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Study on the AI Speaker Security Evaluations and Countermeasure (AI 스피커의 보안성 평가 및 대응방안 연구)

  • Lee, Ji-seop;Kang, Soo-young;Kim, Seung-joo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1523-1537
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    • 2018
  • The AI speaker is a simple operation that provides users with useful functions such as music playback, online search, and so the AI speaker market is growing at a very fast pace. However, AI speakers always wait for the user's voice, which can cause serious problems such as eavesdropping and personal information exposure if exposed to security threats. Therefore, in order to provide overall improved security of all AI speakers, it is necessary to identify potential security threats and analyze them systematically. In this paper, security threat modeling is performed by selecting four products with high market share. Data Flow Diagram, STRIDE and LINDDUN Threat modeling was used to derive a systematic and objective checklist for vulnerability checks. Finally, we proposed a method to improve the security of AI speaker by comparing the vulnerability analysis results and the vulnerability of each product.

Evaluation of the reliability and information quality of YouTube videos on implant overdenture (임플란트 피개의치에 관한 유튜브 영상의 신뢰도 및 질적 평가)

  • Sun-Woo Park;Seon-Ki Lee;Jin-Han Lee;Jae-In Lee
    • The Journal of Korean Academy of Prosthodontics
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    • v.62 no.3
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    • pp.183-192
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    • 2024
  • Purpose. This study aimed to evaluate the reliability and information quality of YouTube videos on implant overdenture searched in two languages (Korean and English). Materials and methods. Youtube, an online video sharing platform was searched using search terms in two different languages related to implant overdenture. A total of 120 videos were selected (60 videos for each search term), then the reliability and information quality of the videos were evaluated. Topic domain, DISCERN instrument, and JAMA benchmark were used to evaluate the reliability and information quality of the videos. Statistical analyses were performed by using the Mann-Whitney U test and Kruskal-Wallis test. Results. Out of a total of 120 videos, the topic domain scores of 78 (65.0%) videos were evaluated as 'poor', and the DISCERN scores of 104.5 (87.1%) videos were evaluated as 'very poor' and 'poor'. The Korean videos had significantly higher topic domain scores and DISCERN scores than the English videos (P < .05). 3.5 Korean videos and 4 English videos met the criteria for attribution of JAMA benchmark. Conclusion. The reliability and information quality of YouTube videos on implant overdenture were low.

A Study upon Online Measurement techniques of Corporate Reputation (기업의 디지털 평판 측정 기법 연구)

  • Kim, Seung-Hee;Kim, Woo-Je;Lee, Kwang-Seok
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.9
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    • pp.139-152
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    • 2013
  • Although a series of studies shows the fact that a company's reputation could affect its sales rate and stock price, due to the increased use of SNS, the research related to the online measurement method for the corporate reputation has been relatively insufficient. This study explores a design for a method to quantify the corporate reputation value by reconstructing the discussions in literature review. Concretely, this study divides the corporate reputation value into the corporate identity information and the corporate awareness information, which includes the following five sub-categories: (1) the quality of product and service; (2) the employment environment; (3) the corporate vision; (4) the social responsibility; and (5) the business achievement. Additionally, for the corporate identity assessment, this study considers the following six factors: (1) Agreeableness (Goodness), (2)Capability (Ability), (3)Enterprise (Rise), (4)Chic (Class), (5) Ruthlessness (Authority), and (6)Informality. Based on these categories and factors, this study develops a technique quantifying the corporate reputation value by selecting 'word items' for the reputation search, and after conducting a frequency analysis in a survey. Also, to verify the result, this study exemplifies the reputation of three SI companies in Korea which could be utilized by using the commercialized reputation service. This study firstly attempts the corporate reputation measurement by classifying the identity and the awareness (corporate image and communication) upon a company in detail and enables its real applicabilities by proposing a formula to measure the reputation scores which can be utilized by verified word items from a frequency analysis.

A Study on Similar Trademark Search Model Using Convolutional Neural Networks (합성곱 신경망(Convolutional Neural Network)을 활용한 지능형 유사상표 검색 모형 개발)

  • Yoon, Jae-Woong;Lee, Suk-Jun;Song, Chil-Yong;Kim, Yeon-Sik;Jung, Mi-Young;Jeong, Sang-Il
    • Management & Information Systems Review
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    • v.38 no.3
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    • pp.55-80
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    • 2019
  • Recently, many companies improving their management performance by building a powerful brand value which is recognized for trademark rights. However, as growing up the size of online commerce market, the infringement of trademark rights is increasing. According to various studies and reports, cases of foreign and domestic companies infringing on their trademark rights are increased. As the manpower and the cost required for the protection of trademark are enormous, small and medium enterprises(SMEs) could not conduct preliminary investigations to protect their trademark rights. Besides, due to the trademark image search service does not exist, many domestic companies have a problem that investigating huge amounts of trademarks manually when conducting preliminary investigations to protect their rights of trademark. Therefore, we develop an intelligent similar trademark search model to reduce the manpower and cost for preliminary investigation. To measure the performance of the model which is developed in this study, test data selected by intellectual property experts was used, and the performance of ResNet V1 101 was the highest. The significance of this study is as follows. The experimental results empirically demonstrate that the image classification algorithm shows high performance not only object recognition but also image retrieval. Since the model that developed in this study was learned through actual trademark image data, it is expected that it can be applied in the real industrial environment.

A Study on Public Awareness of Landslide and Check Dam Using the Big Data Platform 'Hyean' (공공 빅데이터 플랫폼 '혜안'을 통한 산사태 및 사방댐 인식 분석)

  • Sohee Park;Min Jeng Kang;Song Eu
    • Journal of the Society of Disaster Information
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    • v.18 no.4
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    • pp.687-698
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    • 2022
  • Purpose: This study was conducted to understand the public awareness of landslide and check dams in 2015-2020 using the big data platform 'Hyean' and to confirm the utilization of this platform in disaster prevention areas. Method: The total amount, number of detection by period by media, and affirmative and negative trends of a search for 'landslide' and 'check dam' in 2015-2020 were analyzed using a keyword search of 'Hyean.' Result: There is significant lack of public awareness of check dam compared to landslide, and the trend is more noticeable in the conspicuous gap of data amount between the news and SNS media. The number and the timing of the search for 'landslide' coincided with the actual occurrence of landslide, while the detection of 'check dam' was less related to it. Relatively affirmative preception for the check dam is inferred, but it was difficult to confirm accurate statistical affirmative and negative trends in the disaster prevention field using 'Hyean.' Conclusion: Unlike the experts who expect positive public awareness of check dam, the statistic results show that the public awareness of the check dam as an effective countermeasure against landslide was extremely low. Active promotion of erosion control projects should be carried out first, and a balanced sample survey should accompany online and periodic field surveys. Since there is a limit to grasping the effective perception in the field of disaster prevention area using 'Hyean', it should be very cautious to establish local/governmental policies using it.

Multi-day Trip Planning System with Collaborative Recommendation (협업적 추천 기반의 여행 계획 시스템)

  • Aprilia, Priska;Oh, Kyeong-Jin;Hong, Myung-Duk;Ga, Myeong-Hyeon;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.159-185
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    • 2016
  • Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.

A Review Study of Researches on Acupuncture Therapy to Pregnant Women (임산부의 침치료에 대한 국내외 연구동향 분석)

  • Ryu, Soo-Hyeong;Park, Kang-In;Kim, Jin-Woo;Park, Kyoung-Sun;Lee, Jin-Moo
    • The Journal of Korean Obstetrics and Gynecology
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    • v.26 no.4
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    • pp.107-122
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    • 2013
  • Objectives: This study was conducted to investigate the effectiveness and safety of acupuncture therapy for pregnant women. Researches on acupuncture therapy for pregnant women published since 2000 until 2013 were selected and analyzed. Methods: Bibliographic search was carried out using several online database systems using keywords like 'pregnancy', 'pregnant', 'acupuncture', 'forbidden points' within a 13-year time span (2000-2013). Results: 18 journal articles published in Korea and 22 journal articles published abroad were selected. It is reported that acupuncture has significant effect on low back pain and pelvic pain, depression, insomnia during pregnancy. Stimulation of acupuncture during pregnancy seems to be safe with respect to obstetric adverse effects. Conclusions: We can conclude that further investigation is needed to accumulate enough information to establish evidence for acupuncture therapy for pregnant women.

Elementary School Teachers' Use of Visual Representations and their Perceptions of the Functions of Visual Representations (초등교사의 시각적 표상 활용 실태 및 시각적 표상의 기능에 대한 인식)

  • Yoon, Hye-Gyoung;Park, Jisun
    • Journal of Korean Elementary Science Education
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    • v.37 no.2
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    • pp.219-231
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    • 2018
  • This study surveyed the elementary school teachers' use of visual representations and their perceptions of the functions of visual representations in the teaching of electricity unit. A total of 110 elementary teachers who have experiences in teaching electricity unit responded to online survey. The result showed firstly that most of the teachers use visual representations in their teaching and it is mostly limited to those presented in textbooks or images that they can get easily from internet search. Secondly, elementary teachers thought that they have high ability in using visual representations and low ability in understanding students' visual presentation ability. Thirdly, visual representations are more often preferred to be used as teacher-centered ways than student-centered ways for motivating students and conceptual understanding. However, in case of scientific inquiry, both teacher-centered and student-centered ways were equally preferred. Lastly, the teachers' perceptions of the functions of visual representations were categorized into 'teaching-instrumental function', 'learning-instrumental function', 'communicative-instrumental function' and 8 subcategories were found. The most frequent function was the 'information delivery function' in the 'teaching-instrumental function' category. Implications for teacher education and further studies were discussed.

A Study on the Selection Attributes for Restaurant, Customer Satisfaction, and Recommendation Intention on Traveling Domestic Tourists: Targeting Tourists for Rail-ro Tickets

  • Kim, Ju-Hee;Kang, Kyoung-Ku;Lee, Jong-Ho
    • Culinary science and hospitality research
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    • v.23 no.6
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    • pp.27-35
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    • 2017
  • The purpose of this study was to examine the causal relationship among restaurant selection attributes and customer satisfaction and recommendation tastes for young people in their twenties who use tickets for Rail-ro. Data collection was conducted to utilize questionnaire survey with online and offline distribution. The collected data were analyzed using a statistical program SPSS 21.0 with frequency analysis, reliability analysis, factor analysis, and regression analysis. The results of the study showed that Internet search is the most common source of information about restaurants during the trip, and restaurant choice attributes have an important impact on customer satisfaction, food quality, employee service and reputation, but hygiene did not have a big effect on customer satisfaction. In addition, customer satisfaction has a significant effect on recommendation intention. Concluding the results from this study, it investigated the significant attributes for customers selection of restaurants and provide meaningful advice for market managers to make useful marketing strategies to attract more clients and augment economic benefits.

Study On the Object Oriented Design Project of Online Game Engine Using UML (UML을 사용한 온라인 게임 엔진 프로젝트 설계 연구)

  • Choi, Sung
    • Journal of Korea Game Society
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    • v.5 no.1
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    • pp.33-40
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    • 2005
  • Game Designs & Developers that system designs improve, the product and the change of tasks to all developers are essential in achieving On-Line Game project. Existent Or-line Game project management designs supper the definition and the change of project activities, and configuration management designs support version check, workspace management, build management, etc. In this paper. the proposed Design defines Game component based development process model, and achieves recording of process progression, processing the request of change, reporting the progression of each task, product registering and change, version recording, artifact or form search, etc. using UML. Furthermore, study on the stake holders get the systematic management and standardization by sharing information that are necessary in Game design & development and configuration management in distributed environment using the system integrated management design.

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