• Title/Summary/Keyword: Utilizing AI

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Development of AI-based Prediction and Assessment Program for Tunnelling Impact

  • Yoo, Chungsik;HAIDER, SYED AIZAZ;Yang, Jaewon;ALI, TABISH
    • Journal of the Korean Geosynthetics Society
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    • v.18 no.4
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    • pp.39-52
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    • 2019
  • In this paper the development and implementation of an artificial intelligence (AI)-based Tunnelling Impact prediction and assessment program (SKKU-iTunnel) is presented. Program predicts tunnelling induced surface settlement and groundwater drawdown by utilizing well trained ANNs and uses these predicted values to perform the damage assessment likely to occur in nearby structures and pipelines/utilities for a given tunnel problem. Generalised artificial neural networks (ANNs) were trained, to predict the induced parameters, through databases generated by combining real field data and numerical analysis for cases that represented real field conditions. It is shown that program equipped with carefully trained ANN can predict tunnel impact assessments and perform damage assessments quiet efficiently and comparable accuracy to that of numerical analysis. This paper describes the idea and implementation details of the SKKU-iTunnel with an example for demonstration.

A Study on the Enhancement of Utilization of Automatic Identification System (선박자동식별장치의 효율적인 이용방안에 관한 연구)

  • 정중식;양원재
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.9 no.2
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    • pp.15-21
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    • 2003
  • Recently, one of important resolutions of IMO MSC is an adoption of AIS in SOLAS Chapter 5. The AIS, which is a communication system to enhance safety of navigation by transmitting and receiving vessel information automatically, entered into force on July 1st, 2002. This paper provides guidelines for utilizing AIS effectively and successfully in VIS or all ships. For this, we investigated technical characteristics of AIS, the regulations related to AIS, marine accidents.

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A Case Study on Kakao's Resilience: Based on Five Levers of Resilience Theory

  • Song, Minzheong
    • International Journal of Internet, Broadcasting and Communication
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    • v.9 no.3
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    • pp.44-58
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    • 2017
  • The purpose of this study is to prove the Korean Internet company, Kakao's resilience capacity. For it, this paper reviews the previous literatures regarding Kakao's business models and discusses 'resilience' theory. Then, it organizes the research questions based on the theoretical background and explains the research methodology. It investigates the case of Kakao's business and organization. The case analysis shows that five levers of resilience are a good indicator for a successful platform business evolution. The five levers are composed of coordination, cooperation, clout, capability, and connection: First lever, coordination that makes the company to restructure its silo governance in order to respond to actual business flow starting from the basic asset like game and music content; second lever, cooperation where the firm provides creative people with playground for startups such as KakaoPage; third lever, clout where the company shares its data by opening its API of AI and chatbot to $3^{rd}$ party developers; fourth lever, capability where the firm establishes AI R&D center, KakaoBrain as the function of multi-domain generalist for developing diverse platforms tackling customer needs; and the last fifth lever, connection where the firm continues to expand its platform business to the peripheries, O2O businesses such as KakaoTaxi, KakaoOrder, KakaoPay, and KakaoBank. In conclusion, this study proposes Internet companies to be a resilient platform utilizing those five levers of resilience in order to form successful platform. This study contributes to the agile innovation of Internet platform with ecological sense.

A Research to realize a smart logistics warehouse system using 5G-based Logistics Automation Robot (5G 기반 물류 자동화 로봇을 활용한 스마트 물류 창고 시스템 구현을 위한 연구)

  • Park, Tae-uk;Yoon, Mahn-Suk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.532-534
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    • 2022
  • At a time when the 5G era is advancing beyond commercialization, places that used to handle simple logistics warehouse tasks are transforming into smart logistics warehouses by combining IT convergence technology and platforms. Smart logistics warehouses can accurately predict demand and inventory of products with AI, deep learning, and robot technologies based on 5G, and provide information on warehousing and warehousing status in real time. As the e-commerce market grows, the smart logistics sector is also growing rapidly. This paper implements a smart logistics warehouse system and studies and proposes a method of establishing a fast and accurate logistics system by utilizing 5G-based Logistics Automation Robot.

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Signal-Based Fault Detection and Diagnosis on Electronic Packaging and Applications of Artificial Intelligence Techniques (시그널 기반 전자패키지 결함검출진단 기술과 인공지능의 응용)

  • Tae Yeob Kang;Taek-Soo Kim
    • Journal of the Microelectronics and Packaging Society
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    • v.30 no.1
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    • pp.30-41
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    • 2023
  • With the aggressive down-scaling of advanced integrated circuits (ICs), electronic packages have become the bottleneck of both reliability and performance of whole electronic systems. In order to resolve the reliability issues, Institute of Electrical and Electronics Engineers (IEEE) laid down a roadmap on fault detection and diagnosis (FDD), thrusting the digital twin: a combination of reliability physics and artificial intelligence (AI). In this paper, we especially review research works regarding the signal-based FDD approaches on the electronic packages. We also discuss the research trend of FDD utilizing AI techniques.

Proposal of Artificial Intelligence Convergence Curriculum for Upskilling of Financial Manpower : Focusing on Private Bankers and Robo-Advisors

  • KIM, JiWon;WOO, HoSung
    • Fourth Industrial Review
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    • v.2 no.1
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    • pp.19-32
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    • 2022
  • Purpose - As new technologies that have led the 4th industrial revolution spread after the COVID-19 pandemic, the business crisis of existing financial institutions and the threat of employee jobs are growing, especially in the financial sector. The purpose of this study is to propose a human-technology convergence curriculum for creating high value-added in financial institutions and upskilling financial manpower. Research design, data, and methodology - In this study, a curriculum was designed to strengthen job competency for Private Bankers, high-quality employees of a bank dealing with high-net-worth owners. The focus of the design is that learners acquire skills to use robo-advisors as a tool and supplement artificial intelligence ethics. Result - The curriculum is organized into a total of 16 classes, and the main contents are changes in the financial environment and financial consumers, the core technology of robo-advisors and AI ethics, and establishment and evaluation of hyper-personalized asset management strategies using robo-advisors. To achieve the educational goal, two evaluations are performed to derive individual tasks and team project results. Conclusion - Human-centered upskilling convergence education will contribute to improving employee value and expanding corporate high value-added business areas by utilizing new technologies as tools. It is expected that the development and application of convergence curriculum in various fields will continue to be advanced in the future.

Generative Interactive Psychotherapy Expert (GIPE) Bot

  • Ayesheh Ahrari Khalaf;Aisha Hassan Abdalla Hashim;Akeem Olowolayemo;Rashidah Funke Olanrewaju
    • International Journal of Computer Science & Network Security
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    • v.23 no.4
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    • pp.15-24
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    • 2023
  • One of the objectives and aspirations of scientists and engineers ever since the development of computers has been to interact naturally with machines. Hence features of artificial intelligence (AI) like natural language processing and natural language generation were developed. The field of AI that is thought to be expanding the fastest is interactive conversational systems. Numerous businesses have created various Virtual Personal Assistants (VPAs) using these technologies, including Apple's Siri, Amazon's Alexa, and Google Assistant, among others. Even though many chatbots have been introduced through the years to diagnose or treat psychological disorders, we are yet to have a user-friendly chatbot available. A smart generative cognitive behavioral therapy with spoken dialogue systems support was then developed using a model Persona Perception (P2) bot with Generative Pre-trained Transformer-2 (GPT-2). The model was then implemented using modern technologies in VPAs like voice recognition, Natural Language Understanding (NLU), and text-to-speech. This system is a magnificent device to help with voice-based systems because it can have therapeutic discussions with the users utilizing text and vocal interactive user experience.

Trends and Future Directions in Facial Expression Recognition Technology: A Text Mining Analysis Approach (얼굴 표정 인식 기술의 동향과 향후 방향: 텍스트 마이닝 분석을 중심으로)

  • Insu Jeon;Byeongcheon Lee;Subeen Leem;Jihoon Moon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.748-750
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    • 2023
  • Facial expression recognition technology's rapid growth and development have garnered significant attention in recent years. This technology holds immense potential for various applications, making it crucial to stay up-to-date with the latest trends and advancements. Simultaneously, it is essential to identify and address the challenges that impede the technology's progress. Motivated by these factors, this study aims to understand the latest trends, future directions, and challenges in facial expression recognition technology by utilizing text mining to analyze papers published between 2020 and 2023. Our research focuses on discerning which aspects of these papers provide valuable insights into the field's recent developments and issues. By doing so, we aim to present the information in an accessible and engaging manner for readers, enabling them to understand the current state and future potential of facial expression recognition technology. Ultimately, our study seeks to contribute to the ongoing dialogue and facilitate further advancements in this rapidly evolving field.

Audio-Visual Scene Aware Dialogue System Utilizing Action From Vision and Language Features (이미지-텍스트 자질을 이용한 행동 포착 비디오 기반 대화시스템)

  • Jungwoo Lim;Yoonna Jang;Junyoung Son;Seungyoon Lee;Kinam Park;Heuiseok Lim
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.253-257
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    • 2023
  • 최근 다양한 대화 시스템이 스마트폰 어시스턴트, 자동 차 내비게이션, 음성 제어 스피커, 인간 중심 로봇 등의 실세계 인간-기계 인터페이스에 적용되고 있다. 하지만 대부분의 대화 시스템은 텍스트 기반으로 작동해 다중 모달리티 입력을 처리할 수 없다. 이 문제를 해결하기 위해서는 비디오와 같은 다중 모달리티 장면 인식을 통합한 대화 시스템이 필요하다. 기존의 비디오 기반 대화 시스템은 주로 시각, 이미지, 오디오 등의 다양한 자질을 합성하거나 사전 학습을 통해 이미지와 텍스트를 잘 정렬하는 데에만 집중하여 중요한 행동 단서와 소리 단서를 놓치고 있다는 한계가 존재한다. 본 논문은 이미지-텍스트 정렬의 사전학습 임베딩과 행동 단서, 소리 단서를 활용해 비디오 기반 대화 시스템을 개선한다. 제안한 모델은 텍스트와 이미지, 그리고 오디오 임베딩을 인코딩하고, 이를 바탕으로 관련 프레임과 행동 단서를 추출하여 발화를 생성하는 과정을 거친다. AVSD 데이터셋에서의 실험 결과, 제안한 모델이 기존의 모델보다 높은 성능을 보였으며, 대표적인 이미지-텍스트 자질들을 비디오 기반 대화시스템에서 비교 분석하였다.

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Screening of Genetic Variations in Korean Native Duck using Next-Generation Resequencing Data

  • Eunjin Cho;Minjun Kim;Hyo Jun Choo;Jun Heon Lee
    • Korean Journal of Poultry Science
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    • v.50 no.3
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    • pp.187-191
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    • 2023
  • Korean native ducks (KNDs) continue to have a high preference from consumers due to their excellent meat quality and taste characteristics. However, due to low productivity and fixed plumage color phenotype, it could not secure a large share in the domestic market compared to imported species. In order to improve the market share of KNDs, the genetic characteristics of the breed should be identified and used for improvement and selection. Therefore, this study was conducted to identify the genetic information of colored and white KNDs using next-generation resequencing data and screening for differences between the two groups. As a result of the analysis, the genetic variants that showed significant differences between the colored and white KND groups were mainly identified as mutations related to tyrosine activity. The variants were located in the genes that affect melanin synthesis and regulation, such as EGFR, PDGFRA, and DDR2, and these were reported as the candidate genes related to plumage pigmentation in poultry. Therefore, the results of this study are expected to be useful as a basis for understanding and utilizing the genetic characteristics of KNDs for genetic improvement and selection of white broiler KNDs.