technique, and video-oculograph(VOG). The purpose of this study is to embody the algorithm which tracks the location of the gazing point at a pupil. Two kinds of location data were compared to track the gazing point. One is the reference points(infrared LEDs) which is effected from the globe. Another is the center point of the pupil which is gained with a CCD camera. The reference point was captured with the CCD camera and infrared lights which were not recognized by human eyes. Both of images which were thrown and were not thrown an infrared light on the globe were captured and saved. The reflected reference points were detected with the brightness difference between the two saved images. In conclusion, the circumcenter theory of a triangle was used to look for the center of the pupil. The location of the gazing point was relatively indicated with the each center of the pupil and the reference point.

• The korean journal of orthodontics
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• v.52 no.3
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• pp.182-200
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• 2022

Objective: This study aims to examine the effectiveness of miniscrew assisted rapid palatal expansion (MARPE) treatment in late adolescents and adult patients using cone-beam computed tomography (CBCT). Methods: Literature search was conducted in five electronic databases (PubMed, Embase, Scopus, Web of Science, and Cochrane Library) based on the PICOS keyword design focusing on MARPE. Out of the 18 CBCT screened outcomes, only nine parameters were sufficient for the quantitative meta-analysis. The parameters were classified into three main groups: 1) skeletal changes, 2) alveolar change, and 3) dental changes. Heterogeneity test, estimation of pooled means, publication bias, sensitivity analysis and risk of bias assessment were also performed. Results: Upon database searching, only 14 full-text articles were qualified from the 364 obtained results. Heterogeneity test indicated the use of the random-effects model. The pooled mean estimate were as follows: 1) Skeletal expansion: zygomatic width, 2.39 mm; nasal width, 2.68 mm; jugular width, 3.12 mm; and midpalatal suture at the posterior nasal spine and anterior nasal spine, 3.34 mm and 4.56 mm, respectively; 2) Alveolar molar width expansion, 4.80 mm; and 3) Dental expansion: inter-canine width, 3.96 mm; inter-premolar width, 4.99 mm and inter-molar width, 5.99 mm. The percentage of expansion demonstrated a skeletal expansion (PNS) of 55.76%, alveolar molar width expansion of 24.37% and dental expansion of 19.87%. Conclusions: In the coronal view, the skeletal and dental expansion created by MARPE was of the pyramidal pattern. MARPE could successfully expand the constricted maxilla in late adolescents and adult patients.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.1-6
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• 2023

Morphological analysis is a branch of natural language processing, is now a rapidly growing field. The fundamental tenet of morphological analysis is that it can establish the roots or stems of words and enable comparison to the original term. Arabic is a highly inflected and derivational language and it has a strong structure. Each root or stem can have a large number of affixes attached to it due to the non-concatenative nature of Arabic morphology, increasing the number of possible inflected words that can be created. Accurate verb recognition and extraction are necessary nearly all issues in well-known study topics include Web Search, Information Retrieval, Machine Translation, Question Answering and so forth. in this work we have designed and implemented an algorithm to detect and recognize Arbic Verbs from Arabic text.The suggested technique was created with "Python" and the "pyqt5" visual package, allowing for quick modification and easy addition of new patterns. We employed 17 alternative patterns to represent all verbs in terms of singular, plural, masculine, and feminine pronouns as well as past, present, and imperative verb tenses. All of the verbs that matched these patterns were used when a verb has a root, and the outcomes were reliable. The approach is able to recognize all verbs with the same structure without requiring any alterations to the code or design. The verbs that are not recognized by our method have no antecedents in the Arabic roots. According to our work, the strategy can rapidly and precisely identify verbs with roots, but it cannot be used to identify verbs that are not in the Arabic language. We advise employing a hybrid approach that combines many principles as a result.

• The Journal of Advanced Prosthodontics
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• v.15 no.6
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• pp.315-332
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• 2023

PURPOSE. This study aimed to investigate whether the accuracy of intraoral scanners is influenced by different scanning strategies in an in vitro setting, through a systematic review and meta-analysis. MATERIALS AND METHODS. This review was conducted in accordance with the PRISMA 2020 standard. The following PICOS approach was used: population, tooth impressions; intervention, the use of intraoral scanners with scanning strategies different from the manufacturer's instructions; control, the use of intraoral scanners following the manufacturers' requirements; outcome, accuracy of intraoral scanners; type of studies, in vitro. A comprehensive literature search was conducted across various databases including Embase, SciELO, PubMed, Scopus, and Web of Science. The inclusion criteria were based on in vitro studies that reported the accuracy of digital impressions using intraoral scanners. Analysis was performed using Review Manager software (version 5.3.5; Cochrane Collaboration, Copenhagen, Denmark). Global comparisons were made using a standardized mean difference based on random-effect models, with a significance level of α = 0.05. RESULTS. The meta-analysis included 15 articles. Digital impression accuracy significantly improved under dry conditions (P < 0.001). Moreover, trueness and precision were enhanced when artificial landmarks were used (P ≤ 0.02) and when an S-shaped pattern was followed (P ≤ 0.01). However, the type of light used did not have a significant impact on the accuracy of the digital intraoral scanners (P ≥ 0.16). CONCLUSION. The accuracy of digital intraoral scanners can be enhanced by employing scanning processes using artificial landmarks and digital impressions under dry conditions.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.258-266
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• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.25-38
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• 2013

Future wireless systems will be required to support the increasingly nomadic lifestyle of people. This support will be provided through the use of multiple overlaid networks which have very different characteristics. Moreover, these networks will be required to support the seamless delivery of today's popular desktop services, such as web browsing, interactive multimedia and video conferencing to the mobile devices. Thus one of the major challenges in the design of these mobile systems will be the provision of the quality of service (QoS) guarantees that the applications demand under this diverse networking infrastructure. We believe that it is necessary to use resource reservation and adaptation techniques to deliver these QoS guarantee to applications. However, reservation and pre-configuration in the entire service region is overly aggressive, and results in schemes that are extremely inefficient and unreliable. To overcome this, the mobility pattern of a user can be exploited. If the movement of a user is known, the reservation and configuration procedure can be limited to the regions of the network a user is likely to visit. Our proposed Proxy-UMP is not sensitive to increase of the search cost than other schemes and shows that the increasing rate of total cost is low as the SMR increases.

• Journal of Popular Narrative
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• v.25 no.3
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• pp.303-345
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• 2019

This article analyzes the multi-layered communication in the Webtoon Princess Pari, released on the Daum portal site, created (written and illustrated) by Kim Naim, through analyzing the narrative structure and comments with the qualitative / quantitative methodology. The webtoon Princess Pari is structured in an omnibus style in which unit narratives are intermittently articulated, multi-lined, and interconnected. As integrated narratives which link with unitary narratives, Pari's growth story as a shaman and a romance narrative are structured. The classical original story of the shaman was used as a prehistory corresponding to the prequel of the webtoon through a preview, and the writer restructured the narrative to overcome the contradictions of the gender asymmetry and the patriarchal ideology of the original text. The viewer then creates a conversational space by giving critical and reflective comments. According to a statistical analysis conducted through sampling, the types of comments can be classified as follows: Appreciation and criticism of the contents ≫ Emotional response ≫ Intuitive overall review ≫ Knowledge and reflection ≫ Comments on comments. In the process of creation and acceptance of the Webtoon, a multi-layered dialogue between classical and modern, content and audience, acceptance and creation has been at play. In the creation dimension, the writer used a device to fill the gap of mythical symbols of the contents. At the level of the audience, they formed a culture of sharing information, knowledge, and reflection about tradition/folk/culture through comments. This corresponds to classical and modern dialogue through the webtoon. The viewers form a sympathetic bond, attempt hermeneutical coordination, supplement the information, and search for a balanced angle through controversial conversation. In addition, by commenting on attitudes, views, and perspective, the commentators showed a behavioral pattern corresponding to meta-criticism in literature. The viewers' comments acted as feedback on the creation of the webtoons, so that the creation and acceptance itself influenced the production of the content of the webtoon. The webtoon Princess Pari, which was based on Korean classical narrative, has been reorganized onto 'moving and dynamic' content, which leads to sense, thinking, criticism and reflection through the formation of various dialogues.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.