• Title/Summary/Keyword: Mobile AI

Search Result 207, Processing Time 0.024 seconds

A Study on Analysis and Improvement of Contents of Domestic Disaster & Safety Education (국내 재난안전교육 컨텐츠 분석 및 개선방안 연구)

  • Chung, Hee-Soo;Song, Chang-Geun
    • Journal of Convergence for Information Technology
    • /
    • v.12 no.1
    • /
    • pp.76-82
    • /
    • 2022
  • Recently, natural and social disasters in Korea are increasing, and new disasters such as COVID 19 and sinkholes, and large-scale disasters that combine natural and social disasters are occurring frequently. In order to reduce damage caused by disasters and effectively respond to disasters, the importance of disaster safety education is emerging because it is necessary to understand the awareness of disaster situations and the functional response process. Ministry of Public Interior and Security is providing disaster safety education for emergency managers through 54 specialized disaster safety education institutions. There is also a lack of experience facilities. This has a problem in that it makes it difficult for disaster safety personnel to effectively respond to disasters due to lack of experience in actual disaster sites. Also, unlike other education fields, the connection between disaster safety education contents and new technologies such as AI is still lacking. In this study, focusing on natural disaster, the current status and problems of domestic disaster safety education institutions and their contents are investigated and analyzed, and based on this, this study suggested improvement plans for domestic disaster safety education contents such as establishment of a unified disaster safety standard curriculum, production and distribution of disaster safety education experience contents using virtual reality technology and infotainment technology, and development of mobile AI tutoring service.

Performance Evaluation of PBCH Detection of LTE-Based 5G MBMS and 5G NR for Cellular Broadcast (셀룰러 방송을 위한 LTE 기반 5G MBMS와 5G NR의 PBCH 검출 성능 평가)

  • Ahn, Haesung;Kim, Hyeongseok;Cha, Eunyoung;Kim, Jeongchang;Ahn, Seok-Ki;Kwon, Sunhyoung;Park, Sung-Ik;Hur, Namho
    • Journal of Broadcast Engineering
    • /
    • v.26 no.6
    • /
    • pp.766-777
    • /
    • 2021
  • This paper presents an improved scheme for detection of the physical broadcast channel (PBCH) in long-term evolution (LTE)-based fifth-generation (5G) multimedia broadcast and multicast services (MBMS) and 5G new radio (NR) for cellular broadcast. In the time domain, by combining the correlations between the received signal and primary synchronization signal (PSS) within all SS/PBCH blocks, the frame synchronization and the start position of the SS/PBCH blocks can be obtained. In this paper, to improve the detection performance of PBCH for 5G NR, a combining scheme of PBCH signals within a frame is proposed. In addition, the performance of the proposed detection scheme is evaluated and the performance is compared with the conventional scheme for PBCH detection of LTE-based 5G MBMS. The simulation results show that the detection performance of PBCH for 5G NR is improved by combining the PBCH signals and outperforms LTE-based 5G MBMS under the additive white Gaussian noise (AWGN), fixed, and mobile environments.

A Comparative Study on Discrimination Issues in Large Language Models (거대언어모델의 차별문제 비교 연구)

  • Wei Li;Kyunghwa Hwang;Jiae Choi;Ohbyung Kwon
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.3
    • /
    • pp.125-144
    • /
    • 2023
  • Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

Development Trends of Defense Science and Technology based on the 4th Industrial Revolution (제4차 산업혁명 기반의 국방과학기술 개발 동향)

  • Jeong, Y.H.;Kim, S.N.;Park, H.S.
    • Electronics and Telecommunications Trends
    • /
    • v.35 no.6
    • /
    • pp.56-67
    • /
    • 2020
  • The core technologies of the 4th Industrial Revolution, such as artificial intelligence, the Internet of Things, the cloud, big data, and mobile networks, are inspiring major changes and innovations in the defense sector worldwide. The United States, China, and Russia are pursuing defense research and development strategies that seek to maintain their leadership on the battlefield in the future through the overwhelming superiority of defense science technology. Defense science and technology concentrate on the development of challenging new disruptive technologies to efficiently respond to future battlefield environments, where the immediate process of determining the outcome of a war will lead to combat power. In this paper, we first look at the development strategies of the 4th Industrial Revolution in major countries and describe the latest trends in defense science and technology accordingly.

On Power Calculation for First and Second Strong Channel Users in M-user NOMA System

  • Chung, Kyuhyuk
    • International journal of advanced smart convergence
    • /
    • v.9 no.3
    • /
    • pp.49-58
    • /
    • 2020
  • Non-orthogonal multiple access (NOMA) has been recognized as a significant technology in the fifth generation (5G) and beyond mobile communication, which encompasses the advanced smart convergence of the artificial intelligence (AI) and the internet of things (IoT). In NOMA, since the channel resources are shared by many users, it is essential to establish the user fairness. Such fairness is achieved by the power allocation among the users, and in turn, the less power is allocated to the stronger channel users. Especially, the first and second strong channel users have to share the extremely small amount of power. In this paper, we consider the power optimization for the two users with the small power. First, the closed-form expression for the power allocation is derived and then the results are validated by the numerical results. Furthermore, with the derived analytical expression, for the various channel environments, the optimal power allocation is investigated and the impact of the channel gain difference on the power allocation is analyzed.

Designing Cost Effective Open Source System for Bigdata Analysis (빅데이터 분석을 위한 비용효과적 오픈 소스 시스템 설계)

  • Lee, Jong-Hwa;Lee, Hyun-Kyu
    • Knowledge Management Research
    • /
    • v.19 no.1
    • /
    • pp.119-132
    • /
    • 2018
  • Many advanced products and services are emerging in the market thanks to data-based technologies such as Internet (IoT), Big Data, and AI. The construction of a system for data processing under the IoT network environment is not simple in configuration, and has a lot of restrictions due to a high cost for constructing a high performance server environment. Therefore, in this paper, we will design a development environment for large data analysis computing platform using open source with low cost and practicality. Therefore, this study intends to implement a big data processing system using Raspberry Pi, an ultra-small PC environment, and open source API. This big data processing system includes building a portable server system, building a web server for web mining, developing Python IDE classes for crawling, and developing R Libraries for NLP and visualization. Through this research, we will develop a web environment that can control real-time data collection and analysis of web media in a mobile environment and present it as a curriculum for non-IT specialists.

A study on a technological-level evaluation based on integrated data in the intelligent information technology Domain (지능정보기술 분야에 대한 통합적 데이터기반의 기술수준평가 조사연구)

  • Cho, Ilgu
    • Proceedings of the Korea Contents Association Conference
    • /
    • 2017.05a
    • /
    • pp.235-236
    • /
    • 2017
  • 최근 제4차 산업혁명 시대가 도래함에 따라 지능정보기술은 대규모 데이터에 대한 자가학습(Machine Learning)을 통해 알고리즘 성능을 지속적으로 강화함으로써 데이터와 지식이 산업의 주요 경쟁 원천으로 부상시키고 있다. 지능정보기술은 산업전반에 구조적 대변혁을 촉발할 것으로 전망됨에 따라 전세계적으로 지능정보기술을 선제적으로 확보, 도입 및 확산하여 국가경쟁력을 제고해나가려 하고 있다. 따라서 지능정보기술을 확보하기 위한 R&D 전략수립이 무엇보다 중요해졌다. 본 조사 연구에서는 IoT, Cloud, Bigdata, Mobile, AI 등 지능정보기술 분야의 기술경쟁력 수준을 파악하기 위해 전문가 정성적 기술수준평가와 함께 특허, 논문 등 데이터기반의 기술수준평가에 대한 것이다.

  • PDF

Low Power SoC Design Trends Using EDA Tools (설계툴을 사용한 저전력 SoC 설계 동향)

  • Park, Nam Jin;Joo, Yu Sang;Na, Jung-Chan
    • Electronics and Telecommunications Trends
    • /
    • v.35 no.2
    • /
    • pp.69-78
    • /
    • 2020
  • Small portable devices such as mobile phones and laptops currently display a trend of high power consumption owing to their characteristics of high speed and multifunctionality. Low-power SoC design is one of the important factors that must be considered to increase portable time at limited battery capacities. Popular low power SoC design techniques include clock gating, multi-threshold voltage, power gating, and multi-voltage design. With a decreasing semiconductor process technology size, leakage power can surpass dynamic power in total power consumption; therefore, appropriate low-power SoC design techniques must be combined to reduce power consumption to meet the power specifications. This study examines several low-power SoC design trends that reduce semiconductor SoC dynamic and static power using EDA tools. Low-power SoC design technology can be a competitive advantage, especially in the IoT and AI edge environments, where power usage is typically limited.

A Performance Study on Lightweight Neural Network for Mobile Deep Learning (모바일 딥러닝을 위한 신경망 성능 평가에 관한 연구)

  • Shin, Ik Hee;Park, Junyong;Moon, Yong Hyuk;Lee, Yong-Ju
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2019.05a
    • /
    • pp.435-437
    • /
    • 2019
  • 모바일 환경에서 다양한 AI 관련 응용을 수행하기 위해, 정확도에 기반한 크고 깊은 신경망 이외에, 정확도를 비교적 유지하면서 좀더 효율적인 신경망 구조에 대한 다양한 연구가 진행중이다. 본 논문에서는 모바일 딥러닝을 위한 다양한 임베디드 장치 및 모바일 폰에서의 성능 평가를 통해 경량 신경망의 비교 분석에 대한 연구를 담고 있다.

Smart Airport and Next Generation Security Screening Technology (스마트공항과 차세대 보안검색 기술)

  • Hong, J.W.;Oh, J.H.;Lee, H.K.
    • Electronics and Telecommunications Trends
    • /
    • v.34 no.2
    • /
    • pp.73-82
    • /
    • 2019
  • Airport is shifted airport 1.0 to airport 4.0 called smart airport and services paradigm is changed into direction to point the customer targeted benefits. Smart airports make use of integrated Internet of Things components to provide added-value services. By integrating smart components, airports are being exposed to a larger attack surface and new attack vectors. Self-services such as web or mobile check-in, self check-in/tagging/back drop/boarding, etc. should be strengthened to make airport processes smarter, and technologies such as automatic immigration, smart security search, and automatic AI-based baggage search should be applied. In this paper, we describe the necessity and importance of smart airports and next generation security screening technology. Further, we describe a walk through-type smart security screening system.