• 제목/요약/키워드: Boost network

검색결과 141건 처리시간 0.024초

Non-destructive assessment of the three-point-bending strength of mortar beams using radial basis function neural networks

  • Alexandridis, Alex;Stavrakas, Ilias;Stergiopoulos, Charalampos;Hloupis, George;Ninos, Konstantinos;Triantis, Dimos
    • Computers and Concrete
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    • 제16권6호
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    • pp.919-932
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    • 2015
  • This paper presents a new method for assessing the three-point-bending (3PB) strength of mortar beams in a non-destructive manner, based on neural network (NN) models. The models are based on the radial basis function (RBF) architecture and the fuzzy means algorithm is employed for training, in order to boost the prediction accuracy. Data for training the models were collected based on a series of experiments, where the cement mortar beams were subjected to various bending mechanical loads and the resulting pressure stimulated currents (PSCs) were recorded. The input variables to the NN models were then calculated by describing the PSC relaxation process through a generalization of Boltzmannn-Gibbs statistical physics, known as non-extensive statistical physics (NESP). The NN predictions were evaluated using k-fold cross-validation and new data that were kept independent from training; it can be seen that the proposed method can successfully form the basis of a non-destructive tool for assessing the bending strength. A comparison with a different NN architecture confirms the superiority of the proposed approach.

Investigations on aerosols transport over micro- and macro-scale settings of West Africa

  • Emetere, Moses Eterigho
    • Environmental Engineering Research
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    • 제22권1호
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    • pp.75-86
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    • 2017
  • The aerosol content dynamics in a virtual system were investigated. The outcome was extended to monitor the mean concentration diffusion of aerosols in a predefined macro and micro scale. The data set used were wind data set from the automatic weather station; satellite data set from Total Ozone Mapping Spectrometer aerosol index and multi-angle imaging spectroradiometer; ground data set from Aerosol robotic network. The maximum speed of the macro scale (West Africa) was less than 4.4 m/s. This low speed enables the pollutants to acquire maximum range of about 15 km. The heterogeneous nature of aerosols layer in the West African atmosphere creates strange transport pattern caused by multiple refractivity. It is believed that the multiple refractive concepts inhibit aerosol optical depth data retrieval. It was also discovered that the build-up of the purported strange transport pattern with time has enormous potential to influence higher degrees of climatic change in the long term. Even when the African Easterly Jet drives the aerosols layer at about 10 m/s, the interacting layers of aerosols are compelled to mitigate its speed to about 4.2 m/s (macro scale level) and boost its speed to 30 m/s on the micro scale level. Mean concentration diffusion of aerosols was higher in the micro scale than the macro scale level. The minimum aerosol content dynamics for non-decaying, logarithmic decay and exponential decay particulates dispersion is given as 4, 1.4 and 0 respectively.

IT자산과 정보보호 서비스가 정보보호 품질 및 만족도에 미치는 영향에 관한 실증연구 (An Empirical Approach to the Influence of IT Assets and Information Security Service on Information Security Quality and Satisfaction)

  • 권순재;이건창;김창현
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2006년도 추계학술대회
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    • pp.467-481
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    • 2006
  • In the era of the Internet and ubiquitous computing, IS users are still facing a variety of threats. Therefore, a need of more tightened information security service increases unprecedentedly. In this sense, this study is aimed at proposing a new research model in which IT assets (i.e., network, system, and information influence) and Information Security Service (i.e., confidentiality, integrity, nonrepudiation, authentication) affect information security qualty positively, leading to users' satisfaction eventually To prove the validity of the proposed research model, PLS analysis is applied with valid 177 questionnaires. Results reveal that both IT assets and Information Security Service influence informations security quality positively, and user satisfaction as well. From the results, it can be concluded that Korean government's recent orchestrated efforts to boost the IT assets and Information Security Service helped great improve the information security quality and user satisfaction.

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프랜차이즈산업에서의 RFID 적용 방법에 대한 연구 (A Study on RFID Application Method in Franchise Business)

  • 임재석;최원용
    • 대한안전경영과학회지
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    • 제10권4호
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    • pp.189-198
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    • 2008
  • At present, companies write daily work record or use bar-code in order to collect distribution flow data in real time. However, it needs additional works to check the record or read the bar-code with a scanner. In this case, human error could decrease accuracy of data and it would cause problems in reliability. To solve this problem, RFID (Radio Frequency Identification) is introduced in many automatic recognition sector recently. RFID is a technology that identification data is inserted into micro-mini IC chip and recognize, trace, and manage object, animal, or person using wireless frequency. This is being emerged as the core technology in future ubiquitous environment. This study is intended to suggest RFID application method in franchise business. Traceability and visibility of individual product are supplied based on EPCglobal network. It includes DW system which supplies various assessment data about product in supply chain, financial transaction system which is based on product transaction and position information, and RFID middleware which refines and divides product data from RFID tag. With the suggested application methods, individual product's profile data are supplied in real time and it would boost reliability to customer and make effective cooperation with existing operation systems (SCM, CRM, and e-Business) possible.

다중 시구간 신경회로망을 이용한 인간 행동 인식 (Human Activity Recognition using Multi-temporal Neural Networks)

  • 이현진
    • 디지털콘텐츠학회 논문지
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    • 제18권3호
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    • pp.559-565
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    • 2017
  • 스마트폰에 내장된 가속도 센서를 이용하여 사용자의 동작 상태나 행동을 인식하기 위한 연구가 다양하게 진행되어 왔다. 본 논문에서는 스마트폰의 3D 가속도 정보에 신경회로망을 적용하여 사람의 행동을 인식하는 연구를 진행하였다. 시계열 데이터를 신경회로망에 그대로 적용하면 성능상의 문제가 발생한다. 따라서 여러 시구간에 대해 특징을 추출하여 각 시구간에 대해 신경회로망을 학습시키고, 이 신경회로망들의 출력들을 입력으로 하여 학습하여 구성하는 다중 시구간 신경회로망을 제안하였다. 제안하는 방법을 실제 가속도 데이터에 적용한 결과 SVM, AdaBoost, IBk 등 다른 분류기보다 우수한 성능을 보였다.

새로운 H-type 스너버를 이용한 차량 헤드램프용 고효율 컨버터 (High-Efficiency Converter for Automotive Headlamp Using New H-type Snubber)

  • 김성주;김선필;정태욱;박성준;박성미
    • 조명전기설비학회논문지
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    • 제29권10호
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    • pp.65-72
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    • 2015
  • Recently, LED light has been increasingly adopted for vehicles in both domestic and foreign automotive markets, while a variety of LED lights have been developed to be used particularly for headlamps. In this paper, we propose an H-type resonant snubber circuit topology for high efficiency of vehicle LDM (LED Driver Module) and realized LDM functions for vehicle headlamp by designing high-efficiency convertors. In addition, this study reduced the financial burden by configuring the system to control the whole with micom except for the use of individual dedicated chips to drive LED for high and low beam. In order to verify the validity of the proposed H-type resonant snubber capable of soft switching, simulations were performed using PSIM. As a result, the validity was experimentally verified by creating a prototype. Moreover, in order to actually attach the headlamp, the performance of the proposed convertor was confirmed by designing LDM to the limited size. Communications between the headlamp and higher controller were realized using LIN(Local Interconnect Network).

EpiLoc: Deep Camera Localization Under Epipolar Constraint

  • Xu, Luoyuan;Guan, Tao;Luo, Yawei;Wang, Yuesong;Chen, Zhuo;Liu, WenKai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권6호
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    • pp.2044-2059
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    • 2022
  • Recent works have shown that the geometric constraint can be harnessed to boost the performance of CNN-based camera localization. However, the existing strategies are limited to imposing image-level constraint between pose pairs, which is weak and coarse-gained. In this paper, we introduce a pixel-level epipolar geometry constraint to vanilla localization framework without the ground-truth 3D information. Dubbed EpiLoc, our method establishes the geometric relationship between pixels in different images by utilizing the epipolar geometry thus forcing the network to regress more accurate poses. We also propose a variant called EpiSingle to cope with non-sequential training images, which can construct the epipolar geometry constraint based on a single image in a self-supervised manner. Extensive experiments on the public indoor 7Scenes and outdoor RobotCar datasets show that the proposed pixel-level constraint is valuable, and helps our EpiLoc achieve state-of-the-art results in the end-to-end camera localization task.

흉부 X-선 영상을 이용한 14 가지 흉부 질환 분류를 위한 Ensemble Knowledge Distillation (Ensemble Knowledge Distillation for Classification of 14 Thorax Diseases using Chest X-ray Images)

  • 호티키우칸;전영훈;곽정환
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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    • pp.313-315
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    • 2021
  • Timely and accurate diagnosis of lung diseases using Chest X-ray images has been gained much attention from the computer vision and medical imaging communities. Although previous studies have presented the capability of deep convolutional neural networks by achieving competitive binary classification results, their models were seemingly unreliable to effectively distinguish multiple disease groups using a large number of x-ray images. In this paper, we aim to build an advanced approach, so-called Ensemble Knowledge Distillation (EKD), to significantly boost the classification accuracies, compared to traditional KD methods by distilling knowledge from a cumbersome teacher model into an ensemble of lightweight student models with parallel branches trained with ground truth labels. Therefore, learning features at different branches of the student models could enable the network to learn diverse patterns and improve the qualify of final predictions through an ensemble learning solution. Although we observed that experiments on the well-established ChestX-ray14 dataset showed the classification improvements of traditional KD compared to the base transfer learning approach, the EKD performance would be expected to potentially enhance classification accuracy and model generalization, especially in situations of the imbalanced dataset and the interdependency of 14 weakly annotated thorax diseases.

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Advanced Bioremediation Strategies for Organophosphorus Compounds

  • Anish Kumar Sharma;Jyotsana Pandit
    • 한국미생물·생명공학회지
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    • 제51권4호
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    • pp.374-389
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    • 2023
  • Organophosphorus (OP) pesticides, particularly malathion, parathion, diazinon, and chlorpyrifos, are widely used in both agricultural and residential contexts. This refractory quality is shared by certain organ phosphorus insecticides, and it may have unintended consequences for certain non-target soil species. Bioremediation cleans organic and inorganic contaminants using microbes and plants. Organophosphate-hydrolyzing enzymes can transform pesticide residues into non-hazardous byproducts and are increasingly being considered viable solutions to the problem of decontamination. When coupled with system analysis, the multi-omics technique produces important data for functional validation and genetic manipulation, both of which may be used to boost the efficiency of bioremediation systems. RNA-guided nucleases and RNA-guided base editors include zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats (CRISPR), which are used to alter genes and edit genomes. The review sheds light on key knowledge gaps and suggests approaches to pesticide cleanup using a variety of microbe-assisted methods. Researches, ecologists, and decision-makers can all benefit from having a better understanding of the usefulness and application of systems biology and gene editing in bioremediation evaluations.

40MHz에서 1.6 dB 최소잡음지수를 얻는 잡음소거 기술에 근거한 광대역 저항성 LNA (Wideband Resistive LNA based on Noise-Cancellation Technique Achieving Minimum NF of 1.6 dB for 40MHz)

  • 최광석
    • 디지털산업정보학회논문지
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    • 제20권2호
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    • pp.63-74
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    • 2024
  • This Paper presents a resistive wideband fully differential low-noise amplifier (LNA) designed using a noise-cancellation technique for TV tuner applications. The front-end of the LNA employs a cascode common-gate (CG) configuration, and cross-coupled local feedback is employed between the CG and common-source (CS) stages. The moderate gain at the source of the cascode transistor in the CS stage is utilized to boost the transconductance of the cascode CG stage. This produces higher gain and lower noise figure (NF) than a conventional LNA with inductor. The NF can be further optimized by adjusting the local open-loop gain, thereby distributing the power consumption among the transistors and resistors. Finally, an optimized DC gain is obtained by designing the output resistive network. The proposed LNA, designed in SK Hynix 180 nm CMOS, exhibits improved linearity with a voltage gain of 10.7 dB, and minimum NF of 1.6-1.9 dB over a signal bandwidth of 40 MHz to 1 GHz.