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Incremental Antenna Selection Based on Lattice-Reduction for Spatial Multiplexing MIMO Systems

  • Kim, Sangchoon
    • Journal of Advanced Information Technology and Convergence
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    • v.10 no.1
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    • pp.1-14
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    • 2020
  • Antenna selection is a method to enhance the performance of spatial multiplexing multiple-input multiple-output (MIMO) systems, which can achieve the diversity order of the full MIMO systems. Although various selection criteria have been studied in the literature, they should be adjusted to the detection operation implemented at the receiver. In this paper, antenna selection methods that optimize the post-processing signal-to-noise ratio (SNR) and eigenvalue are considered for the lattice reduction (LR)-based receiver. To develop a complexity-efficient antenna selection algorithm, the incremental selection strategy is adopted. Moreover, for improvement of performance, an additional iterative selection method is presented in combination with an incremental strategy.

An Implementation of Full Virtualization based Intelligent Building System for Interface Overload Prevention (인터페이스 부하방지를 위한 전가상화 기반 지능형 빌딩 시스템 구현)

  • Kim, Oh Beom;Chung, Kwang Sik;Shon, Jin Gon
    • Annual Conference of KIPS
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    • 2010.11a
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    • pp.1694-1697
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    • 2010
  • 지능형 빌딩 시스템은 빌딩을 운영하는 다양한 단위시스템 정보를 통합하여 빌딩 거주자에게 쾌적하고, 안전한 생활을 할 수 있도록 운영하는 시스템을 말한다. 하드웨어적인 방법은 단위시스템에 비례하게 비용이 증가하는 단점이 있다. 소프트웨어적인 방법은 하나의 서버에서 정보를 수집하기 때문에 단위시스템에 통신량 증가로 인한 오류가 발생하면 전체 시스템에 영향을 미치는 단점을 가지고 있다. 본 논문에서는 소프트웨어적인 방법의 단점을 개선하기 위해서 부하 및 오류를 격리화할 수 있는 가상화를 이용하여 통합 관리 시스템과 인터페이스 관리 시스템으로 운영한다. 시스템의 구조는 통합 관리 모듈, 가상 관리 모듈, 구성 관리 모듈, 그리고 단위시스템 관리 모듈로 분리되며 제안 시스템을 사용함으로써 인터페이스 관리 시스템에서 발생하는 오류 및 부하로 인한 전체 시스템 오류를 축소시킬 수 있다.

Video Quality Assessment based on Deep Neural Network

  • Zhiming Shi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.2053-2067
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    • 2023
  • This paper proposes two video quality assessment methods based on deep neural network. (i)The first method uses the IQF-CNN (convolution neural network based on image quality features) to build image quality assessment method. The LIVE image database is used to test this method, the experiment show that it is effective. Therefore, this method is extended to the video quality assessment. At first every image frame of video is predicted, next the relationship between different image frames are analyzed by the hysteresis function and different window function to improve the accuracy of video quality assessment. (ii)The second method proposes a video quality assessment method based on convolution neural network (CNN) and gated circular unit network (GRU). First, the spatial features of video frames are extracted using CNN network, next the temporal features of the video frame using GRU network. Finally the extracted temporal and spatial features are analyzed by full connection layer of CNN network to obtain the video quality assessment score. All the above proposed methods are verified on the video databases, and compared with other methods.

WEB FRONT-END COMPUTING RELATIONAL DATABASE SYSTEM FOR ITEM-LEVEL PRELIMINARY HIGHWAY COST ESTIMATES

  • Jui-Sheng Chou ;James T. O'Connor ;Khali R. Persad ;Wai Kiong Chong
    • International conference on construction engineering and project management
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    • 2005.10a
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    • pp.509-514
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    • 2005
  • In recent years, use of the web technologies and on-line process has immensely swapped single-user platform practice. This study attempted to develop preliminary cost estimating program by means of Web technologies based on statistical modeling results. A prototype Web-based Preliminary Item-Level Cost Estimating System (WBPILCES) using open source software was developed as an on-line estimating tool in this research. The primary objective is to study the possible flexibility of implementing a centralized information system that will be maintained by the Texas Department of Transportation (TxDOT) IT division. The full-scale deployment of proposed information architecture is expected to seamlessly integrate with legacy database system currently used by TxDOT so as to streamline data storage, cost growth tracking and estimates documentation.

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Expected Effects of Employment of the socially disadvantaged (사회적 취약계층 고용으로 인한 기대효과)

  • Kim, Sea-won;Yoon, Jeong-bin;Kim, Sun-yoon;Choi, Min-jin;Choi, Hoon;Lee, Yons-Seol
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.602-604
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    • 2022
  • Recently, Korea has implemented the compulsory employment system for the disabled. The compulsory employment system for the disabled is a system that imposes an obligation on the state-local governments, public institutions that employ 50 or more full-time workers, and business owners of private companies to employ more than a certain percentage of the disabled. Accordingly, the expected effects of compulsory employment of the socially disadvantaged, including the disabled, were investigated.

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Trends in Artificial Neural Network-based Cryptanalysis Technology (인공신경망 기반의 암호 분석 연구 동향)

  • Kim, Hyun-Ji;Kang, Yea-Jun;Lim, Se-Jin;Kim, Won-Woong;Seo, Hwa-Jeong
    • Annual Conference of KIPS
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    • 2022.05a
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    • pp.501-504
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    • 2022
  • 안전한 암호 시스템은 평문을 복원하거나 키를 유추해낼 수 없도록 설계된다. 암호 분석은 이러한 암호 시스템에서 평문과 키를 추정하는 것이며, 알려진 평문 공격, 선택 평문 공격, 차분분석 등 다양한 방법이 존재한다. 또한, 최근에는 데이터의 특징을 추출하고 학습해내는 인공신경망 기술을 기반으로 하는 암호 분석 기법들이 제안되고 있다. 현재는 라운드 축소된 S-DES, SPECK, SIMON, PRESENT 등의 경량암호 및 고전암호에 대한 공격이 대부분이며, 이외에도 암호 분석을 위한 active S-box의 수를 예측하는 등과 같이 다양한 측면에서 인공신경망이 적용되고 있다. 향후에는 신경망의 효율적 구현, full-round에 대한 공격과 그에 대한 암호학적 해석이 가능한 연구들이 진행되어야 할 것으로 생각된다.

A Visual Communication Design Study: Graphic Element Design Under Traditional Handwork

  • Gengming Li
    • Journal of Information Processing Systems
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    • v.19 no.2
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    • pp.203-210
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    • 2023
  • The addition of traditional elements can enhance the uniqueness of visual communication design. This paper briefly introduced visual communication and applications of traditional elements in visual communication design and applied paper cuts, a handmade graphic element, to the logo design of Dezhou University's 50th anniversary. The convolutional neural network (CNN) algorithm and the analytic hierarchy process method were applied to evaluation analysis and compared with the support vector machine (SVM) algorithm. The results of the CNN algorithm on the test set verified its effectiveness. The evaluation results of the CNN algorithm were similar to the manual evaluation results, further proving the effectiveness and high efficiency of the CNN algorithm. The hierarchical analysis and the analysis of the assessment results of the CNN algorithm found that the two logo designs made full use of paper cuts.

3D Modeling and Simulation using Virtual Manipulator (가상 조작기를 이용한 3D 모델링 및 시뮬레이션)

  • Park, Hee-Seong;Kim, Ho-Dong
    • Annual Conference of KIPS
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    • 2011.04a
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    • pp.547-550
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    • 2011
  • The purpose of this paper is to verify and validate the maintenance tasks of the construction of a nuclear facility using a digital mock-up and simulation technology instead of a physical mock-up. Prior to the construction of a nuclear facility, a remote simulator that provides the opportunity to produce a complete digital mock-up of the PRIDE (Pyroprocess Integrated Inactive DEmonstration Facility) region and its remote handling equipment, including operations and maintenance procedures has been developed. In this paper, the system architecture and graphic user interface of a remote simulator that coincides with the extraordinary nature of a nuclear fuel cycle facility is introduced. In order to analyze the remote accessibility of a remote manipulator, virtual prototyping that was performed it by using haptic device of external input devices under a 3D full-scale digital mock-up is explained.

An Analysis of Spot Cloud in Cloud Computing

  • Mansoor, Usman;Mehmood, Usman;Khan, Faraz Idris;Kim, Ki-Hyung
    • Annual Conference of KIPS
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    • 2011.04a
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    • pp.242-245
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    • 2011
  • Cloud Computing is a fast developing domain in computer system architecture which enables dynamically scalable and virtualized resources to its users. Spot Cloud is the next evolutionary step in this field which allows the cloud computing resources to be treated as a market commodity. Cloud computing vendors will now be able to put their un used computational resources for sale using the singular access platform provided by Spot Cloud. Meanwhile customers will be able to buy/sell these resources according to their requirements. This paper analyzes the idea of Spot Cloud and the anticipated impact it will have on Cloud Computing globally. The paper also presents the risks and inherent barriers associated with this idea and how they might hinder the development of Spot Cloud to its full potential.

ARIMA, Machine Learning Approach to Forecasting Empty Container Volumes (항만 공컨테이너 재고량 예측을 위한 ARIMA, 머신러닝 적용 연구)

  • Paik, Gio;Kang, Min-Chul;Soul, Min-Wook;Lim, Seo-Jeong
    • Annual Conference of KIPS
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    • 2020.11a
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    • pp.953-955
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    • 2020
  • 공컨테이너(Empty Container)는 적컨테이너(Full Container)와 달리, 화물이 적재되지 않은 비어있는 컨테이너로 공컨테이너 재고는 수출에 비해 수입이 많은 항만에서, 수요는 수입에 비해 수출이 많은 항만에서 발생한다. 그러나 수입과 수출은 기간, 지역에 따라 유동적이기 때문에 수요와 재고량 예측에 어려움이 있는데, 본 연구에서는 자기회귀누적이동평균(ARIMA)과 머신러닝 기법을 활용하여 이를 예측하는 방법을 제시한다. 본 연구에 활용된 데이터와 프로그램 소스코드는 Kaggle 에 공개되어 있다.