Two-dimensional matrix-based non-complex axis-of-rotation error modeling

2016 ◽  
Vol 44 ◽  
pp. 93-108 ◽  
Author(s):  
Jimmie Miller
Keyword(s):  
Error Modeling ◽  
Two Dimensional ◽  
Rotation Error ◽  
Dimensional Matrix ◽  
Axis Of Rotation

Deep convolutional neural networks for human movement detection using wireless signals

2021 ◽  
pp. 1-10
Author(s):  
Chien-Cheng Leea ◽  
Zhongjian Gao ◽  
Xiu-Chi Huanga
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Convolutional Neural Network ◽  
Detection System ◽  
Deep Convolutional Neural Network ◽  
Human Detection ◽  
Two Dimensional ◽  
Dimensional Matrix ◽  
State Classification ◽  
Propagation Paths

This paper proposes a Wi-Fi-based indoor human detection system using a deep convolutional neural network. The system detects different human states in various situations, including different environments and propagation paths. The main improvements proposed by the system is that there is no cameras overhead and no sensors are mounted. This system captures useful amplitude information from the channel state information and converts this information into an image-like two-dimensional matrix. Next, the two-dimensional matrix is used as an input to a deep convolutional neural network (CNN) to distinguish human states. In this work, a deep residual network (ResNet) architecture is used to perform human state classification with hierarchical topological feature extraction. Several combinations of datasets for different environments and propagation paths are used in this study. ResNet’s powerful inference simplifies feature extraction and improves the accuracy of human state classification. The experimental results show that the fine-tuned ResNet-18 model has good performance in indoor human detection, including people not present, people still, and people moving. Compared with traditional machine learning using handcrafted features, this method is simple and effective.

scholarly journals On the 3D → 2D Isomerization of Hexaborane(12)

Chemistry ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 28-38
Author(s):  
Josep M. Oliva-Enrich ◽  
Ibon Alkorta ◽  
José Elguero ◽  
Maxime Ferrer ◽  
José I. Burgos
Keyword(s):  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Transition States ◽  
Three Dimensional ◽  
Reaction Coordinate ◽  
Intrinsic Reaction Coordinate ◽  
Limiting Factor ◽  
Two Dimensional ◽  
Axis Of Rotation

By following the intrinsic reaction coordinate connecting transition states with energy minima on the potential energy surface, we have determined the reaction steps connecting three-dimensional hexaborane(12) with unknown planar two-dimensional hexaborane(12). In an effort to predict the potential synthesis of finite planar borane molecules, we found that the reaction limiting factor stems from the breaking of the central boron-boron bond perpendicular to the C2 axis of rotation in three-dimensional hexaborane(12).

scholarly journals Understanding Structure of Poverty Dimensions in East Java: Bicluster Approach

2017 ◽  
Vol 6 (2) ◽  
pp. 289-300 ◽  
Author(s):  
Budi Yuniarto ◽  
Robert Kurniawan
Keyword(s):  
Data Mining ◽  
Poverty Reduction ◽  
Multidimensional Poverty ◽  
Two Dimensional ◽  
View Point ◽  
Dimensional Matrix ◽  
Clustering Patterns

Poverty is still become a main problem for Indonesia, where recently, the view point of poverty is not just from income or consumption, but it’s defined multidimensionally. The understanding of the structure of multidimensional poverty is essential to government to develop policies for poverty reduction. This paper aims to describe the structure of poverty in East Java by using variables forming the dimensions of poverty and to investigate any clustering patterns in the region of East Java with considering the poverty variables using biclustering method. Biclustering is an unsupervised technique in data mining where we are grouping scalars from the two-dimensional matrix. Using bicluster analysis, we found two bicluster where each bicluster has different characteristics.DOI: 10.15408/sjie.v6i2.4769

scholarly journals FOUR-DIMENSIONAL BALL IN A GRAPHIC REPRESENTATION

2021 ◽  
pp. 37-46
Author(s):  
Helena Bidnichenko
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Geometric Modelling ◽  
Vector Model ◽  
Original Position ◽  
Two Dimensional ◽  
Axis Of Rotation ◽  
Dimensional Ball ◽  
Three Dimensional Space ◽  
Horizontal Vector

The paper presents a method for geometric modelling of a four-dimensional ball. For this, the regularities of the change in the shape of the projections of simple geometric images of two-dimensional and three-dimensional spaces during rotation are considered. Rotations of a segment and a circle around an axis are considered; it is shown that during rotation the shape of their projections changes from the maximum value to the degenerate projection. It was found that the set of points of the degenerate projection belongs to the axis of rotation, and each n-dimensional geometric image during rotation forms a body of a higher dimension, that is, one that belongs to (n + 1) -dimensional space. Identified regularities are extended to the four-dimensional space in which the ball is placed. It is shown that the axis of rotation of the ball will be a degenerate projection in the form of a circle, and the ball, when rotating, changes its size from a volumetric object to a flat circle, then increases again, but in the other direction (that is, it turns out), and then in reverse order to its original position. This rotation is more like a deformation, and such a ball of four-dimensional space is a hypersphere. For geometric modelling of the hypersphere and the possibility of its projection image, the article uses the vector model proposed by P.V. Filippov. The coordinate system 0xyzt is defined. The algebraic equation of the hypersphere is given by analogy with the three-dimensional space along certain coordinates of the center a, b, c, d. A variant of hypersection at t = 0 is considered, which confirms by equations obtaining a two-dimensional ball of three-dimensional space, a point (a ball of zero radius), which coincides with the center of the ball, or an imaginary ball. For the variant t = d, the equation of a two-dimensional ball is obtained, in which the radius is equal to R and the coordinates of all points along the 0t axis are equal to d. The variant of hypersection t = k turned out to be interesting, in which the equation of a two-dimensional sphere was obtained, in which the coordinates of all points along the 0t axis are equal to k, and the radius is . Horizontal vector projections of hypersection are constructed for different values of k. It is concluded that the set of horizontal vector projections of hypersections at t = k defines an ellipse.  

The Loyal Traveler: Examining a Typology of Service Patronage

1997 ◽  
Vol 35 (4) ◽  
pp. 2-10 ◽  
Author(s):  
Mark P. Pritchard ◽  
Dennis R. Howard
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Service Providers ◽  
Two Dimensional ◽  
Composite Measure ◽  
The Third ◽  
Dimensional Matrix ◽  
Repeat Purchase ◽  
Clear Support

The first goal of this study was to determine whether Day's (1969) measure of loyalty could be extended to better understand travel service patronage. Findings provide clear support that this composite measure, of repeat purchase and loyal attitude, is an effective approach to distinguishing the loyal traveler. A cluster analysis that combined scores on the composite measure from 428 travelers supported a two-dimensional matrix that identified four types of loyalty: true, spurious, latent, and low. This accomplished the study's second purpose by confirming that the four distinct levels of loyalty exist in a variety of service settings. Discriminant analysis was used to achieve the third objective — To identify those characteristics that differentiate the truly loyal patron. The resulting profile found this traveler to be a highly satisfied, symbolically involved consumer drawn to those services that exhibit an empathetic, caring concern for their patrons. These findings generate a much clearer understanding of how service providers can measure and manage their returning patrons.

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