• 제목/요약/키워드: Nano-Network

검색결과 259건 처리시간 0.022초

Zigbee MAC 프로토콜기반 인체 응용을 위한 나노 네트워크의 슈퍼 프레임 설계 (Zigbee MAC Protocol based Super frame Design for In-body Nano-Network Applications)

  • 이경환;김성운
    • 한국멀티미디어학회논문지
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    • 제19권9호
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    • pp.1690-1697
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    • 2016
  • In a beacon-enabled Zigbee network, the slotted CSMA/CA mechanism based on the super frame structure fairly provides communication chance for each node and makes a reasonable usage of the available energy. In the case of wireless nano sensors that are implanted into the target human body area for detecting disease symptoms or virus, such a nano-network requires a similar type of channel sharing and transmission of short length event-driven data. In this paper, for nano-network's in-body applications, we aim to design conceptually a new super frame derived from the existing beacon-enabled Zigbee MAC protocol. And we analyze the efficiency of the proposed super frame in the aspect of practical deployment.

The use of artificial neural networks in predicting ASR of concrete containing nano-silica

  • Tabatabaei, Ramin;Sanjaria, Hamid Reza;Shamsadini, Mohsen
    • Computers and Concrete
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    • 제13권6호
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    • pp.739-748
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    • 2014
  • In this article, by using experimental studies and artificial neural network has been tried to investigate the use of nano-silica as concrete admixture to reduce alkali-silica reaction. If there are reactive aggregates and alkali of cement with enough moisture in concrete, a gel will be formed. Then with high reactivity between alkali of cement and existence of silica in aggregates, this gel will expand by absorption of water, and causes expansive pressure and cracks be formed. At the time passes, this gel will reduce both durability and strength of the concrete. By reducing the size of silicate to nano, specific surface area of particles and number of atoms on the surface will be increased, which causes more pozzolanic activity of them. Nano-silica can react with calcium hydroxide ($Ca(OH)_2$) and produces C-S-H gel. In this study, accelerated mortar bar specimens according to ASTM C 1260 and ASTM C 1567, with different mix proportions were prepared using aggregates of Kerman, such as: none admixture and plasticizer, different proportions of nano-silica separately. By opening the moulds after 24 hour and curing in water at $80^{\circ}C$ for 24 hour, then curing in (1N NaOH) at $80^{\circ}C$ for 14 days, length expansion of mortar bars were measured and compared. It was noted that, the lowest length expansion of a specimens shows the best proportion of admixture based on alkali-silica reactivity. Then, prediction of alkali-silica reaction of concrete has been investigated by using artificial neural network. In this study the backpropagation network has been used and compared with different algorithms to train network. Finally, the best amount of nano silica for adding to mix proportion, also the best algorithm and number of neurons in hidden layer of artificial neural network have been offered.

무선 센서 네트워크에서 NanoQplus를 이용한 DYMO 프로토콜 설계와 구현 (Design and Implementation of DYMO Protocol Using NanoQplus in Wireless Sensor Networks)

  • 오수택;배장식;정홍종;김동균;박정수
    • 한국통신학회논문지
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    • 제33권4B호
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    • pp.184-191
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    • 2008
  • 한국전자통신연구원에서 개발한 NanoQplus는 센서 네트워크 운용을 위한 임베디드 운영체제로, 프로그래머에게 친숙한 다중 쓰레드 프로그래밍 환경을 제공하지만 잘 알려진 TinyOS와 같은 운영체제와 비교해볼 때 네트워크 프로토콜 스택이 빈약하다는 단점이 있다. 본 논문에서는 Internet Engineering Task Force (IETF)에서 표준화 중인 Dynamic MANET On-demand (DYMO) 라우팅 프로토콜을 NanoQplus에 적용해본다. DYMO 프로토콜은 본래 이동 애드혹 네트워크에 적합하도록 제안된 라우팅 프로토콜이며, 이동 애드혹 네트워크는 무선 센서 네트워크에 비해 자원의 제약에서 자유로우므로, 기본 DYMO 프로토콜을 아무런 수정 없이 무선 센서 네트워크에 적용하기는 힘들다. 게다가 매체 접근 제어 계층과 네트워크 계층 사이에 존재하는 중복되는 데이터를 줄이기 위해 두 계층 프로토콜간의 결합도도 고려할 필요가 있다. 따라서 우리는 DYMO 기본 명세를 수정하여 NanoQplus에 적합토록 수정하였다. 실제 센서 노드에서의 실험 결과를 통해 NanoQplus에 기반을 둔 DYMO 프로토콜이 무선센서 네트워크 시나리오에서 효율적으로 동작함을 알 수 있었다.

${\mu}TMO$ 모델 기반 실시간 센서 네트워크 운영체제 ([ ${\mu}TMO$ ] Model based Real-Time Operating System for Sensor Network)

  • 이재안;허신;최병규
    • 한국정보과학회논문지:시스템및이론
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    • 제34권12호
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    • pp.630-640
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    • 2007
  • 센서 네트워크의 응용 범위가 점차 넓어지면서 군사 분야나 방사능 감지와 같이 실시간성을 요구하는 응용분야가 생겨나게 되었다. 하지만 기존의 센서 운영체제 연구는 효율적인 자원 활용에 초점을 두고 연구가 진행되었기 때문에 실시간성을 만족시켜 주기 어려운 구조를 가지고 있다. 본 논문에서는 정시성을 보장하는 실시간 분산 객체 TMO 모델을 센서 네트워크의 제한된 자원 환경에 알맞도록 경량화 시킨 ${\mu}TMO$ 모델을 제안한다. ${\mu}TMO$ 모델을 이용한 실시간 센서 네트워크 운영체제를 개발하기 위하여 한국전자통신연구원에서 개발한 센서 노드용 운영체제인 Nano-Q+를 이용하였다. Nano-Q+의 타이머 모듈을 높은 해상도를 가질 수 있도록 수정하였으며, EDF(Earliest-Deadline-First)기반의 실시간 스케줄러에 CST(Context Switch Threshold)와 PAS(Power Aware Scheduling) 기법을 적용하여 센서 노드에 적합한 실시간 스케줄러로 변경하였다. ${\mu}TMO$ 모델을 지원하기 위해 채널 기반의 통신 수단인 ITC-Channel을 새롭게 구현하였으며, 주기적인 스레드를 관리하는 WTMT(Watchdog TMO Management Task) 모듈을 구현하여 SpM 스레드를 주기에 맞게 실행할 수 있도록 하였다.

Effect of Reaction Conditions on the Preparation of Nano-sized Ni Powders inside a Nonionic Polymer

  • Kim, Tea-Wan;Kim, Dong-Hyun;Park, Hong-Chae;Yoon, Seog-Young
    • 한국분말야금학회:학술대회논문집
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    • 한국분말야금학회 2006년도 Extended Abstracts of 2006 POWDER METALLURGY World Congress Part 1
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    • pp.462-463
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    • 2006
  • Monodispersed and nano-sized Ni powders were synthesized from aqueous nickel sulfate hexahydrate $(NiSO_4{\cdot}6H_2O)$ inside nonionic polymer network by using wet chemical reduction process. The sucrose was used as a nonionic polymer network source. The effect of reaction conditions such as the amount of sucrose and a various reaction temperature, nickel sulfate hexahydrate molarity. The influence of a nonionic polymer network on the particle size of the prepared Ni powders was characterized by means of X-ray diffraction (XRD), scanning electron microscopy (SEM), and particle size analysis (PSA). The results showed that the obtained Ni powders were strong by dependent of the reaction conditions. In particular, the Ni powders prepared inside a nonionic polymer network had smooth spherical shape and narrow particle size distribution.

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Analyzing the mechano-bactericidal effect of nano-patterned surfaces by finite element method and verification with artificial neural networks

  • Ecren Uzun Yaylaci;Murat Yaylaci;Mehmet Emin Ozdemir;Merve Terzi;Sevval Ozturk
    • Advances in nano research
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    • 제15권2호
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    • pp.165-174
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    • 2023
  • The study investigated the effect of geometric structures of nano-patterned surfaces, such as peak sharpness, height, width, aspect ratio, and spacing, on mechano-bactericidal properties. Here, in silico models were developed to explain surface interactions with Escherichia coli. Numerical solutions were performed based on the finite element method and verified by the artificial neural network method. An E. coli cell adhered to the nano surface formed elastic and creep deformation models, and the cells' maximum deformation, maximum stress, and maximum strain were calculated. The results determined that the increase in peak sharpness, aspect ratio, and spacing values increased the maximum deformation, maximum stress, and maximum strain on E. coli cell. In addition, the results showed that FEM and ANN methods were in good agreement with each other. This study proved that the geometrical structures of nano-patterned surfaces have an important role in the mechano-bactericidal effect.

Enhancing cloud computing security: A hybrid machine learning approach for detecting malicious nano-structures behavior

  • Xu Guo;T.T. Murmy
    • Advances in nano research
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    • 제15권6호
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    • pp.513-520
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    • 2023
  • The exponential proliferation of cutting-edge computing technologies has spurred organizations to outsource their data and computational needs. In the realm of cloud-based computing environments, ensuring robust security, encompassing principles such as confidentiality, availability, and integrity, stands as an overarching imperative. Elevating security measures beyond conventional strategies hinges on a profound comprehension of malware's multifaceted behavioral landscape. This paper presents an innovative paradigm aimed at empowering cloud service providers to adeptly model user behaviors. Our approach harnesses the power of a Particle Swarm Optimization-based Probabilistic Neural Network (PSO-PNN) for detection and recognition processes. Within the initial recognition module, user behaviors are translated into a comprehensible format, and the identification of malicious nano-structures behaviors is orchestrated through a multi-layer neural network. Leveraging the UNSW-NB15 dataset, we meticulously validate our approach, effectively characterizing diverse manifestations of malicious nano-structures behaviors exhibited by users. The experimental results unequivocally underscore the promise of our method in fortifying security monitoring and the discernment of malicious nano-structures behaviors.

Measurement of Brownian motion of nanoparticles in suspension using a network-based PTV technique

  • Banerjee A.;Choi C. K.;Kihm K. D.;Takagi T.
    • 한국가시화정보학회:학술대회논문집
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    • 한국가시화정보학회 2004년도 Proceedings of 2004 Korea-Japan Joint Seminar on Particle Image Velocimetry
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    • pp.91-110
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    • 2004
  • A comprehensive three-dimensional nano-particle tracking technique in micro- and nano-scale spatial resolution using the Total Internal Reflection Fluorescence Microscope (TIRFM) is discussed. Evanescent waves from the total internal reflection of a 488nm argon-ion laser are used to measure the hindered Brownian diffusion within few hundred nanometers of a glass-water interface. 200-nm fluorescence-coated polystyrene spheres are used as tracers to achieve three-dimensional tracking within the near-wall penetration depth. A novel ratiometric imaging technique coupled with a neural network model is used to tag and track the tracer particles. This technique allows for the determination of the relative depth wise locations of the particles. This analysis, to our knowledge is the first such three-dimensional ratiometric nano-particle tracking velocimetry technique to be applied for measuring Brownian diffusion close to the wall.

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A hybrid artificial intelligence and IOT for investigation dynamic modeling of nano-system

  • Ren, Wei;Wu, Xiaochen;Cai, Rufeng
    • Advances in nano research
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    • 제13권2호
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    • pp.165-174
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    • 2022
  • In the present study, a hybrid model of artificial neural network (ANN) and internet of things (IoT) is proposed to overcome the difficulties in deriving governing equations and numerical solutions of the dynamical behavior of the nano-systems. Nano-structures manifest size-dependent behavior in response to static and dynamic loadings. Nonlocal and length-scale parameters alongside with other geometrical, loading and material parameters are taken as input parameters of an ANN to observe the natural frequency and damping behavior of micro sensors made from nanocomposite material with piezoelectric layers. The behavior of a micro-beam is simulated using famous numerical methods in literature under base vibrations. The ANN was further trained to correlate the output vibrations to the base vibration. Afterwards, using IoT, the electrical potential conducted in the sensors are collected and converted to numerical data in an embedded mini-computer and transferred to a server for further calculations and decision by ANN. The ANN calculates the base vibration behavior with is crucial in mechanical systems. The speed and accuracy of the ANN in determining base excitation behavior are the strengths of this network which could be further employed by engineers and scientists.

Application of Polymer Network Liquid Crystal to Mobile Display and its Electro-Optical Characteristics

  • Woo, Sung-Ho;Jeon, Chan-Wook;Yang, Kee-Jeong;Choi, Byeong-Dae;Rajesh, Kumar;Ahn, Byung-Chul
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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    • pp.1473-1475
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    • 2006
  • The electro-optic properties of an active-matrix polymer network liquid crystal display (AM-PNLCD) with crossed polarizer films to improve its contrast ratio were evaluated. By using crossed polarizer films, it shows good contrast ratio as well as wide viewing angle and adequate response time at normal TFT-twisted nematic (TN) LCD driving voltage (2.8V).

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