Digitalization system of ancient architecture decoration art based on neural network and image features

2020 ◽  
pp. 1-12
Author(s):  
Wu Xin ◽  
Qiu Daping
Keyword(s):  
Neural Network ◽  
Construction Industry ◽  
Three Dimensional ◽  
Performance Testing ◽  
Image Features ◽  
Three Dimensional Model ◽  
Performance Effect ◽  
Data Process ◽  
And Performance ◽  
Construction Mode

The inheritance and innovation of ancient architecture decoration art is an important way for the development of the construction industry. The data process of traditional ancient architecture decoration art is relatively backward, which leads to the obvious distortion of the digitalization of ancient architecture decoration art. In order to improve the digital effect of ancient architecture decoration art, based on neural network, this paper combines the image features to construct a neural network-based ancient architecture decoration art data system model, and graphically expresses the static construction mode and dynamic construction process of the architecture group. Based on this, three-dimensional model reconstruction and scene simulation experiments of architecture groups are realized. In order to verify the performance effect of the system proposed in this paper, it is verified through simulation and performance testing, and data visualization is performed through statistical methods. The result of the study shows that the digitalization effect of the ancient architecture decoration art proposed in this paper is good.

Tailoring Unique Neural-Network-Type Carbon Nanofibers Inserted in CoP/NC Polyhedrons for Robust Hydrogen Evolution Reaction

Nanoscale ◽  
2021 ◽  
Author(s):  
Xiaoyan Wang ◽  
Wenxi Zhao ◽  
Yang Fei ◽  
Yanjuan Sun ◽  
Fan Dong
Keyword(s):  
Neural Network ◽  
Hydrogen Evolution ◽  
Carbon Nanofibers ◽  
Hydrogen Evolution Reaction ◽  
Performance Enhancement ◽  
Three Dimensional ◽  
And Performance ◽  
Structural Innovation ◽  
Network Type

Three-dimensional catalysts have attracted great attention in the field of hydrogen evolution reaction (HER). It still, however, remains a great challenge in structural innovation and performance enhancement. Herein, we designed...

Design and Performance Testing of Three Dimensional Trapezia Structure for Fabric Keyboard Switch

2011 ◽  
Vol 332-334 ◽  
pp. 955-958
Author(s):  
Mei Ling Zhang ◽  
Rui Wang ◽  
Qian Qian Zhang
Keyword(s):  
Contact Resistance ◽  
Three Dimensional ◽  
Performance Testing ◽  
Smart Textile ◽  
And Performance ◽  
Further Development

Fabric keyboard is a field of smart textile. It can overcome many disadvantages of conventional keyboard. In order to study the fabric keyboard switch, trapezia structures of two kinds of orifice dimension are designed for example 8 wefts and 16 wefts. Different roots of conductive wires are woven into the down layer of the orifice part for each kind of orifice dimension. 4 and 8 roots of wires are woven for 8 wefts. 4, 8 and 16 roots of wires are woven for 16wefts. Then the immediate regain, connection pressure, connection ratio and contact resistance are tested and analyzed for every kind of fabric keyboard switch. It is concluded that 8 wefts orifice dimension and 8 roots of wires woven into the down layer of the orifice part is a better project. These findings may assist in recommendations regarding the further development of flexible fabric keyboard.

Role Ambiguity in Voluntary Sport Organizations

2009 ◽  
Vol 23 (5) ◽  
pp. 615-643 ◽  
Author(s):  
Jesse Sakires ◽  
Alison Doherty ◽  
Katie Misener
Keyword(s):  
Organizational Commitment ◽  
Role Ambiguity ◽  
Three Dimensional ◽  
Performance Outcomes ◽  
Role Clarity ◽  
Sport Organizations ◽  
Organizational Setting ◽  
Three Dimensional Model ◽  
Online Questionnaire ◽  
And Performance

This study examined perceptions and correlates of role ambiguity among sport administrators in voluntary sport organizations. Building on the seminal work of Kahn, Wolfe, Quinn, Snoek, and Rosenthal (1964), a multidimensional measure of role ambiguity in the organizational setting was developed for this purpose. The sample consisted of 79 paid staff and 143 volunteer board members from provincial voluntary sport organizations. Respondents completed an online questionnaire that included items pertaining to role ambiguity, job satisfaction, organizational commitment, effort, and demographic variables including age, gender, position, organization tenure, and position tenure. Preliminary support was found for a three-dimensional model of role ambiguity consisting of scope of responsibilities ambiguity, mean-sends knowledge ambiguity, and performance outcomes ambiguity. Role ambiguity was negatively associated with age, job tenure, and organization tenure, with more years of experience reflecting greater role clarity. Greater role ambiguity was also associated with lower levels of satisfaction, organizational commitment, and effort. In addition, ambiguity pertaining to scope of responsibilities was the primary predictor of both satisfaction and organizational commitment, while performance outcomes ambiguity and means-ends knowledge ambiguity significantly predicted effort. Implications for the management of role ambiguity in voluntary sport organizations, and the merits of a multidimensional approach to understanding this phenomenon, are discussed.

Structural Design and Performance Testing of Flexible Fabric Keyboard Switch

2009 ◽  
Vol 79-82 ◽  
pp. 1133-1136
Author(s):  
Mei Ling Zhang ◽  
Rui Wang
Keyword(s):  
Structural Design ◽  
Three Dimensional ◽  
Performance Testing ◽  
Primary Position ◽  
Insulating Layer ◽  
Complex Processes ◽  
Fabric Structure ◽  
Smart Textile ◽  
And Performance ◽  
Further Development

Flexible fabric keyboard is a field of smart textile. It can overcome traditional horniness keyboard can’t be foldable and washing. Because conventional keyboard’s switch is matrix circuit, two conductive layers are not touchable due to action of a middle insulating layer in relaxing. When the key is pressed, two conductive layers contact and form electric current. In this laboratory study there are two kinds of methods adopted, for example, Three-layer Fabric Weaved Separately (TFWS) and Three-layer Fabric Shaped Once(TFSO). They were significantly different in weaving methods, fabric structure and weaving efficiency. Three species were designed for every method. Although Connection Ratio (CR) of 6×6 and 8×8 in TFWS was 100%, TFWS took many repeating and complex processes. Much time and labor were seriously spent so that weaving efficiency was consumedly reduced. However, if making use of Three-layer Fabric Shaped Once(TFSO) which adopted three dimensional weaving method, only one procedure was required for fabric keyboard matrix circuit. The three dimensional weaving fabric consisted of support part and orifice part. When pressed in the key position, the top and down layer of the orifice part can contact with each other. Then the circuit can connect. When the applied force was released, the top and down layer can return to primary position due to the action of the support part. TFSO didn’t require many repetitive and complex courses. Therefore the weaving efficiency can be greatly increased. To be more importantly, CR of 16 wefts in TFSO was comparatively not bad among in three species of TFSO. When considering all six species for two methods together, 16 wefts in TFSO appears to provide the most suitable fabric for flexible fabric keyboard matrix circuit as a result of shaping once, high weaving efficiency and 100% CR. These findings may assist in recommendations regarding the further development of flexible fabric keyboard.

Modeling of Cell Deformation Under External Force Using Neural Network

2010 ◽  
Author(s):  
M. T. Ahmadian ◽  
G. R. Vossoughi ◽  
A. A. Abbasi ◽  
P. Raeissi
Keyword(s):  
Neural Network ◽  
Back Propagation ◽  
Three Dimensional ◽  
Point Load ◽  
Cell Deformation ◽  
Back Propagation Algorithm ◽  
Three Dimensional Model ◽  
Error Back Propagation ◽  
Injection Process ◽  
The Neural Network

Embryogenesis, regeneration and cell differentiation in microbiological entities are influenced by mechanical forces. Therefore, development of mechanical properties of these materials is important. Neural network technique is a useful method which can be used to obtain cell deformation by the means of force-geometric deformation data or vice versa. Prior to insertion in the needle injection process, deformation and geometry of cell under external point-load is a key element to understand the interaction between cell and needle. In this paper the goal is the prediction of cell membrane deformation under a certain force, and to visually estimate the force of indentation on the membrane from membrane geometries. The neural network input and output parameters are associated to a three dimensional model without the assumption of the adherent affects. The neural network is modeled by applying error back propagation algorithm. In order to validate the strength of the developed neural network model, the results are compared with the experimental data on mouse oocyte and mouse embryos that are captured from literature. The results of the modeling match nicely the experimental findings.

scholarly journals Design and Performance Testing of a Novel Three-Dimensional Elliptical Vibration Turning Device

Micromachines ◽  
2017 ◽  
Vol 8 (10) ◽  
pp. 305 ◽  
Author(s):  
Jieqiong Lin ◽  
Jinguo Han ◽  
Mingming Lu ◽  
Jiakang Zhou ◽  
Yan Gu ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Performance Testing ◽  
Elliptical Vibration ◽  
And Performance

Architectural Structure of Channel Sand Bodies in Meandering River and Remaining Oil Tapping Study-as on PI2a of South-Two Area in Sanan Field

2011 ◽  
Vol 361-363 ◽  
pp. 8-14
Author(s):  
Zong Bao Liu ◽  
He Bi
Keyword(s):  
Quantitative Research ◽  
Single Point ◽  
Three Dimensional ◽  
Three Dimensional Model ◽  
Point Bar ◽  
Verification Methods ◽  
Remaining Oil ◽  
Point Bars ◽  
And Performance ◽  
Sand Bodies

According to the theory of reservoir architectural structure and sedimentology, applied the hierarchy analysis, pattern guidance and performance verification methods, taking the South-Two area for example, with the cores, logs and performance, we have done some quantitative research on the parameters of composite channel sand bodies, single point bar sand bodies and the lateral accretion bodies on point bars in South two area, built Three-dimensional model of point bars. Study shows that the point bar sand bodies in PI2a unit are meandering point bar sand bodies formed by the lateral accretion of distributary channels in coastal delta distributary plain. The space combination model of lateral accretion bodies is horizontal-obique type. The width of lateral accretion bodies is 38.5～54m, the average dip of lateral accretion layer is 9.5°, and separation of lateral accretion layer is about 15m. The features above shows the spatial distribution of the lateral accretion body on point bars. With the changes of seepage field and gravity, the influence to remaining oil of lateral accretion layer has been analyzed. Numerical simulation and performance showed that the main concentration of remaining oil is in the upper of the point bar lateral accretion body, proposed the principles and methods of horizontal wells in the point bar sand bodies to tapping potential remaining oil, which provide a theoretical guidance to domestic similar fine reservoir description and the remaining oil tapping.

Rapid postearthquake safety evaluation of buildings using sparse acceleration measurements

2020 ◽  
pp. 147592172093629 ◽  
Author(s):  
Koji Tsuchimoto ◽  
Yasutaka Narazaki ◽  
Vedhus Hoskere ◽  
Billie F Spencer
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Nonlinear Model ◽  
Damage Index ◽  
Three Dimensional ◽  
Safety Evaluation ◽  
Training Data ◽  
Seismic Events ◽  
Analysis Model ◽  
Three Dimensional Model

After a seismic event, buildings need to be inspected to confirm their safety prior to reoccupation. As such, the rapid evaluation of the condition of individual buildings is important for minimizing disruption to lives and business. However, traditional manual inspection by experts is laborious and time-consuming. Structural health monitoring provides the potential to accelerate the required evaluation. This article proposes a cost-effective approach for rapid safety evaluation of buildings after seismic events using sparse acceleration measurements. First, a damage-sensitive feature is defined that can be used to infer the condition of buildings. Herein, the maximum interstory drift angle is proposed as a reliable damage index to classify the safety of buildings after seismic events. A convolutional neural network is then employed to uncover the complex relationship between the damage-sensitive features and the building condition. A five-story steel building is considered to validate the proposed approach. First, a three-dimensional nonlinear model of the building is created. To generate the required training data, a simplified nonlinear model is developed, along with a corresponding linear model, as use of the three-dimensional model is too computationally expensive. The training data for the convolutional neural network incorporates uncertainties in both the analysis model and the ground motion. Initial evaluation is conducted using the simplified nonlinear model, while final validation of the proposed approach is performed using the results of the three-dimensional nonlinear analysis model subjected to historical earthquakes. The results demonstrate the ability of the proposed approach to accommodate differences between the in-situ structure and the analysis model, as well as the efficacy of this approach for rapid postearthquake safety evaluation of buildings.

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