• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.346-356
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• 2022

The jurisprudential legal rules govern the way Muslims react and interact to daily life. This creates a huge stream of questions, that require highly qualified and well-educated individuals, called Muftis. With Muslims representing almost 25% of the planet population, and the scarcity of qualified Muftis, this creates a demand supply problem calling for Automation solutions. This motivates the application of Artificial Intelligence (AI) to solve this problem, which requires a well-designed Question-Answering (QA) system to solve it. In this work, we propose a QA system, based on retrieval augmented generative transformer model for jurisprudential legal question. The main idea in the proposed architecture is the leverage of both state-of-the art transformer models, and the existing knowledge base of legal sources and question-answers. With the sensitivity of the domain in mind, due to its importance in Muslims daily lives, our design balances between exploitation of knowledge bases, and exploration provided by the generative transformer models. We collect a custom data set of 850,000 entries, that includes the question, answer, and category of the question. Our evaluation methodology is based on both quantitative and qualitative methods. We use metrics like BERTScore and METEOR to evaluate the precision and recall of the system. We also provide many qualitative results that show the quality of the generated answers, and how relevant they are to the asked questions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4084-4104
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• 2021

Visual place recognition (VPR) is a fundamental yet challenging task of mobile robot navigation and localization. The existing VPR methods are usually based on some pairwise similarity of image descriptors, so they are sensitive to visual appearance change and also computationally expensive. This paper proposes a simple yet effective four-step method that achieves adaptive convolutional neural network (CNN) landmark matching for VPR. First, based on the features extracted from existing CNN models, the regions with higher significance scores are selected as landmarks. Then, according to the coordinate positions of potential landmarks, landmark matching is improved by removing mismatched landmark pairs. Finally, considering the significance scores obtained in the first step, robust image retrieval is performed based on adaptive landmark matching, and it gives more weight to the landmark matching pairs with higher significance scores. To verify the efficiency and robustness of the proposed method, evaluations are conducted on standard benchmark datasets. The experimental results indicate that the proposed method reduces the feature representation space of place images by more than 75% with negligible loss in recognition precision. Also, it achieves a fast matching speed in similarity calculation, satisfying the real-time requirement.

• The Journal of Korean Obstetrics and Gynecology
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• v.36 no.3
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• pp.25-45
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• 2023

Objectives: The purpose of this study is to review the clinical research trends of ovarian cysts and to recognize the efficacy of Korean medicine intervention. Methods: Based on four domestic databases, including Korean studies Information Service System (KISS), Oriental Medicine Advanced Searching Integrated System (OASIS), Korean Medical Database (KMbase) and Research Information Sharing Service (RISS), we analyzed the case reports using Korean medicine intervention, which include acupuncture, moxibustion and herbal medicine. Data retrieval was carried out from May 12^th, to 18^th, 2022, and a total of 9 papers were included. Results: All papers were published in Korea and they contain seventeen case reports in total. The most frequently used intervention was herbal medicine, especially Gyejibokryeong-hwan-gami (桂枝茯苓丸加味), Guichulpajing-tang-gagam (歸朮破癥湯加減), Guibiondam-tang-gami (歸脾溫膽湯加味). Most cases reported statistically significant results on using Korean-medicine intervention. Also, there was no serious side effect of Korean medicine. Conclusions: In this study, we investigated the efficacy of Korean medicine intervention as an adjuvant therapy for ovarian cyst patients and research trends on ovarian cysts. Further studies are needed to supplement the safety and the evaluation of Korean medicine. However, the results should be taken cautiously as more clinical studies are needed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.52-54
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• 2021

With the advent of the era of artificial intelligence, robot education and teaching under its empowerment have been widely concerned and applied worldwide. The purpose of this study: systematically evaluate the application effect of AI educational robots in student education and teaching; the method of this study: use the computer to search for relevant education in the search tools such as "Web of Science", "CNKI", "ERIC", "IEEE" A comparative study of the effects of robot teaching and traditional teaching. The retrieval time is from January 2000 to January 2020. Comprehensive MetaAnalysis 2.0 was used for Meta analysis. The results of this study: A quantitative analysis of the 31 valid research literatures included, and an objective evaluation of the effect of the meta-analysis on AI educational robots. The analysis results show that the combined effect of AI educational robots on student learning effects is 0.465 This indicates that educational robots have a moderately positive effect on students 'learning effectiveness. The conclusion of this study: The application effect of AI educational robots in student education and teaching is better than traditional education methods, which can better promote student learning.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.311-318
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• 2024

As the amount of data increases due to the development of artificial intelligence and the Internet, data management is becoming increasingly important, and the efficient utilization of data retrieval and memory space is crucial. In this study, we investigate how to optimize search speed and memory efficiency by analyzing data structure based on metadata. As a research method, we compared and analyzed the performance of the array, association list, dictionary binary tree, and graph data structures using metadata of photographic images, focusing on temporal and space complexity. Through experimentation, it was confirmed that dictionary data structure performs best in collection speed and graph data structure performs best in search speed when dealing with large-scale image data. We expect the results of this paper to provide practical guidelines for selecting data structures to optimize search speed and memory efficiency for the images data.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.44-58
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• 2014

In this study, a standard vector data model was developed for interoperability of river-geospatial information and for verification purpose the applicability of the standard vector model was evaluated using a model to RIMGIS vector data at Changnyeong-Hapcheon & Gangjung-Goryeong irrigation watershed. The standards from ISO and OGC were analyzed and the river geospatial data model standard was established by applying the standards. The ERD was designed based on the analysis information on data characteristics and relationship. The verification of RIMGIS vector data included points, lines and polygon to develope GDM was carried out by comparing with the data by layer. This conducting comparison of basic spatial data and attribute data to each record and spatial information vertex. The error in the process of conversion was 0 %, indicating no problem with model. Our Geospatial Data Model presented in this study provides a new and consistent format for the storage and retrieval of river geospatial data from connected database. It is designed to facilitators integrated analysis of large data sets collected by multiple institutes.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.754-758
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• 2009

Extracting information in large-scale documents would be very useful not only for information retrieval but also for question answering and summarization. Even though relation extraction is very important area, it is difficult to develop and evaluate a machine learning based system without test collection. The study shows how to build test collection(KREC2008) for the relation extraction system. We extracted technology terms from abstracts of journals and selected several relation candidates between them using Wordnet. Judges who were well trained in evaluation process assigned a relation from candidates. The process provides the method with which even non-experts are able to build test collection easily. KREC2008 are open to the public for researchers and developers and will be utilized for development and evaluation of relation extraction system.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.23-35
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• 2007

With the development of semantic web technologies in information retrieval area, the necessity for thesaurus is recently increasing along with internet lexicons. A thesaurus is the combination of classification and a lexicon, and is the topic map of knowledge structure expressing relations among concepts(terms) subject to human knowledge activities such as learning and research using formally organized and controlled index terms for clarifying the context of superordinate and subordinate concepts. However, although thesaurus are regarded as essential tools for controlling and standardizing terms and searching and processing information efficiently, we do not have a Korean thesaurus for geology. To build a thesaurus, we need standardized and well-defined guidelines. The standardized guidelines enable efficient information management and help information users use correct information easily and conveniently. The present study purposed to build a thesaurus system with terms used in geology. For this, First, we surveyed related works for standardizing geological terms in Korea and other countries. Second, we defined geological topics in 15 areas and prepared a classification system(draft) for each topic. Third, based on the geological thesaurus classification system, we created the specification of geological thesaurus. Lastly, we designed and implemented an internet-based geological thesaurus system using the specification.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.133-159
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• 2016

The purpose of this study is to analyze related studies and domestic/international online reference cases, extract obstructive factors present in online reference services, and reveal whether or not there are differences in perception between the university librarian and the users. The results with respect to the failure of the resources revealed that while the user considers the quantitative / qualitative shortage of content as the greatest obstacle in the online reference service, librarians see the lack of human resources (Specialist Librarian / trained staff) in this light. Users think this is the least of the problems. In addition, other obstacles that are the most highly evaluated by librarians are, in order, the limitation of service because of copyright issues, the difficulty of information retrieval and complexity of methods of use, and a general lack of information in the reference services menu and missing information in the main menu. For the users the other most important obstacles were similar with the limitation of service because of copyright issues being highest, followed by the difficulty of access because of the confusion over service names, and the general lack of information in the reference services menu and missing information in the main menu.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.179-188
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• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.