Centralized Algorithms Based on Clustering with Self-tuning of Parameters for Cooperative Target Observation

Clustering on target positions is a class of centralized algorithms used to calculate the surveillance robots' displacements in the Cooperative Target Observation (CTO) problem. This work proposes and evaluates Fuzzy C-means (FCM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) with K-means (DBSk) based self-tuning clustering centralized algorithms for the CTO problem and compares its performances with that of K-means. Two random motion patterns are adopted for the targets: in free space or on a grid. As a contribution, the work allows identifying ranges of problem configuration parameters in which each algorithm shows the highest average performance. As a first conclusion, in the challenging situation in which the relative speed of the targets is high, and the relative sensor range of the surveillance is low, for which the existing algorithms present a substantial drop in performance, the FCM algorithm proposed outperforms the others. Finally, the DBSk algorithm adapts very well in low execution frequency, showing promising results in this challenging situation.

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Analysis on the Effects of the Human Body on the Performance of Electro-Textile Antennas for Wearable Monitoring and Tracking Application

Materials ◽

10.3390/ma12101636 ◽

2019 ◽

Vol 12 (10) ◽

pp. 1636 ◽

Cited By ~ 2

Author(s):

Nurul Huda Abd Rahman ◽

Yoshihide Yamada ◽

Muhammad Shakir Amin Nordin

Keyword(s):

Human Body ◽

Free Space ◽

Dielectric Material ◽

Near Field ◽

The Body ◽

Antenna Structure ◽

Dielectric Characteristics ◽

Wearable Antennas ◽

Close Proximity ◽

Substantial Drop

Previous works have shown that wearable antennas can operate ideally in free space; however, degradation in performance, specifically in terms of frequency shifts and efficiency was observed when an antenna structure was in close proximity to the human body. These issues have been highlighted many times yet, systematic and numerical analysis on how the dielectric characteristics may affect the technical behavior of the antenna has not been discussed in detail. In this paper, a wearable antenna, developed from a new electro-textile material has been designed, and the step-by-step manufacturing process is presented. Through analysis of the frequency detuning effect, the on-body behavior of the antenna is evaluated by focusing on quantifying the changes of its input impedance and near-field distribution caused by the presence of lossy dielectric material. When the antenna is attached to the top of the body fat phantom, there is an increase of 17% in impedance, followed by 19% for the muscle phantom and 20% for the blood phantom. These phenomena correlate with the electric field intensities (V/m) observed closely at the antenna through various layers of mediums (z-axis) and along antenna edges (y-axis), which have shown significant increments of 29.7% in fat, 35.3% in muscle and 36.1% in blood as compared to free space. This scenario has consequently shown that a significant amount of energy is absorbed in the phantoms instead of radiated to the air which has caused a substantial drop in efficiency and gain. Performance verification is also demonstrated by using a fabricated human muscle phantom, with a dielectric constant of 48, loss tangent of 0.29 and conductivity of 1.22 S/m.

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Contribution of the slow motion mechanism to global motion revealed by an MAE technique

Scientific Reports ◽

10.1038/s41598-021-82900-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Satoshi Shioiri ◽

Kazumichi Matsumiya ◽

Chia-huei Tseng

Keyword(s):

Temporal Frequency ◽

Slow Motion ◽

Motion Aftereffect ◽

Random Motion ◽

Global Motion ◽

Global Integration ◽

Motion Mechanism ◽

Motion Patterns ◽

Spatial Frequencies ◽

Fast Motion

AbstractTwo different motion mechanisms have been identified with motion aftereffect (MAE). (1) A slow motion mechanism, accessed by a static MAE, is sensitive to high-spatial and low-temporal frequency; (2) a fast motion mechanism, accessed by a flicker MAE, is sensitive to low-spatial and high-temporal frequency. We examined their respective responses to global motion after adapting to a global motion pattern constructed of multiple compound Gabor patches arranged circularly. Each compound Gabor patch contained two gratings at different spatial frequencies (0.53 and 2.13 cpd) drifting in opposite directions. The participants reported the direction and duration of the MAE for a variety of global motion patterns. We discovered that static MAE durations depended on the global motion patterns, e.g., longer MAE duration to patches arranged to see rotation than to random motion (Exp 1), and increase with global motion strength (patch number in Exp 2). In contrast, flicker MAEs durations are similar across different patterns and adaptation strength. Further, the global integration occurred at the adaptation stage, rather than at the test stage (Exp 3). These results suggest that slow motion mechanism, assessed by static MAE, integrate motion signals over space while fast motion mechanisms do not, at least under the conditions used.

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Going Beyond 3-D Imaging: Automated 3-D Montaged image Analysis of Cytological Specimens

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100163873 ◽

1996 ◽

Vol 54 ◽

pp. 282-283

Author(s):

Badrinath Roysam ◽

Hakan Ancin ◽

Douglas E. Becker ◽

Robert W. Mackin ◽

Matthew M. Chestnut ◽

...

Keyword(s):

Image Analysis ◽

Structural Changes ◽

Sampling Methods ◽

Spatial Clustering ◽

Three Dimensional ◽

Field Of View ◽

Cell Counting ◽

Depth Of Field ◽

Tissue Cell ◽

Tissue Organization

This paper summarizes recent advances made by this group in the automated three-dimensional (3-D) image analysis of cytological specimens that are much thicker than the depth of field, and much wider than the field of view of the microscope. The imaging of thick samples is motivated by the need to sample large volumes of tissue rapidly, make more accurate measurements than possible with 2-D sampling, and also to perform analysis in a manner that preserves the relative locations and 3-D structures of the cells. The motivation to study specimens much wider than the field of view arises when measurements and insights at the tissue, rather than the cell level are needed.The term “analysis” indicates a activities ranging from cell counting, neuron tracing, cell morphometry, measurement of tracers, through characterization of large populations of cells with regard to higher-level tissue organization by detecting patterns such as 3-D spatial clustering, the presence of subpopulations, and their relationships to each other. Of even more interest are changes in these parameters as a function of development, and as a reaction to external stimuli. There is a widespread need to measure structural changes in tissue caused by toxins, physiologic states, biochemicals, aging, development, and electrochemical or physical stimuli. These agents could affect the number of cells per unit volume of tissue, cell volume and shape, and cause structural changes in individual cells, inter-connections, or subtle changes in higher-level tissue architecture. It is important to process large intact volumes of tissue to achieve adequate sampling and sensitivity to subtle changes. It is desirable to perform such studies rapidly, with utmost automation, and at minimal cost. Automated 3-D image analysis methods offer unique advantages and opportunities, without making simplifying assumptions of tissue uniformity, unlike random sampling methods such as stereology.12 Although stereological methods are known to be statistically unbiased, they may not be statistically efficient. Another disadvantage of sampling methods is the lack of full visual confirmation - an attractive feature of image analysis based methods.

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