• Title/Summary/Keyword: Use of AI

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Correlation analysis between COVID-19 cases and emergency alerts service (COVID-19 확진자 수와 긴급재난문자 서비스의 상관관계 분석)

  • Ju, Sang-Lim;Kang, Hyunjoo;Oh, Seung-Hee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.1-9
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    • 2021
  • In Korea, various information related to COVID-19 has been provided to the public through an EAM (Emergency Alert Message) service using CBS (Cell Broadcast Service) technology to respond to COVID-19. In particular, local governments have been actively using the EAM service as a major means of responding to COVID-19. However, since excessive use of EAM service has caused the inconvenience of the people rather than the positive effects, the authority to be able to send EAMs has be limited. In this paper, with the purpose of providing primary data for establishing a plan to properly operate EAMs, we compare and analyze the number of EAMs issued and the incidence rate of COVID-19 cases during the period from 2020 to the present. In addition, the monthly EAM usage and incidence rate of COVID-19 cases are compared in detail and correlation analysis is performed for local governments that have issued many EAMs. We expect that the analysis results of this paper will be used as primary data in establishing strategies for EAM service to counteract the prolonged COVID-19.

Study on the Selection of Optimal Operation Position Using AI Techniques (인공지능 기법에 의한 최적 운항자세 선정에 관한 연구)

  • Dong-Woo Park
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.6
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    • pp.681-687
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    • 2023
  • The selection technique for optimal operation position selection technique is used to present the initial bow and stern draft with minimum resistance, for achievingthat is, the optimal fuel consumption efficiency at a given operating displacement and speed. The main purpose of this studypaper is to develop a program to select the optimal operating position with maximum energy efficiency under given operating conditions based on the effective power data of the target ship. This program was written as a Python-based GUI (Graphic User Interface) usingbased on artificial intelligence techniques sucho that ship owners could easily use the GUIit. In the process, tThe introduction of the target ship, the collection of effective power data through computational fluid dynamics (CFD), the learning method of the effective power model using deep learning, and the program for presenting the optimal operation position using the deep neural network (DNN) model were specifically explained. Ships are loaded and unloaded for each operation, which changes the cargo load and changes the displacement. The shipowners wants to know the optimal operating position with minimum resistance, that is, maximum energy efficiency, according to the given speed of each displacement. The developed GUI can be installed on the ship's tablet PC and application and used to determineselect the optimal operating position.

A Study on the Build of Equipment Predictive Maintenance Solutions Based on On-device Edge Computer

  • Lee, Yong-Hwan;Suh, Jin-Hyung
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.4
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    • pp.165-172
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    • 2020
  • In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

A Method of Extending a Multiagent Framework with a Plan Generation Module (계획생성 모듈을 갖는 멀티에이전트 기반구조의 확장방법)

  • Lee, Gowang-Lo;Park, Sang-Kyu;Jang, Myong-Wuk;Min, Byung-Eui;Choi, Joong-Min
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.9
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    • pp.2280-2288
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    • 1997
  • An agent is a software element that, by making use of knowledge and inference, performs tasks on behalf of the user. In general, an agent has the properties of autonomy, social ability, reactivity, and durability. Many researches on agents are more and more aiming at the multiagent systems since it is not sufficient to let a single agent do the whole things, especially in a real world where tasks require many diverse activities. However, the multiagent frameworks still have some limitations in the processing of user queries that are often ambiguous and goal-oriented. Also, a series of procedures or plans could not be generated from a single query directly. In order to give more intelligence to the multiagent framework, we propose a method of extending the framework with a plan generation module. The open agent architecture (OAA), which is a multiagent framework that we developed, is integrated with UCPOP, which is a AI planner. A travel schedule management agent (TSMA) system is implemented to explore the effects of the method. The extended system enables the user to only specify goal-oriented queries, and the plans and procedures to satisfy these goals are generated automatically. Also, this system provides a cooperative and knowledge-sharing environment that integrates several knowledge-based systems and planning systems that are distributed and used independently.

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A Study on the Development of Airworthiness Standards for VTOL UAS (수직이착륙(VTOL) 무인항공기 감항기준 개발에 대한 연구)

  • Gil, Ginam;Yoo, Minyoung;Park, Jongsung
    • Journal of Aerospace System Engineering
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    • v.14 no.1
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    • pp.44-53
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    • 2020
  • In conjunction with the Fourth Industrial Revolution, the unmanned aerial vehicle industry is being developed to a new paradigm by combining advanced technologies such as AI, Big Data and the IoT. Aeronautical developed countries such as the U.S. are focusing their efforts on the development of the safer unmanned aerial vehicles. The Korea Aerospace Research Institute, as part of the national R&D project in 2011, had succeeded in developing the first vertical takeoff and landing (VTOL) UAS, called Smart-UAV. However, although the development technology of the VTOL UAS is possessed, developing and operating of the VTOL UAS for commercial or military use are limited. The type certification procedure of the VTOL UAS developed by domestic technology is stipulated in the Korean Aviation Safety Act, but the Korean VTOL UAS airworthiness standards (KAS) hsve not been established. Thus, this study investigated the development trends of the VTOL UAS in Korea and abroad and national certification systems and procedures, and benchmarked the special conditions for the VTOL aircraft, announced by the EASA on July 2, 2019, to establish standards for type certificate of the VTOL UAS in Korea.

Systematic Review and Meta-Analysis of Antibiotic-Impregnated Shunt Catheters on Anti-Infective Effect of Hydrocephalus Shunt

  • Zhou, Wen-xiu;Hou, Wen-bo;Zhou, Chao;Yin, Yu-xia;Lu, Shou-tao;Liu, Guang;Fang, Yi;Li, Jian-wen;Wang, Yan;Liu, Ai-hua;Zhang, Hai-jun
    • Journal of Korean Neurosurgical Society
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    • v.64 no.2
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    • pp.297-308
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    • 2021
  • Objective : Shunt infection is a common complication while treating hydrocephalus. The antibiotic-impregnated shunt catheter (AISC) was designed to reduce shunt infection rate. A meta-analysis was conducted to study the effectiveness of AISCs in reduction of shunt infection in terms of age, follow-up time and high-risk patient population. Methods : This study reviewed literature from three databases including PubMed, EMBASE, and Cochrane Library (from 2000 to March 2019). Clinical studies from controlled trials for shunt operation were included in this analysis. A subgroup analysis was performed based on the patient's age, follow-up time and high-risk population. The fixed effect in RevMan 5.3 software (Cochrane Collaboration) was used for this meta-analysis. Results : This study included 19 controlled clinical trials including 10105 operations. The analysis demonstrated that AISC could reduce the infection rate in shunt surgery compared to standard shunt catheter (non-AISC) from 8.13% to 4.09% (odds ratio [OR], 0.48; 95% confidence interval [CI], 0.40-0.58; p=0.01; I2=46%). Subgroup analysis of different age groups showed that AISC had significant antimicrobial effects in all three groups (adult, infant, and adolescent). Follow-up time analysis showed that AISC was effective in preventing early shunt infections (within 6 months after implant). AISC is more effective in high-risk population (OR, 0.24;95% CI, 0.14-0.40; p=0.60; I2=0%) than in general patient population. Conclusion : The results of meta-analysis indicated that AISC is an effective method for reducing shunt infection. We recommend that AISC should be considered for use in infants and high-risk groups. For adult patients, the choice for AISC could be determined based on the treatment cost.

Developing a New Algorithm for Conversational Agent to Detect Recognition Error and Neologism Meaning: Utilizing Korean Syllable-based Word Similarity (대화형 에이전트 인식오류 및 신조어 탐지를 위한 알고리즘 개발: 한글 음절 분리 기반의 단어 유사도 활용)

  • Jung-Won Lee;Il Im
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.267-286
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    • 2023
  • The conversational agents such as AI speakers utilize voice conversation for human-computer interaction. Voice recognition errors often occur in conversational situations. Recognition errors in user utterance records can be categorized into two types. The first type is misrecognition errors, where the agent fails to recognize the user's speech entirely. The second type is misinterpretation errors, where the user's speech is recognized and services are provided, but the interpretation differs from the user's intention. Among these, misinterpretation errors require separate error detection as they are recorded as successful service interactions. In this study, various text separation methods were applied to detect misinterpretation. For each of these text separation methods, the similarity of consecutive speech pairs using word embedding and document embedding techniques, which convert words and documents into vectors. This approach goes beyond simple word-based similarity calculation to explore a new method for detecting misinterpretation errors. The research method involved utilizing real user utterance records to train and develop a detection model by applying patterns of misinterpretation error causes. The results revealed that the most significant analysis result was obtained through initial consonant extraction for detecting misinterpretation errors caused by the use of unregistered neologisms. Through comparison with other separation methods, different error types could be observed. This study has two main implications. First, for misinterpretation errors that are difficult to detect due to lack of recognition, the study proposed diverse text separation methods and found a novel method that improved performance remarkably. Second, if this is applied to conversational agents or voice recognition services requiring neologism detection, patterns of errors occurring from the voice recognition stage can be specified. The study proposed and verified that even if not categorized as errors, services can be provided according to user-desired results.

An Empirical Study on the Prediction of Future New Defense Technologies in Artificial Intelligence (인공지능 분야 국방 미래 신기술 예측에 관한 실증연구)

  • Ahn, Jin-Woo;Noh, Sang-Woo;Kim, Tae-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.9
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    • pp.458-465
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    • 2020
  • Technological advances in artificial intelligence are affecting many industries, such as telecommunications, logistics, security, and healthcare, and research and development related to economic, efficiency, linkage with commercial technologies are the current focus. Predicting the changes in the future battlefield environment and ways of conducting war from a strategic point of view, as well as designing/planning the direction of military development for a leading response is not only a basic element to prepare for comprehensive future threats but also an indispensable factor that can produce an optimal effect over a limited budget/time. From this perspective, this study was conducted as part of a technology-driven plan to discover potential future technologies with high potential for use in the defense field and apply them to R&D. In this study, based on research data collected in a defense future technology investigation, the future new technology that requires further research was predicted by considering the redundancy with existing defense research projects and the feasibility of technology. In addition, an empirical study was conducted to verify the significance between the future new defense technology and the evaluation indicators in the AI field.

eXtensible Rule Markup Language (XRML): Design Principles and Application (확장형 규칙 표식 언어(eXtensible Rule Markup Language) : 설계 원리 및 응용)

  • 이재규;손미애;강주영
    • Journal of Intelligence and Information Systems
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    • v.8 no.1
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    • pp.141-157
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    • 2002
  • extensible Markup Language (XML) is a new markup language for data exchange on the Internet. In this paper, we propose a language extensible Rule Markup Language (XRML) which is an extension of XML. The implicit rules embedded in the Web pages should be identifiable, interchangeable with structured rule format, and finally accessible by various applications. It is possible to realize by using XRML. In this light, Web based Knowledge Management Systems (KMS) can be integrated with rule-based expert systems. To meet this end, we propose the six design criteria: Expressional Completeness, Relevance Linkability, Polymorphous Consistency, Applicative Universality, Knowledge Integrability and Interoperability. Furthermore, we propose three components such as RIML (Rule Identification Markup Language), RSML (Rule Structure Markup Language) and RTML (Rule Triggering Markup Language), and the Document Type Definition DTD). We have designed the XRML version 0.5 as illustrated above, and developed its prototype named Form/XRML which is an automated form processing for disbursement of the research fund in the Korea Advanced Institute of Science and Technology (KAISI). Since XRML allows both human and software agent to use the rules, there is huge application potential. We expect that XRML can contribute to the progress of Semantic Web platforms making knowledge management and e-commerce more intelligent. Since there are many emerging research groups and vendors who investigate this issue, it will not take long to see XRML commercial products. Matured XRML applications may change the way of designing information and knowledge systems in the near future.

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A Study on the Current Situation and Improved Method for the Smombie through Field Survey and ICT Trend Analysis (현장 조사와 ICT 동향 분석을 통한 스몸비 현황과 개선 방안 연구)

  • Lee, Dong Hoon;Oh, Hye Soo;Jang, Jae Min;Jeong, Jong Woon;Yang, Sang Oon
    • Journal of the Korean Society of Safety
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    • v.35 no.5
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    • pp.74-85
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    • 2020
  • Smart phone zombie or Smombie means pedestrians who walk without attention to their surroundings because they are focused upon their smart phone. Because the traffic accidents and injuries caused by Smombie have been increased rapidly in recent years, the social attention and policies are needed to prevent it. This study was conducted to analyze Smombie's current status and some solutions used before and to propose new improved method through the latest ICT trend. In this study, we did the field survey to check Smombies at several places in Seoul through people counting, and found that a lot of pedestrians still use the smart phone while walking. And we analyzed many case studies about some solutions to prevent Smombies previously. The case studies include legal regulations, government policies, smart phone app services and facilities that are used before. We studied them through internet searches and reference studies and we also checked the current operating situation as visiting several places that the solutions actually has been operated. Therefore, we found there are some limitations in previous solutions in terms of effectiveness and management. To consider new solution that can be expected to overcome the limitations, we analyzed the latest ICT trends focused on features to utilize the Smombie prevention, especially video recognition and digital signage. In these days, video recognition has been developed rapidly with assistance of AI technology and it can recognize the specific pedestrian's characteristics such as holding smart phone as well as hair style, clothes, backpack and etc. On the other hands, the digital signage is the convergence device that includes big display, network connection and various IoT sensors. It can be used as public media in many places for public services as well as advertising. Through these analysis results, we show the requirements and the user scenario for the improved method to prevent Smombie. Finally, we propose to develop R&D technology to recognize Smombie exactly as pedestrian attributes and to spread creative contents to increase pedestrian's interest and engagement for Smombie prevention through digital signage.