scholarly journals Generalized analytical model based on harmonic coupling for hybrid plasmonic modes: comparison with numerical and experimental results

2015 ◽  
Vol 23 (21) ◽  
pp. 27376 ◽  
Author(s):  
Mitradeep Sarkar ◽  
Jean-François Bryche ◽  
Julien Moreau ◽  
Mondher Besbes ◽  
Grégory Barbillon ◽  
...  
Keyword(s):  
Analytical Model ◽  
Experimental Results ◽  
Model Based

Convective Losses From Cavity Solar Receivers—Comparisons Between Analytical Predictions and Experimental Results

1983 ◽  
Vol 105 (1) ◽  
pp. 29-33 ◽  
Author(s):  
A. M. Clausing
Keyword(s):  
Experimental Data ◽  
Experimental Evidence ◽  
Analytical Model ◽  
Excellent Agreement ◽  
Experimental Results ◽  
Simple Analytical Model ◽  
Refined Model ◽  
Wall Area

Cavity solar receivers are generally believed to have higher thermal efficiencies than external receivers due to reduced losses. A simple analytical model was presented by the author which indicated that the ability to heat the air inside the cavity often controls the convective loss from cavity receivers. Thus, if the receiver contains a large amount of inactive hot wall area, it can experience a large convective loss. Excellent experimental data from a variety of cavity configurations and orientations have recently become available. These data provided a means of testing and refining the analytical model. In this manuscript, a brief description of the refined model is presented. Emphasis is placed on using available experimental evidence to substantiate the hypothesized mechanisms and assumptions. Detailed comparisons are given between analytical predictions and experimental results. Excellent agreement is obtained, and the important mechanisms are more clearly delineated.

scholarly journals Research of Personalized Recommendation Technology Based on Knowledge Graphs

2021 ◽  
Vol 11 (15) ◽  
pp. 7104
Author(s):  
Xu Yang ◽  
Ziyi Huan ◽  
Yisong Zhai ◽  
Ting Lin
Keyword(s):  
Neural Network ◽  
Hot Spot ◽  
Experimental Results ◽  
Graph Representation ◽  
Personalized Recommendation ◽  
Knowledge Graph ◽  
Learning Technology ◽  
Data Set ◽  
Model Based ◽  
Knowledge Graphs

Nowadays, personalized recommendation based on knowledge graphs has become a hot spot for researchers due to its good recommendation effect. In this paper, we researched personalized recommendation based on knowledge graphs. First of all, we study the knowledge graphs’ construction method and complete the construction of the movie knowledge graphs. Furthermore, we use Neo4j graph database to store the movie data and vividly display it. Then, the classical translation model TransE algorithm in knowledge graph representation learning technology is studied in this paper, and we improved the algorithm through a cross-training method by using the information of the neighboring feature structures of the entities in the knowledge graph. Furthermore, the negative sampling process of TransE algorithm is improved. The experimental results show that the improved TransE model can more accurately vectorize entities and relations. Finally, this paper constructs a recommendation model by combining knowledge graphs with ranking learning and neural network. We propose the Bayesian personalized recommendation model based on knowledge graphs (KG-BPR) and the neural network recommendation model based on knowledge graphs(KG-NN). The semantic information of entities and relations in knowledge graphs is embedded into vector space by using improved TransE method, and we compare the results. The item entity vectors containing external knowledge information are integrated into the BPR model and neural network, respectively, which make up for the lack of knowledge information of the item itself. Finally, the experimental analysis is carried out on MovieLens-1M data set. The experimental results show that the two recommendation models proposed in this paper can effectively improve the accuracy, recall, F1 value and MAP value of recommendation.

An Analysis of Conventional and Self-Aligned four Terminal Resistor Structures for The Determination of The Contact Resistivity from End Resistance Measurements

1986 ◽  
Vol 71 ◽  
Author(s):  
I. Suni ◽  
M. Finetti ◽  
K. Grahn
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Computer Model ◽  
Contact Resistivity ◽  
Experimental Results ◽  
The Finite Element Method ◽  
Model Based ◽  
A Value ◽  
And Diffusion

AbstractA computer model based on the finite element method has been applied to evaluate the effect of the parasitic area between contact and diffusion edges on end resistance measurements in four terminal Kelvin resistor structures. The model is then applied to Al/Ti/n+ Si contacts and a value of contact resistivity of Qc = 1.8×10−7.Ωcm2 is derived. For comparison, the use of a self-aligned structure to avoid parasitic effects is presented and the first experimental results obtained on Al/Ti/n+Si and Al/CoSi2/n+Si contacts are shown and discussed.

scholarly journals Adaptive Broadcasting Mechanism for Bandwidth Allocation in Mobile Services

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Gwo-Jiun Horng ◽  
Chi-Hsuan Wang ◽  
Chih-Lun Chou
Keyword(s):  
Analytical Model ◽  
Bandwidth Allocation ◽  
Data Dissemination ◽  
Data Access ◽  
Experimental Results ◽  
Bandwidth Utilization ◽  
Access Latency ◽  
The Mean ◽  
Access Efficiency ◽  
Broadcast Program

This paper proposes a tree-based adaptive broadcasting (TAB) algorithm for data dissemination to improve data access efficiency. The proposed TAB algorithm first constructs a broadcast tree to determine the broadcast frequency of each data and splits the broadcast tree into some broadcast wood to generate the broadcast program. In addition, this paper develops an analytical model to derive the mean access latency of the generated broadcast program. In light of the derived results, both the index channel’s bandwidth and the data channel’s bandwidth can be optimally allocated to maximize bandwidth utilization. This paper presents experiments to help evaluate the effectiveness of the proposed strategy. From the experimental results, it can be seen that the proposed mechanism is feasible in practice.

scholarly journals Person Reidentification Model Based on Multiattention Modules and Multiscale Residuals

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yongyi Li ◽  
Shiqi Wang ◽  
Shuang Dong ◽  
Xueling Lv ◽  
Changzhi Lv ◽  
...  
Keyword(s):  
Local Features ◽  
Attention Mechanism ◽  
Experimental Results ◽  
Original Network ◽  
Fine Grained ◽  
Backbone Network ◽  
Model Based ◽  
Local Branch ◽  
Feature Expression ◽  
Global And Local

At present, person reidentification based on attention mechanism has attracted many scholars’ interests. Although attention module can improve the representation ability and reidentification accuracy of Re-ID model to a certain extent, it depends on the coupling of attention module and original network. In this paper, a person reidentification model that combines multiple attentions and multiscale residuals is proposed. The model introduces combined attention fusion module and multiscale residual fusion module in the backbone network ResNet 50 to enhance the feature flow between residual blocks and better fuse multiscale features. Furthermore, a global branch and a local branch are designed and applied to enhance the channel aggregation and position perception ability of the network by utilizing the dual ensemble attention module, as along as the fine-grained feature expression is obtained by using multiproportion block and reorganization. Thus, the global and local features are enhanced. The experimental results on Market-1501 dataset and DukeMTMC-reID dataset show that the indexes of the presented model, especially Rank-1 accuracy, reach 96.20% and 89.59%, respectively, which can be considered as a progress in Re-ID.

Sign in / Sign up

Export Citation Format

Share Document