Modeling Multi-Target Detection and Gravitation by Intelligent Self-Organizing Bioparticles

Iwasaki, Satoru; Yang, Jian; Abraham, Anthony O; Hagad, Juan Lorenzo; Obuchi, Takuya; Nakano, Tadashi

doi:10.1109/glocom.2016.7842000

Cited by 8 publications

(11 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…performs target tracking with the aim of targeted drug delivery . carries out in‐silico experiments by utilizing chemotactic bacteria and provide some information‐theoretic insights on the performance of their proposed target tracking Scheme . extends the previous works to track multiple targets .…”

Section: Introductionmentioning

confidence: 98%

Channel impulse response‐based source localization in a diffusion‐based molecular communication system

Baidoo-Williams

Rahman

Abbasi

2020

Internet Technology Letters

View full text Add to dashboard Cite

Molecular source localization finds its applications in future healthcare systems, including proactive diagnostics. This work localizes a molecular source in a diffusion based molecular communication (DbMC) system via a minimal set of passive anchor nodes and a fusion center. Two methods are presented which both utilize (the peak of) the channel impulse response measurements to uniquely localize the source, under the assumption that the molecular source of interest lies within the open convex‐hull of the sensor/anchor nodes. The first method is a one‐shot, triangulation‐based approach which estimates the unknown location of the molecular source using least‐squares method. The second method is an iterative approach, which utilizes the gradient‐descent control law to minimize a non‐convex cost function. The corresponding Cramer‐Rao bound (CRB) is also derived. Simulation results reveal that: (a) the gradient‐descent method outperforms the triangulation method (in terms of mean squared error performance) for a wide range of values of signal‐to‐noise ratio; (b) the gradient‐descent method converges to the true source location uniformly (in less than 100 iterations).

show abstract

Section: Introductionmentioning

confidence: 98%

Channel impulse response‐based source localization in a diffusion‐based molecular communication system

Baidoo-Williams

Rahman

Abbasi

2020

Internet Technology Letters

View full text Add to dashboard Cite

show abstract

“…on a swarm of bioparticles that interact by secreting signaling molecules called attractants and repellents to detect and localize to targets (e.g. cancer cells) that may exist in the environment [3,5,6,7,9].…”

Section: Introductionmentioning

confidence: 99%

“…The specific problem considered in this paper is referred to as the multi-target detection and gravitation problem [3] and illustrated in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

Performance Optimization of Self-organizing Bioparticles for Multi-target Detection and Gravitation Problems

Yang¹,

Iwasaki²,

Abraham³

et al. 2017

Proceedings of the 10th EAI International Conference on Bio-Inspired Information and Communications Technologies (Formerly BION

Self Cite

View full text Add to dashboard Cite

This paper investigates the performance of self-organizing bioparticles for multi-target detection and gravitation problems. This paper describes three approaches to multi-target detection and gravitation problems in which bioparticles coordinate their behavior by secreting (1) attractants, (2) repellents or (3) both attractants and repellents. We first define the behavior of bioparticles in these approaches by using differential equations. We then show numerical results to understand the basic behavior of bioparticles in each approach and to demonstrate optimized performance for multi-target detection and gravitation problems. CCS Concepts •Applied computing → Health care information systems; •Hardware → Biology-related information processing;

show abstract

“…For the model proposed by Okaie et al, Iwasaki made assumptions; (i) attractants and repellents do not diffuse, (ii) attractants and repellents quickly reach into stationary state, then introduced the following model equation with respect to concentration of agents [10]:…”

Section: Target-detection Modelmentioning

confidence: 99%

“…Iwasaki proposed a simplified model based on above model and has proved that concentrations of agents converge to stationary concentration which is characterized by a "target" concentration [10]. Furthermore, Iwasaki proved a "target" concentration and stationary concentration of agents have the same locations of local minima and local maxima.…”

Section: Introductionmentioning

confidence: 99%

Estimation distribution algorithm based on a molecular target detector model

Iwasaki

Hatanaka

2017

Stochastic Systems Theory and its Applications (SSS)

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a kind of evolutionary computation procedure for multimodal function optimization. The proposed approach is based on a partial differential equation whose solutions are analytically ensured to converge a stationary distribution depending on a given target distribution. We construct bootstrap procedure of a sampling and a target distribution estimation. Then, by numerical study, we show that our proposed algorithm has similar properties to estimation of distribution algorithms.

show abstract

Modeling Multi-Target Detection and Gravitation by Intelligent Self-Organizing Bioparticles

Cited by 8 publications

References 19 publications

Channel impulse response‐based source localization in a diffusion‐based molecular communication system

Channel impulse response‐based source localization in a diffusion‐based molecular communication system

Performance Optimization of Self-organizing Bioparticles for Multi-target Detection and Gravitation Problems

Estimation distribution algorithm based on a molecular target detector model

Contact Info

Product

Resources

About