• Title/Summary/Keyword: AI engine

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Dynamic Stiffness and Frequency Response Analysis for the Development of Magnesium Oil Pans (마그네슘 합금 오일팬 개발을 위한 동적 강성 및 주파수 응답 해석)

  • Shin, Hyun-Woo;Chung, Yeon-Jun
    • Transactions of the Korean Society of Automotive Engineers
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    • v.17 no.2
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    • pp.141-149
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    • 2009
  • The oil pan is an important factor for the noise behavior of the engine system. In this paper a new Magnesium oil pan was designed and analyzed to replace the current Aluminium oil pan. Dynamic stiffness and sound pressure level of the newly designed Mg oil pan were compared with the AI oil pan using the finite element method. NVH characteristics of the Mg oil pan is slightly insufficient when we changed the material of the oil pan from Al to Mg without modifying the design. Some design modifications of the Mg oil pan resulted in equal or superior characteristics compared to the Al oil pan. New ribs were added to stiffen the structure of the Mg oil pan. Thickness of thin plate area was increased to reduce the radiated noise. Through the changes of shape, higher dynamic stiffness than the current Al oil pan were achieved. Results of frequency response analysis show that we can reduce the sound pressure level of the oil pan if we increase the thickness of the thin plate area. It is shown that the new Mg oil pan could reduce the weight of the engine system and improve NVH quality of an automobile.

Overview of VR Media Technology and Methods to Reduce Cybersickness (가상현실 미디어 기술동향과 VR 멀미저감 방안)

  • Mun, Sungchul;Kim, Hong-Ik;Park, Sangin;Lee, Dong Won;Whang, Mincheol
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2018.06a
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    • pp.24-27
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    • 2018
  • 본 논문은 최신 가상현실 미디어 기술동향과 다양한 분야에서 시도해 온 VR 멀미저감 방안을 리뷰하여, 가상현실 사용자의 인지적 수용성을 높이는 방안에 대해 논의하였다. 이를 통해 최신 미디어 기술의 사용자 가치제안 방식을 분석하고 Social VR 플랫폼의 인지적 수용성을 개선하는 효율적 방안을 제안하였다. 생체신호 모니터링, VR 콘텐츠 적합도 분석, 멀미 메커니즘 조절, 신체동요측정 기반 멀미예측 등 다양한 멀미저감 방식 중 개발 비용과 사용자 수용성 측면에서 가장 효율적인 신체동요측정 기반 멀미예측 기술의 사전테스트 결과를 소개하고 적용 방안을 구체화하였다. 가상현실 체험 전 미세한 신체동요가 많은 사용자일수록 VR 멀미 민감도가 크게 증가하는 것을 확인하였다. 개인의 멀미민감도를 반영하는 본 측정 결과를 다양한 가상현실 환경에서 테스트하고 개인특성에 따른 VR 멀미 데이터베이스를 구축한다면 AI 기반의 멀미 예측기술을 구현하는데 크게 기여할 것으로 예상된다.

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A Study on System and Application Performance Monitoring System Using Mass Processing Engine(ElasticSearch) (대량 처리 엔진(ElasticSearch)을 이용한 시스템 및 어플리케이션 성능 모니터링 시스템에 관한 연구)

  • Kim, Seung-Cheon;Jang, Hee-Don
    • Journal of Digital Convergence
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    • v.17 no.9
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    • pp.147-152
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    • 2019
  • Infrastructure is rapidly growing as Internet business grows with the latest IT technologies such as IoT, BigData, and AI. However, in most companies, a limited number of people need to manage a lot of hardware and software. Therefore, Polestar Enterprise Management System(PEMS) is applied to monitor the system operation status, IT service and key KPI monitoring. Real-time monitor screening prevents system malfunctions and quick response. With PEMS, you can see configuration information related to IT hardware and software at a glance, and monitor performance throughout the entire end-to-end period to see when problems occur in real time.

Interface Application of a Virtual Assistant Agent in an Immersive Virtual Environment (몰입형 가상환경에서 가상 보조 에이전트의 인터페이스 응용)

  • Giri Na;Jinmo Kim
    • Journal of the Korea Computer Graphics Society
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    • v.30 no.1
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    • pp.1-10
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    • 2024
  • In immersive virtual environments including mixed reality (MR) and virtual reality (VR), avatars or agents, which are virtual humans, are being studied and applied in various ways as factors that increase users' social presence. Recently, studies are being conducted to apply generative AI as an agent to improve user learning effects or suggest a collaborative environment in an immersive virtual environment. This study proposes a novel method for interface application of a virtual assistant agent (VAA) using OpenAI's ChatGPT in an immersive virtual environment including VR and MR. The proposed method consists of an information agent that responds to user queries and a control agent that controls virtual objects and environments according to user needs. We set up a development environment that integrates the Unity 3D engine, OpenAI, and packages and development tools for user participation in MR and VR. Additionally, we set up a workflow that leads from voice input to the creation of a question query to an answer query, or a control request query to a control script. Based on this, MR and VR experience environments were produced, and experiments to confirm the performance of VAA were divided into response time of information agent and accuracy of control agent. It was confirmed that the interface application of the proposed VAA can increase efficiency in simple and repetitive tasks along with user-friendly features. We present a novel direction for the interface application of an immersive virtual environment through the proposed VAA and clarify the discovered problems and limitations so far.

An Expert System for NC Part Programming (ESPP-1) (NC파트 프로그래밍을 위한 전문가시스템)

  • 정선환
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.11
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    • pp.3091-3097
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    • 1994
  • An expert system for NC part programming of NC lathe (ESPP-1) is developed as a part of Computer-Adied Manufacturing system. Conventional computer-assisted part programming system essentially requires an NC part programmer who is an expert in NC part programming. But the developed ESSP-1 can allow an inexperienced person to make an excellent NC data for the NC Lathe without any problem, since the system has a knowledge base composed of EIA and ISO NC code, feed rate, spindle speed, machining coordinates selection, and tool selection etc., which were directly evoked from some skilled NC part programmers, and referenced some machining handbooks. This paper discusses the algorithm of the expert system for NC part programming of the NC lathe (ESPP-1) and the performance comparisons between the developed expert system and the conventional system.

Disambiguiation of Qualitative Reasoning with Quantitative Knowledge (정성추론에서의 모호성제거를 위한 양적지식의 활용)

  • Yoon, Wan-Chul
    • Journal of Korean Institute of Industrial Engineers
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    • v.18 no.1
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    • pp.81-89
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    • 1992
  • After much research on qualitative reasoning, the problem of ambiguities still hampers the practicality of this important AI tool. In this paper, the sources of ambiguities are examined in depth with a systems engineering point of view and possible directions to disambiguation are suggested. This includes some modeling strategies and an architecture of temporal inference for building unambiguous qualitative models of practical complexity. It is argued that knowledge of multiple levels in abstraction hierarchy must be reflected in the modeling to resolve ambiguities by introducing the designer's decisions. The inference engine must be able to integrate two different types of temporal knowledge representation to determine the partial ordering of future events. As an independent quantity management system that supports the suggested modeling approach, LIQUIDS(Linear Quantity-Information Deriving System) is described. The inference scheme can be conjoined with ordinary rule-based reasoning systems and hence generalized into many different domains.

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Structure Recognition Method in Various Table Types for Document Processing Automation (문서 처리 자동화를 위한 다양한 표 유형에서 표 구조 인식 방법)

  • Lee, Dong-Seok;Kwon, Soon-Kak
    • Journal of Korea Multimedia Society
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    • v.25 no.5
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    • pp.695-702
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    • 2022
  • In this paper, we propose the method of a table structure recognition in various table types for document processing automation. A table with items surrounded by ruled lines are analyzed by detecting horizontal and vertical lines for recognizing the table structure. In case of a table with items separated by spaces, the table structure are recognized by analyzing the arrangement of row items. After recognizing the table structure, the areas of the table items are input into OCR engine and the character recognition result output to a text file in a structured format such as CSV or JSON. In simulation results, the average accuracy of table item recognition is about 94%.

Trend Analysis of IoT Technology Using Open Source (오픈소스를 이용한 IoT 기술의 동향 분석)

  • Kwon, Yong-Kwang;Kim, Sun-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.3
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    • pp.65-72
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    • 2020
  • The Internet of Things(IoT) is to build a hyper-connected society through interconnection, and on this basis, to improve the quality of life and productivity, including solving social problems, and to become the next growth engine for the nation. The open common eco-system pursued by the IoT can start with the under- standing of the word 'open'. The IoT can achieve the expected effect of lowering the barriers to entry of technology development, and in these changes, OSSW and OSHW play a very important role in accelerating IoT eco-system maturity and breaking the boundaries between industries to promote convergence. Recently, it has developed into an intelligent IoT that combines artificial intelligence (AI) with the connectivity of the IoT. Here, I will analyze the direction of development of the IoT through understanding and analysis of open source.

An AutoML-driven Antenna Performance Prediction Model in the Autonomous Driving Radar Manufacturing Process

  • So-Hyang Bak;Kwanghoon Pio Kim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.12
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    • pp.3330-3344
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    • 2023
  • This paper proposes an antenna performance prediction model in the autonomous driving radar manufacturing process. Our research work is based upon a challenge dataset, Driving Radar Manufacturing Process Dataset, and a typical AutoML machine learning workflow engine, Pycaret open-source Python library. Note that the dataset contains the total 70 data-items, out of which 54 used as input features and 16 used as output features, and the dataset is properly built into resolving the multi-output regression problem. During the data regression analysis and preprocessing phase, we identified several input features having similar correlations and so detached some of those input features, which may become a serious cause of the multicollinearity problem that affect the overall model performance. In the training phase, we train each of output-feature regression models by using the AutoML approach. Next, we selected the top 5 models showing the higher performances in the AutoML result reports and applied the ensemble method so as for the selected models' performances to be improved. In performing the experimental performance evaluation of the regression prediction model, we particularly used two metrics, MAE and RMSE, and the results of which were 0.6928 and 1.2065, respectively. Additionally, we carried out a series of experiments to verify the proposed model's performance by comparing with other existing models' performances. In conclusion, we enhance accuracy for safer autonomous vehicles, reduces manufacturing costs through AutoML-Pycaret and machine learning ensembled model, and prevents the production of faulty radar systems, conserving resources. Ultimately, the proposed model holds significant promise not only for antenna performance but also for improving manufacturing quality and advancing radar systems in autonomous vehicles.

A Development of Intelligent Simulation Tools based on Multi-agent (멀티 에이전트 기반의 지능형 시뮬레이션 도구의 개발)

  • Woo, Chong-Woo;Kim, Dae-Ryung
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.6
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    • pp.21-30
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    • 2007
  • Simulation means modeling structures or behaviors of the various objects, and experimenting them on the computer system. And the major approaches are DEVS(Discrete Event Systems Specification). Petri-net or Automata and so on. But, the simulation problems are getting more complex or complicated these days, so that an intelligent agent-based is being studied. In this paper, we are describing an intelligent agent-based simulation tool, which can supports the simulation experiment more efficiently. The significances of our system can be described as follows. First, the system can provide some AI algorithms through the system libraries. Second, the system supports simple method of designing the simulation model, since it's been built under the Finite State Machine (FSM) structure. And finally, the system acts as a simulation framework by supporting user not only the simulation engine, but also user-friendly tools, such as modeler scriptor and simulator. The system mainly consists of main simulation engine, utility tools, and some other assist tools, and it is tested and showed some efficient results in the three different problems.

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