scholarly journals An Adaptive Epidemiology-Based Approach to Swarm Foraging with Dynamic Deadlines

2021 ◽  
Vol 11 (10) ◽  
pp. 4627
Author(s):  
Hebah ElGibreen
Keyword(s):  
Research Problem ◽  
Efficient Solutions ◽  
Epidemiological Modeling ◽  
Dynamic Task ◽  
Open Research ◽  
Novel Approach ◽  
Dynamic Task Allocation ◽  
Recent Developments ◽  
Limited Sensing ◽  
Real World Problems

Swarm robotics is an emerging field that can offer efficient solutions to real-world problems with minimal cost. Despite recent developments in the field, however, it is still not sufficiently mature, and challenges clearly remain. The dynamic deadline problem is neglected in the literature, and thus, time-sensitive foraging tasks are still an open research problem. This paper proposes a novel approach—ED_Foraging—that allows simple robots with limited sensing and communication abilities to perform complex foraging tasks that are dynamic and time constrained. A new mathematical model is developed in this paper to utilize epidemiological modeling and predict the dynamics of resource deadlines. Moreover, an improved dynamic task allocation (DTA) method is proposed to assign robots to the most critical region, where a deadline is represented by a state and time. The main goal is to reduce the number of expired resources and collect them as quickly as possible by giving priority to those that are more likely to expire if not collected. The deadlines are unknown and change dynamically. Thus, the robots continuously collect local information throughout their journeys and allocate themselves dynamically to the predicted hotspots. In the experiments, the proposed approach is adapted to four DTA methods and tested with different setups using simulated foot-bot robots. The flexibility, scalability, and robustness of this approach are measured in terms of the foraging and expiration rates. The empirical results support the hypothesis that epidemiological modeling can be utilized to handle foraging tasks that are constrained by dynamic deadlines. It is also confirmed that the proposed DTA method improves the results, which were found to be flexible, scalable, and robust to changes in the number of robots and the map size.

scholarly journals Auction-Based Consensus of Autonomous Vehicles for Multi-Target Dynamic Task Allocation and Path Planning in an Unknown Obstacle Environment

2021 ◽  
Vol 11 (11) ◽  
pp. 5057
Author(s):  
Wan-Yu Yu ◽  
Xiao-Qiang Huang ◽  
Hung-Yi Luo ◽  
Von-Wun Soo ◽  
Yung-Lung Lee
Keyword(s):  
Path Planning ◽  
Task Allocation ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Dynamic Task ◽  
The Core ◽  
Dynamic Task Allocation ◽  
Vehicle Technology ◽  
Future Work ◽  
Complicated Task

The autonomous vehicle technology has recently been developed rapidly in a wide variety of applications. However, coordinating a team of autonomous vehicles to complete missions in an unknown and changing environment has been a challenging and complicated task. We modify the consensus-based auction algorithm (CBAA) so that it can dynamically reallocate tasks among autonomous vehicles that can flexibly find a path to reach multiple dynamic targets while avoiding unexpected obstacles and staying close as a group as possible simultaneously. We propose the core algorithms and simulate with many scenarios empirically to illustrate how the proposed framework works. Specifically, we show that how autonomous vehicles could reallocate the tasks among each other in finding dynamically changing paths while certain targets may appear and disappear during the movement mission. We also discuss some challenging problems as a future work.

scholarly journals Use of Continuous Positive Airway Pressure (CPAP) to Limit Diaphragm Motion—A Novel Approach for Definitive Radiation Therapy for Inoperable Pleural Mesothelioma: A Pilot Study

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 711
Author(s):  
Assaf Moore ◽  
Marc J. Kindler ◽  
Aaron Max Allen
Keyword(s):  
Pilot Study ◽  
Static Field ◽  
Normal Lung ◽  
Pleural Mesothelioma ◽  
Lung Dose ◽  
Lung Inflation ◽  
Novel Approach ◽  
Recent Developments ◽  
Ct Simulation ◽  
Dose Constraints

Malignant pleural mesothelioma (MPM) is a deadly disease and radiotherapy (RT) plays an important role in its management. Recent developments in technique have made it is possible to deliver RT to MPM in the intact lung. However, it is imperative to reduce normal lung doses. We present a pilot study examining the use of CPAP and VMAT radiotherapy to reduce toxicity when treating MPM, involving three consecutive patients with MPM, not amenable to surgery, who were treated according to Helsinki committee approval. Patients were simulated using four-dimentional CT simulation with the assistance of CPAP lung inflation, then were treated using both IMRT and VMAT techniques. Radiation lung dose was optimized based on accepted lung dose constraints. Patients were followed for toxicity as well as local control and survival. Results: Three patients were treated with CPAP-based IMRT treatment. These patients tolerated the treatment and DVH constraints were able to be met. The comparison plans among the four VMAT arcs and the IMRT static field treatment were able to accomplish the treatment planning objectives without significant advantages with either technique. The treatment combined with CPAP reduced the normal lung dose in MPM patients with intact lungs. This technique is worthy of further investigation.

An Innovation System for Building Manufacturing

2012 ◽  
Author(s):  
Flávio Craveiro ◽  
João Meneses de Matos ◽  
Helena Bártolo ◽  
Paulo Bártolo
Keyword(s):  
New Technologies ◽  
Innovation System ◽  
Efficient Solutions ◽  
Urban Environments ◽  
Functionally Graded ◽  
Functional Requirements ◽  
Geometric Information ◽  
Material Deposition ◽  
Novel Approach ◽  
Graded Material

Traditionally the construction sector is very conservative, risk averse and reluctant to adopt new technologies and ideas. The construction industry faces great challenges to develop more innovative and efficient solutions. In recent years, significant advances in technology and more sustainable urban environments has been creating numerous opportunities for innovation in automation. This paper proposes a new system based on extrusion-based technologies aiming at solving some limitations of current technologies to allow a more efficient building construction with organic forms and geometries, based on sustainable eco principles. This novel approach is described through a control deposition software. Current modeling techniques focus only on capturing the geometric information and cannot satisfy the requirements from modeling the components made of multi-heterogeneous materials. There is a great deal of interest in tailoring structures so the functional requirements can vary with location. The proposed functionally graded material deposition (FGM) system will allow a smooth variation of material properties to build up more efficient buildings regarding thermal, acoustic and structural conditions.

scholarly journals A multi-responsibility–oriented coalition formation framework for dynamic task allocation in mobile–distributed multi-agent systems

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881303 ◽  
Author(s):  
Bing Xie ◽  
Xueqiang Gu ◽  
Jing Chen ◽  
LinCheng Shen
Keyword(s):  
Coalition Formation ◽  
Task Allocation ◽  
Game Model ◽  
Multi Agent Systems ◽  
Coalition Game ◽  
Task Execution ◽  
Agent Systems ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Multi Agent

In this article, we study a problem of dynamic task allocation with multiple agent responsibilities in distributed multi-agent systems. Agents in the research have two responsibilities, communication and task execution. Movements in agent task execution bring changes to the system network structure, which will affect the communication. Thus, agents need to be autonomous on communication network reconstruction for good performance on task execution. First, we analyze the relationships between the two responsibilities of agents. Then, we design a multi-responsibility–oriented coalition formation framework for dynamic task allocation with two parts, namely, task execution and self-adaptation communication. For the former part, we integrate our formerly proposed algorithm in the framework for task execution coalition formation. For the latter part, we develop a constrained Bayesian overlapping coalition game model to formulate the communication network. A task-allocation efficiency–oriented communication coalition utility function is defined to optimize a coalition structure for the constrained Bayesian overlapping coalition game model. Considering the geographical location dependence between the two responsibilities, we define constrained agent strategies to map agent strategies to potential location choices. Based on the abovementioned design, we propose a distributed location pruning self-adaptive algorithm for the constrained Bayesian overlapping coalition formation. Finally, we test the performance of our framework, multi-responsibility–oriented coalition formation framework, with simulation experiments. Experimental results demonstrate that the multi-responsibility oriented coalition formation framework performs better than the other two distributed algorithms on task completion rate (by over 9.4% and over 65% on average, respectively).

scholarly journals An under sampled k-means approach for handlingimbalanced data using diversified distribution

2018 ◽  
Vol 7 (1.8) ◽  
pp. 113 ◽  
Author(s):  
G Shobana ◽  
Bhanu Prakash Battula
Keyword(s):  
Research Issue ◽  
Minority Class ◽  
Effective Utilization ◽  
Specific Strategy ◽  
Open Research ◽  
Novel Approach ◽  
Under Sampling ◽  
F Measure

Some true applications uncover troubles in taking in classifiers from imbalanced information. Albeit a few techniques for enhancing classifiers have been presented, the distinguishing proof of conditions for the effective utilization of the specific strategy is as yet an open research issue. It is likewise worth to think about the idea of imbalanced information, qualities of the minority class dissemination and their impact on arrangement execution. In any case, current investigations on imbalanced information trouble factors have been predominantly finished with manufactured datasets and their decisions are not effortlessly material to this present reality issues, likewise on the grounds that the techniques for their distinguishing proof are not adequately created. In this paper, we recommended a novel approach Under Sampling Utilizing Diversified Distribution (USDD) for explaining the issues of class lopsidedness in genuine datasets by thinking about the systems of recognizable pieces of proof and expulsion of marginal, uncommon and anomalies sub groups utilizing k-implies. USDD utilizes exceptional procedure for recognizable proof of these kinds of cases, which depends on breaking down a class dissemination in a nearby neighborhood of the considered case utilizing k-closest approach. The exploratory outcomes recommend that the proposed USDD approach performs superior to the looked at approach as far as AUC, accuracy, review and f-measure.

scholarly journals Analysis of Dynamic Task Allocation in Multi-Robot Systems

2006 ◽  
Author(s):  
Kristina Lerman ◽  
Chris Jones ◽  
Aram Galstyan ◽  
Maja J. Mataric
Keyword(s):  
Task Allocation ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Robot Systems ◽  
Multi Robot
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