• Title/Summary/Keyword: Google Cloud

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Trend analysis of Smart TV and Mobile Operating System (모바일 운영체제와 스마트 TV 동향 분석)

  • Bae, Yu-Mi;Jung, Sung-Jae;Jang, Rae-Young;Park, Jeong-Su;Kyung, Ji-Hun;Sung, Kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.740-743
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    • 2012
  • The initial role of the operating system acts as an intermediary between the computer and the user, and, hardware and process management, and the convenience of your computer system is to use. Of these operating systems as well as servers and personal computers, smartphones and tablet mounted on mobile devices such as mobile operating system was born. Mobile Operating System has been expanded a TV or Car Area that built into a simple embedded operating system, is emergence of a variety of devices, cloud services, combined with the desire of users due to the high built-in simple embedded operating system that was working on a TV or a car is expanding to the area. The reason for the emergence of a variety of devices, cloud services, combined with the desire of users is high. In this paper, the mobile operating system, N-Screen, Smart TV to find out about and through the analysis of the major smart TV, the future Find out about trends in the mobile operating system.

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Performance comparison of wake-up-word detection on mobile devices using various convolutional neural networks (다양한 합성곱 신경망 방식을 이용한 모바일 기기를 위한 시작 단어 검출의 성능 비교)

  • Kim, Sanghong;Lee, Bowon
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.5
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    • pp.454-460
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    • 2020
  • Artificial intelligence assistants that provide speech recognition operate through cloud-based voice recognition with high accuracy. In cloud-based speech recognition, Wake-Up-Word (WUW) detection plays an important role in activating devices on standby. In this paper, we compare the performance of Convolutional Neural Network (CNN)-based WUW detection models for mobile devices by using Google's speech commands dataset, using the spectrogram and mel-frequency cepstral coefficient features as inputs. The CNN models used in this paper are multi-layer perceptron, general convolutional neural network, VGG16, VGG19, ResNet50, ResNet101, ResNet152, MobileNet. We also propose network that reduces the model size to 1/25 while maintaining the performance of MobileNet is also proposed.

Keyword Analysis of Data Technology Using Big Data Technique (빅데이터 기법을 활용한 Data Technology의 키워드 분석)

  • Park, Sung-Uk
    • Journal of Korea Technology Innovation Society
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    • v.22 no.2
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    • pp.265-281
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    • 2019
  • With the advent of the Internet-based economy, the dramatic changes in consumption patterns have been witnessed during the last decades. The seminal change has led by Data Technology, the integrated platform of mobile, online, offline and artificial intelligence, which remained unchallenged. In this paper, I use data analysis tool (TexTom) in order to articulate the definitfite notion of data technology from Internet sources. The data source is collected for last three years (November 2015 ~ November 2018) from Google and Naver. And I have derived several key keywords related to 'Data Technology'. As a result, it was found that the key keyword technologies of Big Data, O2O (Offline-to-Online), AI, IoT (Internet of things), and cloud computing are related to Data Technology. The results of this study can be used as useful information that can be referred to when the Data Technology age comes.

Preliminary Test of Google Vertex Artificial Intelligence in Root Dental X-ray Imaging Diagnosis (구글 버텍스 AI을 이용한 치과 X선 영상진단 유용성 평가)

  • Hyun-Ja Jeong
    • Journal of the Korean Society of Radiology
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    • v.18 no.3
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    • pp.267-273
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    • 2024
  • Using a cloud-based vertex AI platform that can develop an artificial intelligence learning model without coding, this study easily developed an artificial intelligence learning model by the non-professional general public and confirmed its clinical applicability. Nine dental diseases and 2,999 root disease X-ray images released on the Kaggle site were used for the learning data, and learning, verification, and test data images were randomly classified. Image classification and multi-label learning were performed through hyper-parameter tuning work using a learning pipeline in vertex AI's basic learning model workflow. As a result of performing AutoML(Automated Machine Learning), AUC(Area Under Curve) was found to be 0.967, precision was 95.6%, and reproduction rate was 95.2%. It was confirmed that the learned artificial intelligence model was sufficient for clinical diagnosis.

A Study of Time Synchronization Methods for IoT Network Nodes

  • Yoo, Sung Geun;Park, Sangil;Lee, Won-Young
    • International journal of advanced smart convergence
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    • v.9 no.1
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    • pp.109-112
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    • 2020
  • Many devices are connected on the internet to give functionalities for interconnected services. In 2020', The number of devices connected to the internet will be reached 5.8 billion. Moreover, many connected service provider such as Google and Amazon, suggests edge computing and mesh networks to cope with this situation which the many devices completely connected on their networks. This paper introduces the current state of the introduction of the wireless mesh network and edge cloud in order to efficiently manage a large number of nodes in the exploding Internet of Things (IoT) network and introduces the existing Network Time Protocol (NTP). On the basis of this, we propose a relatively accurate time synchronization method, especially in heterogeneous mesh networks. Using this NTP, multiple time coordinators can be placed in a mesh network to find the delay error using the average delay time and the delay time of the time coordinator. Therefore, accurate time can be synchronized when implementing IoT, remote metering, and real-time media streaming using IoT mesh network.

Development of Interactive Hologram Education System based on Speech Recognition - Live Map (음성인식 기반 대화형 홀로그램 교육 시스템의 개발 및 평가에 관한 연구 - 라이브맵(Live Map))

  • Kwon, Chongsan;Lee, Dong-Heon;Moon, Mikyeong
    • Journal of Industrial Convergence
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    • v.17 no.4
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    • pp.69-75
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    • 2019
  • In this study, we developed a world map learning system for elementary education that uses Google Cloud platform STT, Dialog Flow, and fan holograms to recognize the voices of learners and to show and explain three-dimensional images of suitable results as holograms. As a result of the experiments and interviews, it is expected to be helpful for improving the learning effect by inducing students' interest and immersion and is expected to be effectively used for collaborative learning and education for students with disabilities.

Design and Implementation of Application for Monitoring Companion Animals in Smart Devices (반려견 관리를 위한 앱의 설계 및 구현)

  • Kwon, Dae-Wan;Park, Dong-Won
    • Journal of the Korea Convergence Society
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    • v.7 no.2
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    • pp.7-12
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    • 2016
  • The health of the companion animal is one of the most important factors for the owners. However, many owners are not aware of their companion's obesity condition. Data shows that 40% of dogs are suffering from obesity. This application is designed for and compatible with high-volume-user devices such as Android-based devices. The size of the application is reduced keeping standard data such as weight and vaccination date of species on servers and analyzing and fetching these data when user inquires about. Finally, the application has an added component of community space in order to share the knowledge among the number of users.

Digital Healthcare and Main Issues (디지털 헬스케어와 주요이슈)

  • Woo, SungHee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.560-563
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    • 2016
  • The changes in the medical and healthcare are started from the digital technology. The new field of digital healthcare has started fused with existing healthcare, medical technology, and digital technology. It can increase the service effect and reduce healthcare costs by applying ICT skills such as ICBM(Internet of Things, Cloud, Big data and Mobile), artificial intelligence, robotics, virtual, augmented reality, and wearable devices to healthcare services including healthcare, disease management. Recently there has been grafted an artificial intelligence technologies such as AlphaGo of Google and Watson of IBM onto the healthcare area. In this study, we analyze the main technology, ecosystem, platforms for digital healthcare, and lastly future changes in health care services and issues of digital healthcare.

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Forensic Investigation Procedure for Real-time Synchronization Service (실시간 동기화 서비스에 대한 포렌식 조사 절차에 관한 연구)

  • Lee, Jeehee;Jung, Hyunji;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.6
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    • pp.1363-1374
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    • 2012
  • The number and use of Internet connected devices has dramatically increased in the last several years. Therefore many services synchronizing data in real-time is increasing such as mail, calendar and storage service. This service provides convenience to users. However, after devices are seized, the data could be changed because of characteristic about real-time synchronization. Therefore digital investigation could be difficult by this service. This work investigates the traces on each local device and proposes a method for the preservation of real-time synchronized data. Based on these, we propose the procedures of real-time synchronization data.

Safe clinical photography: best practice guidelines for risk management and mitigation

  • Chandawarkar, Rajiv;Nadkarni, Prakash
    • Archives of Plastic Surgery
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    • v.48 no.3
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    • pp.295-304
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    • 2021
  • Clinical photography is an essential component of patient care in plastic surgery. The use of unsecured smartphone cameras, digital cameras, social media, instant messaging, and commercially available cloud-based storage devices threatens patients' data safety. This paper Identifies potential risks of clinical photography and heightens awareness of safe clinical photography. Specifically, we evaluated existing risk-mitigation strategies globally, comparing them to industry standards in similar settings, and formulated a framework for developing a risk-mitigation plan for avoiding data breaches by identifying the safest methods of picture taking, transfer to storage, retrieval, and use, both within and outside the organization. Since threats evolve constantly, the framework must evolve too. Based on a literature search of both PubMed and the web (via Google) with key phrases and child terms (for PubMed), the risks and consequences of data breaches in individual processes in clinical photography are identified. Current clinical-photography practices are described. Lastly, we evaluate current risk mitigation strategies for clinical photography by examining guidelines from professional organizations, governmental agencies, and non-healthcare industries. Combining lessons learned from the steps above into a comprehensive framework that could contribute to national/international guidelines on safe clinical photography, we provide recommendations for best practice guidelines. It is imperative that best practice guidelines for the simple, safe, and secure capture, transfer, storage, and retrieval of clinical photographs be co-developed through cooperative efforts between providers, hospital administrators, clinical informaticians, IT governance structures, and national professional organizations. This would significantly safeguard patient data security and provide the privacy that patients deserve and expect.