• Title/Summary/Keyword: Mobile AI

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A Study on the Use of Retailtech and Intention to Accept Technology based on Experiential Marketing (체험마케팅에 기반한 리테일테크 활용과 기술수용의도에 관한 연구)

  • Sangho Lee;Kwangmoon Cho
    • Journal of Internet of Things and Convergence
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    • v.10 no.2
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    • pp.137-148
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    • 2024
  • The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.

Trends in AI Processor Technology (인공지능프로세서 기술 동향)

  • Lee, M.Y.;Chung, J.;Lee, J.H.;Han, J.H.;Kwon, Y.S.
    • Electronics and Telecommunications Trends
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    • v.35 no.3
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    • pp.66-75
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    • 2020
  • As the increasing expectations of a practical AI (Artificial Intelligence) service makes AI algorithms more complicated, an efficient processor to process AI algorithms is required. To meet this requirement, processors optimized for parallel processing, such as GPUs (Graphics Processing Units), have been widely employed. However, the GPU has a generalized structure for various applications, so it is not optimized for the AI algorithm. Therefore, research on the development of AI processors optimized for AI algorithm processing has been actively conducted. This paper briefly introduces an AI processor especially for inference acceleration, developed by the Electronics and Telecommunications Research Institute, South Korea., and other global vendors for mobile and server platforms. However, the GPU has a generalized structure for various applications, so it is not optimized for the AI algorithm. Therefore, research on the development of AI processors optimized for AI algorithm processing has been actively conducted.

CSSMA/AI Protocol for Data Services in Packet CDMA Networks (패킷 CDMA 망에서 데이터 서비스를 위한 CSSMA/AI 프로토콜)

  • 임인택
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05b
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    • pp.475-478
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    • 2004
  • In this paper, a CSSMA/AI MAC protocol for data services in packet CDMA network is presented. The proposed protocol is based on the code status sensing and reservation scheme. In the proposed protocol, the base station broadcast the rode status on a frame-by-frame basis just before the beginning of each preamble transmission, and the mobile station transmits a preamble for reserving a randomly selected code based on the received code status. After having transmitted the preamble, the mobile station listens to the downlink of the selected rode and waits for the base station reply. If this reply indicates that the code has been correctly acquired, it continues the packet transmission lot the rest of the frame. If there are other packets waiting for transmission, the base station broadcasts the status of the code as reserved, and the mobile station transmits a packet through the reserved code for the successive frames.

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A Study on Finding Emergency Conditions for Automatic Authentication Applying Big Data Processing and AI Mechanism on Medical Information Platform

  • Ham, Gyu-Sung;Kang, Mingoo;Joo, Su-Chong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.8
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    • pp.2772-2786
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    • 2022
  • We had researched an automatic authentication-supported medical information platform[6]. The proposed automatic authentication consists of user authentication and mobile terminal authentication, and the authentications are performed simultaneously in patients' emergency conditions. In this paper, we studied on finding emergency conditions for the automatic authentication by applying big data processing and AI mechanism on the extended medical information platform with an added edge computing system. We used big data processing, SVM, and 1-Dimension CNN of AI mechanism to find emergency conditions as authentication means considering patients' underlying diseases such as hypertension, diabetes mellitus, and arrhythmia. To quickly determine a patient's emergency conditions, we placed edge computing at the end of the platform. The medical information server derives patients' emergency conditions decision values using big data processing and AI mechanism and transmits the values to an edge node. If the edge node determines the patient emergency conditions, the edge node notifies the emergency conditions to the medical information server. The medical server transmits an emergency message to the patient's charge medical staff. The medical staff performs the automatic authentication using a mobile terminal. After the automatic authentication is completed, the medical staff can access the patient's upper medical information that was not seen in the normal condition.

Development of Radar-enabled AI Convergence Transportation Entities Detection System for Lv.4 Connected Autonomous Driving in Adverse Weather

  • Myoungho Oh;Mun-Yong Park;Kwang-Hyun Lim
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.190-201
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    • 2023
  • Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.

Development of Induction machine Diagnosis System using LabVIEW and PDA (LabVIEW 기반의 PDA를 이용한 기계 진단 시스템의 개발)

  • Son, Jong-Duk;Yang, Bo-Suk;Han, Tian;Ha, Jong-Yong
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.945-948
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    • 2005
  • Mobile computing devices are becoming increasingly prevalent in a huge range of physical area, offering a considerable market opportunity. The focus of this paper is on the development of a platform of fault diagnosis system integrating with personal digital assistant (PDA). An improvement of induction machine rotor fault diagnosis based on AI algorithms approach is presented. This network system consists of two parts; condition monitoring and fault diagnosis by using Artificial Intelligence algorithm. LabVIEW allows easy interaction between acquisition instrumentation and operators. Also it can easily integrate AI algorithm. This paper presents a development environment fur intelligent application for PDA. The introduced configuration is a LabVIEW application in PDA module toolkit which is LabVIEW software.

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Helping People with Visual Disability Using AI

  • Naif Al Otaibi;Tariq S Almurayziq
    • International Journal of Computer Science & Network Security
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    • v.24 no.1
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    • pp.205-208
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    • 2024
  • Artificial Intelligence (AI) technology has evolved rapidly in recent years and is used in everything from banking to email management to surgery, but without the help of the visible, most of the fun features of the Internet include visual impairment. It benefits people with disabilities. The main purpose of this study is to find ways to help people with visual impairments using AI technology. A visually impaired request is made for the visually impaired. For example, when a message arrives that the program will notify you by voice (reads the sender's name, read the message, and replies to it if necessary), this is a special program installed on your mobile phone. This program uses a customized algorithm developed in Python to convert written text to voice, read text, and convert voice to written text on a message when a visually impaired person wants to respond. Then it sends the response in the form of a text message. Therefore, the research should lead to programs for people with visual impairments. This program makes mobile phones easier and more comfortable to use and makes the daily life easier for visual impairments.

A loop closing scheme using UWB based indoor positioning technique (UWB 기반 실내 측위 기술을 활용한 루프 클로징 기법)

  • Hyunwoo You;Jungkyun Lee;Somi Nam;Juyeon Lee;Yoonseo Lee;Minsung Kim;Hong Min
    • Smart Media Journal
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    • v.12 no.4
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    • pp.41-46
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    • 2023
  • UWB is a type of technology used for indoor positioning and is characterized by higher accuracy than RSSI-based schemes. Mobile equipment operating based on ROS can monitor the environment around the equipment using lidar and cameras. When applying the loop closing technique to determine the starting position in this monitoring process, the existing method has a problem of low accuracy because the closing operation occurs only when there are feature points on the image. In this paper, to solve this problem, we designed a system that increases the accuracy of loop closing work by providing location information by mounting a UWB tag on a mobile device. In addition, the accuracy of the UWB-based indoor positioning system was evaluated through experiments, and it was verified that it could be used for loop closing techniques.

A Study on the Effective Preprocessing Methods for Accelerating Point Cloud Registration

  • Chungsu, Jang;Yongmin, Kim;Taehyun, Kim;Sunyong, Choi;Jinwoo, Koh;Seungkeun, Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.1
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    • pp.111-127
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    • 2023
  • In visual slam and 3D data modeling, the Iterative Closest Point method is a primary fundamental algorithm, and many technical fields have used this method. However, it relies on search methods that take a high search time. This paper solves this problem by applying an effective point cloud refinement method. And this paper also accelerates the point cloud registration process with an indexing scheme using the spatial decomposition method. Through some experiments, the results of this paper show that the proposed point cloud refinement method helped to produce better performance.

Physical-Layer Technology Trend and Prospect for AI-based Mobile Communication (AI 기반 이동통신 물리계층 기술 동향과 전망)

  • Chang, K.;Ko, Y.J.;Kim, I.G.
    • Electronics and Telecommunications Trends
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    • v.35 no.5
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    • pp.14-29
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    • 2020
  • The 6G mobile communication system will become a backbone infrastructure around 2030 for the future digital world by providing distinctive services such as five-sense holograms, ultra-high reliability/low-latency, ultra-high-precision positioning, ultra-massive connectivity, and gigabit-per-second data rate for aerial and maritime terminals. The recent remarkable advances in machine learning (ML) technology have recognized its efficiency in wireless networking fields such as resource management and cell-configuration optimization. Further innovation in ML is expected to play an important role in solving new problems arising from 6G network management and service delivery. In contrast, an approach to apply ML to a physical-layer (PHY) target tackles the basic problems in radio links, such as overcoming signal distortion and interference. This paper reviews the methodologies of ML-based PHY, relevant industrial trends, and candiate technologies, including future research directions and standardization impacts.