Array codes correcting a cluster of unidirectional errors for two-dimensional matrix symbols [identification technology]

2004 ◽  
Author(s):  
H. Kaneko ◽  
E. Fujiwara
Keyword(s):  
Two Dimensional ◽  
Array Codes ◽  
Dimensional Matrix

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 A two-dimensional matrix Padé-type approximation in the inner product space

2009 ◽  
Vol 231 (2) ◽  
pp. 680-695 ◽  
Author(s):  
Youtian Tao ◽  
Chuanqing Gu
Keyword(s):  
Product Space ◽  
Inner Product Space ◽  
Inner Product ◽  
Two Dimensional ◽  
Type Approximation ◽  
Dimensional Matrix

Invariant lines in two‐dimensional matrix geometry

1987 ◽  
Vol 18 (1) ◽  
pp. 67-72
Author(s):  
M. C. Hughes†
Keyword(s):  
Two Dimensional ◽  
Dimensional Matrix

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

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.

Helicity Manipulation of a Double-Paddled Binaphthyl in a Two-Dimensional Matrix Field at the Air–Water Interface

ACS Nano ◽  
2020 ◽  
Vol 14 (10) ◽  
pp. 13294-13303 ◽  
Author(s):  
Masaki Ishii ◽  
Taizo Mori ◽  
Waka Nakanishi ◽  
Jonathan P. Hill ◽  
Hideki Sakai ◽  
...  
Keyword(s):  
Water Interface ◽  
Two Dimensional ◽  
Dimensional Matrix ◽  
Air Water Interface

993 poster ULTRAFAST TWO-DIMENSIONAL MATRIX X-RAY COLLIMATORS

2011 ◽  
Vol 99 ◽  
pp. S374
Author(s):  
O. Heid ◽  
T. Huges ◽  
T. Kluge ◽  
J. Heller
Keyword(s):  
Two Dimensional ◽  
X Ray ◽  
Dimensional Matrix
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