• Title/Summary/Keyword: communication cost

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Legal Issues for the Implementation of Non-Face-to-Face Treatment (비대면진료 실행을 위한 법적 쟁점)

  • Kwon, Ohtak
    • The Korean Society of Law and Medicine
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    • v.23 no.3
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    • pp.47-87
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    • 2022
  • Due to the COVID-19 pandemic, non-face-to-face treatment was temporarily permitted. A lot of consensus has been formed on the need to continuous non-face-to-face treatment. However, the current 「Medical Service Act」 only permits telemedicine between doctors and medical personnel. On the other hand, as a result of legal interpretation, there is an opinion that non-face-to-face treatment is allowed. But considering the overall legal system, non-face-to-face treatment is not allowed. Nevertheless, we have to consider the reality such as the development of science and technology and the outbreak of infectious diseases. Therefore, it is not advisable to allow face-to-face treatment only. Ultimately, it is necessary to find ways to ensure that non-foce-to-face treatment can be performed in a safe and effective manner. And it should be institutionalized. This is strategically necessary and important. Therefore, we must look over ahead legal issues to be discussed. First of all, the scope, the target disease and the subject of implement have to be clear. Also, structurally, the standards of facilities and equipment must be prepared for non-face-to-face treatment to be implemented. Functionally, communication and information exchange between doctors and patients should be well conducted. In addition, the information protection management system that occurs in the process of non-face-to-face treatment should be materialized. Lastly, the issue of responsibility and cost of non-face-to-face treatment should be decided in detail. When these problems materialize, it can be expected that a safe non-face-to-face treatment environment will be established.

Important Facility Guard System Using Edge Computing for LiDAR (LiDAR용 엣지 컴퓨팅을 활용한 중요시설 경계 시스템)

  • Jo, Eun-Kyung;Lee, Eun-Seok;Shin, Byeong-Seok
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.10
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    • pp.345-352
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    • 2022
  • Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

A Multi-speaker Speech Synthesis System Using X-vector (x-vector를 이용한 다화자 음성합성 시스템)

  • Jo, Min Su;Kwon, Chul Hong
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.675-681
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    • 2021
  • With the recent growth of the AI speaker market, the demand for speech synthesis technology that enables natural conversation with users is increasing. Therefore, there is a need for a multi-speaker speech synthesis system that can generate voices of various tones. In order to synthesize natural speech, it is required to train with a large-capacity. high-quality speech DB. However, it is very difficult in terms of recording time and cost to collect a high-quality, large-capacity speech database uttered by many speakers. Therefore, it is necessary to train the speech synthesis system using the speech DB of a very large number of speakers with a small amount of training data for each speaker, and a technique for naturally expressing the tone and rhyme of multiple speakers is required. In this paper, we propose a technology for constructing a speaker encoder by applying the deep learning-based x-vector technique used in speaker recognition technology, and synthesizing a new speaker's tone with a small amount of data through the speaker encoder. In the multi-speaker speech synthesis system, the module for synthesizing mel-spectrogram from input text is composed of Tacotron2, and the vocoder generating synthesized speech consists of WaveNet with mixture of logistic distributions applied. The x-vector extracted from the trained speaker embedding neural networks is added to Tacotron2 as an input to express the desired speaker's tone.

Design and Implementation of Virtual Reality Prototype Crane Training System using Unity 3D (Unity 3D를 이용한 가상현실 프로토타입 크레인 훈련 시스템 설계 및 구현)

  • Heo, Seok-Yeol;Kim, Geon-Young;Choi, Jung-Bin;Park, Ji-Woo;Jeon, Min-Ji;Lee, Wan-Jik
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.569-575
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    • 2022
  • It is most desirable to build a crane training program in the same evvironment as the actual port, but it has problem such as time constraint and cost. To overcome these limitations, next-generation training programs based on AR/VR are receiving a lot of attention. In this paper, a prototype of a harbor crane training system based on virtual reality was designed and implemented. The system implemented in this paper consists of two elements: an Arduino-based IoT terminal and an HMD equipped with a Unity application program. The IoT terminal consists of 2 controllers, 2 toggle switches, and 8 button switches to process data generated according to the user's operation. The HMD uses Oculus Quest2 and is connected to the IoT terminal through wireless communication to provide user convenience. The training system implemented in this paper is expected to provide trainees with a training environment independent of time and place through virtual reality and to save time and money.

Post-Quantum Security Strength Evaluation through Implementation of Quantum Circuit for SIMECK (SIMEC 경량암호에 대한 양자회로 구현 및 Post-Quantum 보안 강도 평가)

  • Song Gyeong Ju;Jang Kyung Bae;Sim Min Joo;Seo Hwa Jeong
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.6
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    • pp.181-188
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    • 2023
  • Block cipher is not expected to be safe for quantum computer, as Grover's algorithm reduces the security strength by accelerating brute-force attacks on symmetric key ciphers. So it is necessary to check the post-quantum security strength by implementing quantum circuit for the target cipher. In this paper, we propose the optimal quantum circuit implementation result designed as a technique to minimize the use of quantum resources (qubits, quantum gates) for SIMECK lightweight cryptography, and explain the operation of each quantum circuit. The implemented SIMECK quantum circuit is used to check the estimation result of quantum resources and calculate the Grover attack cost. Finally, the post-quantum strength of SIMECK lightweight cryptography is evaluated. As a result of post-quantum security strength evaluation, all SIMECK family cipher failed to reach NIST security strength. Therefore, it is expected that the safety of SIMECK cipher is unclear when large-scale quantum computers appear. About this, it is judged that it would be appropriate to increase the block size, the number of rounds, and the key length to increase the security strength.

An Improvement of Kubernetes Auto-Scaling Based on Multivariate Time Series Analysis (다변량 시계열 분석에 기반한 쿠버네티스 오토-스케일링 개선)

  • Kim, Yong Hae;Kim, Young Han
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.3
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    • pp.73-82
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    • 2022
  • Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

Efficient IoT data processing techniques based on deep learning for Edge Network Environments (에지 네트워크 환경을 위한 딥 러닝 기반의 효율적인 IoT 데이터 처리 기법)

  • Jeong, Yoon-Su
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.325-331
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    • 2022
  • As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

A Study for the Efficient Improvement Measures of Military EMP Protection Ability (국방 EMP 방호능력의 효율적 개선을 위한 방안 연구)

  • Jung, Seunghoon;An, Jae-Choon;Hwang, Yeung-Kyu;Jung, Hyun-Ju;Shin, Yongtae
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.1
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    • pp.219-227
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    • 2017
  • Current military command information system uses electronic equipment a lot on which semiconductor chip is attached. It seems its' importance will increase more with latest information communication technology developing. Electronic equipment which uses electricity contains regular tolerance to high output electric signal. And EMC specification is the standardized of this electronic equipment's tolerance. On the other hand, the Institute of Atomic Energy Research has ever declared that high output electromagnetic pulse(EMP) will be broken out within the radius of 170Km when 10kt nuclear explosion occurs at an altitude of 40Km above Seoul. Then, the region suffer from the damage of most electronic equipments. Therefore, the norm to protect the influences in that case is defined by EMP protection specification. Most common electronic equipments meet the EMC norm, but there is no way to check whether they meet the EMP norm or not. That is because it is difficult to check whether they meet EMP protection norm and is on the matter of cost. Except inevitable cases, there is no review of checking whether they meet the norm or not. Considering the above, in this research, we speculate about the measures to improve military EMP protection ability by analyzing the EMC-EMP correlation and checking the EMP protection ability of general electronic equipment through the analysis.

Determinants of U.S. Buyer Loyalty toward Gobizkorea.com: A Study Focused on Country Image, E-Service Quality, and Satisfaction (미국 바이어의 고비즈코리아에 대한 충성도 결정요인: 국가이미지, 서비스 품질 및 만족도를 중심으로)

  • Chung, Jae-Eun;Oh, Jeong Suk;Jeong, So Won
    • Korea Trade Review
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    • v.43 no.5
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    • pp.203-232
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    • 2018
  • Gobizkorea is an online B2B matching platform operated by the Small & Medium Business Corporation. Gobizkorea provides an opportunity for resource-poor SMEs to promote their products and exploit new market opportunities at low cost. The successful operation of Gobizkorea will contribute to the increased exports of Korean SMEs. Accordingly, the present study examined determinants of foreign buyer loyalty toward Gobizkorea.com focusing on country image, e-service quality, and satisfaction. One hundred two survey questionnaires were collected from U.S. buyers registered with Gobizkorea.com. Exploratory and confirmatory factor analysis confirmed three dimensions of e-service quality including information & efficiency, reliability & privacy, and prompt communication & delivery. The path analysis results showed that the country image of Korea significantly and positively affected these three dimensions of e-service quality. Information & efficiency and reliability & privacy positively influenced buyer satisfaction. Reliability & privacy and satisfaction had a positive impact on buyer loyalty. This study enhances the understanding of the foreign buyers use of the domestic e-market platform by examining of determinants of U.S. buyer loyalty toward Gobizkorea.

One-to-All and All-to-all Broadcasting Algorithms of Matrix Hypercube (매트릭스 하이퍼큐브의 일-대-다 방송과 다-대-다 방송 알고리즘)

  • Kim, Jongseok;Lee, Heongok
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.8
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    • pp.825-834
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    • 2018
  • Broadcasting is a basic data communication method for interconnection networks. There are two types of broadcasting. One-to-all broadcasting is to transmit a message from one node to all other nodes and all-to-all broadcasting is to transmit a message from all the nodes that have messages to other nodes. And by the using way of the transmission port per unit time, there are two schemes of broadcasting. Single port telecommunication(SLA) is to transmit messages from one node that contains the messages to one adjacent node only and all port telecommunication(MLA) is to transmit messages from one node to all adjacent nodes within a time of unit. Matrix hypercube is that an interconnection network has improved network cost than that of hypercube with the same number of nodes. In this paper, we analyze broadcasting scheme of matirx hypercube. First, we propose one-to-all and all-to-all broadcasting algorithms of matrix hypercube. And we prove that one-to-all broadcasting times are 2n+1 and $2{\lceil}{\frac{n}{2}}{\rceil}+1$ based on the SLA and MLA models, respectively. Also, we show all-to-all broadcasting time using SLA model is $5{\times}2^{\frac{n}{2}}-2$ when n=even, and is $5{\times}2^{\frac{n-1}{2}}+2$ when n=odd.