• Title/Summary/Keyword: Layer Selection

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Estimation of Genetic Gains in Commercial Layer Breeding Population (상업용 난용종계 집단에서의 유전적 개량량 추정에 관한 연구)

  • 오봉국;최연호
    • Korean Journal of Poultry Science
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    • v.17 no.4
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    • pp.243-254
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    • 1990
  • This study was carried out to investigate the effectiveness of the selection for commercial populations of layer chickens subjected to multiple objectives. For that purpose, predicted selection responses obtained from estimated genetic parameters and observed values were compared. Data for two layer pure lines, Line-w(Single Comb White Leghorn) and Line-B (brown layer) which have been maintained at the Mani Breeding Farm were collected from 1980 to 1985 during 5 generations. The annual genetic gains were estimated by the moth of selection index in retrospect on the basis of selection differentials, phenotypic and genetic variance-covariance for the traits considered. SM was found to be shorten by 1.67 days and 1.14 days per generation in Line-W and Line-B. EN300 and EN400 were found to be increased by 4.15 and 5.92 per generation in Line-W and 257 and 3.73 per generation in Line-B. The annual gains realized were found to be significantly different from expected gains predicted on the basis of the annual selection differentials and genetic parameters in later generations, but it could not be concluded that the differences were attributed to genetic effects.

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Adaptive Inter-layer Filter Selection Mechanism for Improved Scalable Extensions of High Efficiency Video Coding (SHVC) (스케일러블 HEVC 부호화 효율 개선을 위한 계층 간 적응적 필터 선택 알고리즘)

  • Lee, Jong-Hyeok;Kim, Byung-Gyu
    • Journal of Digital Contents Society
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    • v.18 no.1
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    • pp.141-147
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    • 2017
  • Scalable extension of High Efficiency Video Coding (SHVC) standard uses the up-sampled residual data from the base layer to make a residual data in the enhancement layer. This paper describes an efficient algorithm for improving coding gain by using the filtered residual signal of base layer in the Scalable extension of High Efficiency Video Coding (SHVC). The proposed adaptive filter selection mechanism uses the smoothing and sharpening filters to enhance the quality of inter-layer prediction. Based on two filters and the existing up-sampling filter, a rate-distortion (RD)-cost fuction-based competitive scheme is proposed to get better quality of video. Experimental results showed that average BD-rate gains of 1.5%, 2.1%, and 1.7% for Y, U and V components, respectively, were achieved, compared with SHVC reference software 5.0, which is based on HEVC reference model (HM) 13.

Effect of QMix irrigant in removal of smear layer in root canal system: a systematic review of in vitro studies

  • Chia, Margaret Soo Yee;Parolia, Abhishek;Lim, Benjamin Syek Hur;Jayaraman, Jayakumar;de Moraes Porto, Isabel Cristina Celerino
    • Restorative Dentistry and Endodontics
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    • v.45 no.3
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    • pp.28.1-28.13
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    • 2020
  • Objectives: To evaluate the outcome of in vitro studies comparing the effectiveness of QMix irrigant in removing the smear layer in the root canal system compared with other irrigants. Materials and Methods: The research question was developed by using Population, Intervention, Comparison, Outcome and Study design framework. Literature search was performed using 3 electronic databases PubMed, Scopus, and EBSCOhost until October 2019. Two reviewers were independently involved in the selection of the articles and data extraction process. Risk of bias of the studies was independently appraised using revised Cochrane Risk of Bias tool (RoB 2.0) based on 5 domains. Results: Thirteen studies fulfilled the selection criteria. The overall risk of bias was moderate. QMix was found to have better smear layer removal ability than mixture of tetracycline isonomer, an acid and a detergent (MTAD), sodium hypochlorite (NaOCl), and phytic acid. The efficacy was less effective than 7% maleic acid and 10% citric acid. No conclusive results could be drawn between QMix and 17% ethylenediaminetetraacetic acid due to conflicting results. QMix was more effective when used for 3 minutes than 1 minute. Conclusions: QMix has better smear layer removal ability compared to MTAD, NaOCl, Tubulicid Plus, and Phytic acid. In order to remove the smear layer more effectively with QMix, it is recommended to use it for a longer duration.

Inductively coupled nanocomposite wireless strain and pH sensors

  • Loh, Kenneth J.;Lynch, Jerome P.;Kotov, Nicholas A.
    • Smart Structures and Systems
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    • v.4 no.5
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    • pp.531-548
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    • 2008
  • Recently, dense sensor instrumentation for structural health monitoring has motivated the need for novel passive wireless sensors that do not require a portable power source, such as batteries. Using a layer-by-layer self-assembly process, nano-structured multifunctional carbon nanotube-based thin film sensors of controlled morphology are fabricated. Through judicious selection of polyelectrolytic constituents, specific sensing transduction mechanisms can be encoded within these homogenous thin films. In this study, the thin films are specifically designed to change electrical properties to strain and pH stimulus. Validation of wireless communications is performed using traditional magnetic coil antennas of various turns for passive RFID (radio frequency identification) applications. Preliminary experimental results shown in this study have identified characteristic frequency and bandwidth changes in tandem with varying strain and pH, respectively. Finally, ongoing research is presented on the use of gold nanocolloids and carbon nanotubes during layer-by-layer assembly to fabricate highly conductive coil antennas for wireless communications.

A Comparative Study on the Buckling Characteristics of Single-layer and Double-layer Lattice Dome According to Rise ratio (라이즈비에 따른 단층 및 복층 래티스 돔의 좌굴특성에 관한 비교연구)

  • 권영환;정환목;석창목;박상훈
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1998.10a
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    • pp.283-289
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    • 1998
  • In the latticed domes which is a set of space frame, buckling is derived if the external force reaches a limitation by the lightness of the material and the minimization of the member section area. these are concerned with a geometric shape, network pattern, the number of layer, and so on. Most of all, the number of layer of the lattice dome is a important factor from the viewpoint of initial and structure design. Therefore this study compared buckling characteristics of single-layer with double-layer latticed domes and investigated the relativity of buckling-stress-ratio and member-density-ratio according to rise ratio to improve that designers could extend the range of .design selection

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Performance Analysis of Physical Layer Security using Partial Relay Selection in Cooperative Communication based on Decode-and-Forward with Multi-Relay (다수의 중계기가 존재하는 복호 후 재전송 기반 협력 통신 시스템에서 부분적인 중계기 선택을 사용하는 물리 계층 보안의 성능 분석)

  • Park, Sol;Kong, Hyung-Yun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.21-27
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    • 2019
  • In this paper, we investigate the secrecy outage probability when using a partial relay selection scheme in cooperative communication systems based on decode-and-forward with multi-relay. It is assumed that both the receiving node and the eavesdropping node receive signals at both the transmitting node and the relaying node. The two received signals are used to obtain the diversity gain using the MRC scheme. In this paper, we compute the theoretical formula of secrecy outage probability and compare the theoretical value with the simulation value to prove that equation is valid. The simulation results show how the secrecy outage probability varies with the number of relays.

Improvement of Cutting Conditions in End-milling Using Deep-layered Neural Networks (심층 신경회로망을 이용한 엔드밀 가공의 절삭 조건 개선)

  • Lee, Sin-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.26 no.4
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    • pp.402-409
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    • 2017
  • Selection of optimal cutting conditions is important for improving productivity and implementing efficient process control in metal machining. In this study, improvement of cutting conditions in machining using end-mills is studied by using deep-layered neural networks, which comprise an input layer, output layer, and two hidden layers. System networks are designed with inputs as cutting conditions, and they output the cutting force. A pseudo-inverse network is designed that has the adjustable cutting condition as output and cutting force and other cutting conditions as input. The combination of the system network and pseudo-inverse network enables selection or improvement of cutting conditions that results in the expected cutting force.

An Optimal Selective Protection Scheme for Scalable Video Coding

  • Hendry, Hendry;Kim, Munchurl
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2011.07a
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    • pp.294-295
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    • 2011
  • The fundamental problem of selective protection scheme for encoded bitstreams is to find an efficient algorithm to select the set of frames required to be encrypted that can maximize protection effect with the minimum amount of protected data is required. In this paper, we propose an optimal selective protection scheme for SVC bitstreams by protecting the best combination of frames for selective protection in the sense that the amount of data required for protection is minimized and the resulting visual quality degradation is maximized. The selection of the frames to be encrypted is done by first expressing R-Q (protection rate - visual quality) relationship with Lagragian cost model. The experimental results show that, compared to protecting SVC bitstreams layer by layer, the proposed scheme gives superior performance in terms of protection effectiveness due to its better selection of frames for protection given protection bit budgets.

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Neural Networks Based Modeling with Adaptive Selection of Hidden Layer's Node for Path Loss Model

  • Kang, Chang Ho;Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
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    • v.8 no.4
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    • pp.193-200
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    • 2019
  • The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

연결강도분석을 이용한 통합된 부도예측용 신경망모형

  • Lee Woongkyu;Lim Young Ha
    • Proceedings of the Korea Association of Information Systems Conference
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    • 2002.11a
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    • pp.289-312
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    • 2002
  • This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.

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