scholarly journals New Position Candidate Identification via Clustering toward an Extensible On-Body Smartphone Localization System

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1276
Author(s):  
Mitsuaki Saito ◽  
Kaori Fujinami
Keyword(s):  
Main Parameter ◽  
Spatial Clustering ◽  
Number Of Clusters ◽  
Localization System ◽  
Identification Process ◽  
Simulation Based ◽  
Optimal Value ◽  
The One ◽  
Unsupported Position ◽  
Candidate Identification

On-body device position awareness plays an important role in providing smartphone-based services with high levels of usability and quality. Traditionally, the problem assumed that the positions that were supported by the system were fixed at the time of design. Thus, if a user stores his/her terminal into an unsupported position, the system forcibly classifies it into one of the supported positions. In contrast, we propose a framework to discover new positions that are not initially supported by the system, which adds them as recognition targets via labeling by a user and re-training on-the-fly. In this article, we focus on a component of identifying a set of samples that are derived from a single storing position, which we call new position candidate identification. Clustering is applied as a key component to prepare a reliable dataset for re-training and to reduce the user’s burden of labeling. Specifically, density-based spatial clustering of applications with noise (DBSCAN) is employed because it does not require the number of clusters in advance. We propose a method of finding an optimal value of a main parameter, Eps-neighborhood (eps), which affects the accuracy of the resultant clusters. Simulation-based experiments show that the proposed method performs as if the number of new positions were known in advance. Furthermore, we clarify the timing of performing the new position candidate identification process, in which we propose criteria for qualifying a cluster as the one comprising a new position.

Innovation

2019 ◽  
pp. 438-510
Author(s):  
Sheilagh Ogilvie
Keyword(s):  
Technological Innovation ◽  
Diffusion Of Innovations ◽  
Spatial Clustering ◽  
Technological Knowledge ◽  
The Other ◽  
Market Failures ◽  
New Techniques ◽  
The One ◽  
And Diffusion

This chapter addresses how guilds dealt with technological innovation. Innovation is a final sphere in which market failures are widespread in premodern economies, as in modern ones. On the one hand, contemporaries frequently complained that guilds blocked new techniques and practices. On the other hand, guilds were in a position to generate cartel rents, and this might have encouraged their members to incur the costs of invention. Guilds might also have encouraged diffusion of technological knowledge through compulsory apprenticeship, mandatory travelling by journeymen, or the spatial clustering of practitioners. Guilds could also affect innovation unintentionally by things they did for other reasons. Guilds thus provide a rich context for investigating the role of different institutional mechanisms in encouraging the invention and diffusion of innovations.

Neural Network-Based Process Analysis in Sport

2011 ◽  
pp. 1212-1218 ◽  
Author(s):  
Juergen Perl
Keyword(s):  
Process Analysis ◽  
Original Data ◽  
Simulation Based ◽  
Communication Interaction ◽  
Mapping Process ◽  
Information Patterns ◽  
Kohonen Feature Map ◽  
The One ◽  
Adaptation Processes ◽  
A Current

Processes in sport like motions or games are influenced by communication, interaction, adaptation, and spontaneous decisions. Therefore, on the one hand, those processes are often fuzzy and unpredictable and so have not extensively been dealt with, yet. On the other hand, most of those processes structurally are roughly determined by intention, rules, and context conditions and so can be classified by means of information patterns deduced from data models of the processes. Self organizing neural networks of type Kohonen Feature Map (KFM) help for classifying information patterns – either by mapping whole processes to corresponding neurons (see Perl & Lames, 2000; McGarry & Perl, 2004) or by mapping process steps to neurons, which then can be connected by trajectories that can be taken as process patterns for further analyses (see examples below). In any case, the dimension of the original data (i.e. the number of contained attributes) is reduced to the dimension of the representing neuron (normally 2 or 3), which makes it much easier to deal with. Additionally, extensions of the KFM-approach are introduced, which are able to flexibly adjust the net to dynamically changing training situations. Moreover, those extensions allow for simulating adaptation processes like learning or tactical behaviour. Finally, a current project is introduced, where tactical processes in soccer are analysed under the aspect of simulation-based optimization.

Parameter sensitivity analysis and optimum model of the magnetorheological damper’s Bouc–Wen model

2020 ◽  
pp. 107754632095929
Author(s):  
Min Jiang ◽  
Xiaoting Rui ◽  
Wei Zhu ◽  
Fufeng Yang ◽  
Hongtao Zhu ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Fitness Function ◽  
Least Square Method ◽  
Least Square ◽  
Identification Process ◽  
Long Time ◽  
Method Optimization ◽  
Optimum Model ◽  
The One ◽  
Sensitive Parameters

To overcome the shortcomings of the Bouc–Wen model, such as too many parameters, complex identification process, and long time consuming, the sensitivity of parameters was analyzed. A Bouc–Wen optimum model with sensitive parameters to guarantee calculating accuracy was established. First, according to the results of the magnetorheological damper’s mechanical property test, the sensitivity of Bouc–Wen model’s parameters was analyzed by the one-at-a-time method. Optimization of the Bouc–Wen model was completed. Second, the parameters of the Bouc–Wen optimum model were identified under three harmonic excitations. Compared with the original Bouc–Wen model, the differences of calculation accuracy were 0.0055, 0.0007, and 0.0070 respectively. And the convergence rate of the fitness function for parameter identification increased by 67.89%, 49.94%, and 67.24%, respectively. And the iteration time of 1000 iterations was shortened by 36.52%, 25.95%, and 64.11%, respectively. It indicates that the Bouc–Wen optimum model had higher efficiency and certain accuracy in parameter identification process. Then, the calculation accuracy of Bouc–Wen optimum model with independent and coupled mean parameters were analyzed respectively. Finally, the parameters of the Bouc–Wen optimum model and current were fitted by the least square method. The results showed that the Bouc–Wen optimum model can accurately and efficiently simulate the dynamic characteristics of magnetorheological dampers.

scholarly journals Experimental Analysis and Simulation of Novel Technical Textile Reinforced Composite of Banana Fibre

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1134 ◽  
Author(s):  
Mario Monzón ◽  
Rubén Paz ◽  
Martí Verdaguer ◽  
Luis Suárez ◽  
Pere Badalló ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Predictive Modelling ◽  
Experimental Results ◽  
Average Error ◽  
Acceptable Error ◽  
Simulation Based ◽  
Banana Fibre ◽  
The One ◽  
Textile Reinforced Composite ◽  
Definition Of

The use of natural fibres allows reducing environmental impact, due to their natural renewable origin and the lower energy needed for their production and processing. This work presents the mechanical characterization of a newly developed technical textile, with banana fibre treated by enzymes, comparing experimental results with numerical simulation based on the definition of the unit cell at micromechanical level. The experimental test shows that the composite with the fabric of banana fibre presents worse mechanical behaviour than the one with commercial flax fibre. The presence of wool, necessary for producing the yarn, reduces the mechanical properties of the banana textile. The numerical simulation had an acceptable error compared with the experimental results, with a global average error of 9%, showing that the predictive modelling based on the multiscale method is suitable for the design process of this kind of composite.

scholarly journals Contractor’s bid pricing strategy: a model with correlation among competitors’ prices

2019 ◽  
Vol 9 (1) ◽  
pp. 159-166
Author(s):  
Piotr Jaśkowski ◽  
Agata Czarnigowska
Keyword(s):  
Probabilistic Method ◽  
Indirect Costs ◽  
Pricing Strategy ◽  
Bidding Strategy ◽  
Direct And Indirect Costs ◽  
Practical Applications ◽  
Construction Companies ◽  
Simulation Based ◽  
The One

AbstractThe approach used by construction companies to determine bid prices is an element of their strategy used to win jobs in competitive tenders. Such strategies build upon an analysis of the contactor’s potential and capabilities (am I able to deliver? am I eligible to participate in the tender?), and the analysis of the economic environment, including the expected behavior of competitors. The tender strategy sets out both the guidelines and the procedure in deciding whether or not to bid as well as the rules for determining the price. The price, on the one hand, should be high enough to cover expected direct and indirect costs as well as risk-adjusted profit. On the other hand, it needs to be low enough to be considered most attractive (typically: the lowest) among the prices offered by the competitors. The paper focuses on the price definition component of the bidding strategy. It provides a brief overview of the existing methods that support bidding decisions by comparing their demand for input and limitations in practical applications and presents a simulation-based method supporting the determination of the profit ratio. This probabilistic method assumes the existence of a positive correlation between the prices offered by the competitors. Its application is illustrated by means of a numerical example. The outcomes of the simulation prompt the amount of the profit margin that maximizes the expected value of the contractor’s profit.

scholarly journals Linear Regression with Optimal Rotation

Stats ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 416-425 ◽  
Author(s):  
George Livadiotis
Keyword(s):  
Linear Regression ◽  
Correlation Coefficient ◽  
Rotation Angle ◽  
Outer Region ◽  
Optimal Angle ◽  
Optimal Rotation ◽  
Optimal Value ◽  
The One ◽  
Optimal Rotation Angle ◽  
Selection Of

The paper shows how the linear regression depends on the selection of the reference frame. The slope of the fitted line and the corresponding Pearson’s correlation coefficient are expressed in terms of the rotation angle. The correlation coefficient is found to be maximized for a certain optimal angle, for which the slope attains a special optimal value. The optimal angle, the value of the optimal slope, and the corresponding maximum correlation coefficient were expressed in terms of the covariance matrix, but also in terms of the values of the slope, derived from the fitting at the nonrotated and right-angle-rotated axes. The potential of the new method is to improve the derived values of the fitting parameters by detecting the optimal rotation angle, that is, the one that maximizes the correlation coefficient. The presented analysis was applied to the linear regression of density and temperature measurements characterizing the proton plasma in the inner heliosheath, the outer region of our heliosphere.

scholarly journals Cluster Head Selection in a Homogeneous Wireless Sensor Network Ensuring Full Connectivity with Minimum Isolated Nodes

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Tapan Kumar Jain ◽  
Davinder Singh Saini ◽  
Sunil Vidya Bhooshan
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Research Work ◽  
Cluster Head ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Number Of Clusters ◽  
Minimum Number ◽  
The One

The research work proposes a cluster head selection algorithm for a wireless sensor network. A node can be a cluster head if it is connected to at least one unique neighbor node where the unique neighbor is the one that is not connected to any other node. If there is no connected unique node then the CH is selected on the basis of residual energy and the number of neighbor nodes. With the increase in number of clusters, the processing energy of the network increases; hence, this algorithm proposes minimum number of clusters which further leads to increased network lifetime. The major novel contribution of the proposed work is an algorithm that ensures a completely connected network with minimum number of isolated nodes. An isolated node will remain only if it is not within the transmission range of any other node. With the maximum connectivity, the coverage of the network is automatically maximized. The superiority of the proposed design is verified by simulation results done in MATLAB, where it clearly depicts that the total numbers of rounds before the network dies out are maximum compared to other existing protocols.

The optimal value of markov stopping problems with one-step look ahead policy

1988 ◽  
Vol 25 (3) ◽  
pp. 544-552 ◽  
Author(s):  
Masami Yasuda
Keyword(s):  
Random Number ◽  
Secretary Problem ◽  
Choice Problem ◽  
Best Choice Problem ◽  
Look Ahead ◽  
Optimal Value ◽  
One Step ◽  
The Difference ◽  
The One ◽  
A Charge

This paper treats stopping problems on Markov chains in which the OLA (one-step look ahead) policy is optimal. Its associated optimal value can be explicitly expressed by a potential for a charge function of the difference between the immediate reward and the one-step-after reward. As an application to the best choice problem, we shall obtain the value of three problems: the classical secretary problem, a problem with a refusal probability and a problem with a random number of objects.

Effect of Ball Material Ratio on the Grinding Efficiency of Copper-Bearing Minerals in Dahongshan

2012 ◽  
Vol 616-618 ◽  
pp. 619-623 ◽  
Author(s):  
Chun Mei Wang ◽  
Gu Zhang Zhuang ◽  
Hai Yin
Keyword(s):  
Critical Value ◽  
Optimal Range ◽  
Operation Optimization ◽  
Particle Size Fractions ◽  
Fine Grinding ◽  
Optimal Value ◽  
Value Range ◽  
Optimal Value Range ◽  
The One ◽  
Grinding Efficiency

In this paper, The Copper-bearing minerals Powder (≤2mm) in Dahongshan is used in conical ball grinding, the experimental study shows that the effect of ball material ratio on the grinding efficiency is obvious. The critical value and the optimal value range of the ball material ratio are different on different grinding stages, the feasible ball material ratio of coarse grinding is bigger than the one of fine grinding. In the test conditions, in terms of the ball material ratio, the critical value of ores’ over crushing in coarse grinding is 13, and the optimal range is 6-8, which is beneficial to the next beneficiation; while the critical value in fine grinding is 7 and the optimal range is 5-7. Although the ball material ratios are different, the change rule of grinding fineness corresponding to different particle size fractions is consistent, which can be used as a reference in the site operation optimization.

Numerical Investigation of Choking Cavitator Based on Orthogonal Experiment

2014 ◽  
Vol 599-601 ◽  
pp. 603-607
Author(s):  
Feng Hua Zhang ◽  
Li Wei Shan ◽  
Chuan Lin Tang
Keyword(s):  
Numerical Investigation ◽  
Orthogonal Experiment ◽  
Back Pressure ◽  
Entry Point ◽  
Characteristic Parameters ◽  
Optimal Flow ◽  
Simulation Based ◽  
Optimal Value ◽  
Optimal Values

The different structures of choking cavitator were studied by using numerically simulation based on the orthogonal experiment. Many different structures of choking cavitator were researched to get a set of parameters which can produce much stronger intensity of cavitation. The results of investigation show that the optimal values of characteristic parameters are the optimal flow value of 1.5 m3 / h, entry point of the optimal value of 35 o, the outlet diameter of 9 mm, the back pressure of 70 kPa and the throat length of 70 mm.

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