An adaptive grid algorithm for 3-D GIS landform optimization based on improved ant algorithm

NASA Astrophysics Data System (ADS)

Wu, Chenhan; Meng, Lingkui; Deng, Shijun

2005-07-01

The key technique of 3-D GIS is to realize quick and high-quality 3-D visualization, in which 3-D roaming system based on landform plays an important role. However how to increase efficiency of 3-D roaming engine and process a large amount of landform data is a key problem in 3-D landform roaming system and improper process of the problem would result in tremendous consumption of system resources. Therefore it has become the key of 3-D roaming system design that how to realize high-speed process of distributed data for landform DEM (Digital Elevation Model) and high-speed distributed modulation of various 3-D landform data resources. In the paper we improved the basic ant algorithm and designed the modulation strategy of 3-D GIS landform resources based on the improved ant algorithm. By initially hypothetic road weights σi , the change of the information factors in the original algorithm would transform from ˜τj to ∆τj+σi and the weights was decided by 3-D computative capacity of various nodes in network environment. So during the course of initial phase of task assignment, increasing the resource information factors of high task-accomplishing rate and decreasing ones of low accomplishing rate would make load accomplishing rate approach the same value as quickly as possible, then in the later process of task assignment, the load balanced ability of the system was further improved. Experimental results show by improving ant algorithm, our system not only decreases many disadvantage of the traditional ant algorithm, but also like ants looking for food effectively distributes the complicated landform algorithm to many computers to process cooperatively and gains a satisfying search result.

An improved self-adaptive ant colony algorithm based on genetic strategy for the traveling salesman problem

NASA Astrophysics Data System (ADS)

Wang, Pan; Zhang, Yi; Yan, Dong

2018-05-01

Ant Colony Algorithm (ACA) is a powerful and effective algorithm for solving the combination optimization problem. Moreover, it was successfully used in traveling salesman problem (TSP). But it is easy to prematurely converge to the non-global optimal solution and the calculation time is too long. To overcome those shortcomings, a new method is presented-An improved self-adaptive Ant Colony Algorithm based on genetic strategy. The proposed method adopts adaptive strategy to adjust the parameters dynamically. And new crossover operation and inversion operation in genetic strategy was used in this method. We also make an experiment using the well-known data in TSPLIB. The experiment results show that the performance of the proposed method is better than the basic Ant Colony Algorithm and some improved ACA in both the result and the convergence time. The numerical results obtained also show that the proposed optimization method can achieve results close to the theoretical best known solutions at present.

Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

PubMed

Li, Yang; Li, Guoqing; Wang, Zhenhao

2015-01-01

In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

Ant Lion Optimization algorithm for kidney exchanges.

PubMed

Hamouda, Eslam; El-Metwally, Sara; Tarek, Mayada

2018-01-01

The kidney exchange programs bring new insights in the field of organ transplantation. They make the previously not allowed surgery of incompatible patient-donor pairs easier to be performed on a large scale. Mathematically, the kidney exchange is an optimization problem for the number of possible exchanges among the incompatible pairs in a given pool. Also, the optimization modeling should consider the expected quality-adjusted life of transplant candidates and the shortage of computational and operational hospital resources. In this article, we introduce a bio-inspired stochastic-based Ant Lion Optimization, ALO, algorithm to the kidney exchange space to maximize the number of feasible cycles and chains among the pool pairs. Ant Lion Optimizer-based program achieves comparable kidney exchange results to the deterministic-based approaches like integer programming. Also, ALO outperforms other stochastic-based methods such as Genetic Algorithm in terms of the efficient usage of computational resources and the quantity of resulting exchanges. Ant Lion Optimization algorithm can be adopted easily for on-line exchanges and the integration of weights for hard-to-match patients, which will improve the future decisions of kidney exchange programs. A reference implementation for ALO algorithm for kidney exchanges is written in MATLAB and is GPL licensed. It is available as free open-source software from: https://github.com/SaraEl-Metwally/ALO_algorithm_for_Kidney_Exchanges.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Ling, H.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Improved understanding of the searching behavior of ant colony optimization algorithms applied to the water distribution design problem

NASA Astrophysics Data System (ADS)

Zecchin, A. C.; Simpson, A. R.; Maier, H. R.; Marchi, A.; Nixon, J. B.

2012-09-01

Evolutionary algorithms (EAs) have been applied successfully to many water resource problems, such as system design, management decision formulation, and model calibration. The performance of an EA with respect to a particular problem type is dependent on how effectively its internal operators balance the exploitation/exploration trade-off to iteratively find solutions of an increasing quality. For a given problem, different algorithms are observed to produce a variety of different final performances, but there have been surprisingly few investigations into characterizing how the different internal mechanisms alter the algorithm's searching behavior, in both the objective and decision space, to arrive at this final performance. This paper presents metrics for analyzing the searching behavior of ant colony optimization algorithms, a particular type of EA, for the optimal water distribution system design problem, which is a classical NP-hard problem in civil engineering. Using the proposed metrics, behavior is characterized in terms of three different attributes: (1) the effectiveness of the search in improving its solution quality and entering into optimal or near-optimal regions of the search space, (2) the extent to which the algorithm explores as it converges to solutions, and (3) the searching behavior with respect to the feasible and infeasible regions. A range of case studies is considered, where a number of ant colony optimization variants are applied to a selection of water distribution system optimization problems. The results demonstrate the utility of the proposed metrics to give greater insight into how the internal operators affect each algorithm's searching behavior.

Improved Ant Algorithms for Software Testing Cases Generation

PubMed Central

Yang, Shunkun; Xu, Jiaqi

2014-01-01

Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to porduce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations. PMID:24883391

Escalated convergent artificial bee colony

NASA Astrophysics Data System (ADS)

Jadon, Shimpi Singh; Bansal, Jagdish Chand; Tiwari, Ritu

2016-03-01

Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such as particle swarm optimisation, firefly algorithm and ant colony optimisation. The solution search equation of ABC is influenced by a random quantity which helps its search process in exploration at the cost of exploitation. In order to find a fast convergent behaviour of ABC while exploitation capability is maintained, in this paper basic ABC is modified in two ways. First, to improve exploitation capability, two local search strategies, namely classical unidimensional local search and levy flight random walk-based local search are incorporated with ABC. Furthermore, a new solution search strategy, namely stochastic diffusion scout search is proposed and incorporated into the scout bee phase to provide more chance to abandon solution to improve itself. Efficiency of the proposed algorithm is tested on 20 benchmark test functions of different complexities and characteristics. Results are very promising and they prove it to be a competitive algorithm in the field of swarm intelligence-based algorithms.

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

NASA Technical Reports Server (NTRS)

Alena, Richard I.; Lee, Charles

2004-01-01

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Discrete bacteria foraging optimization algorithm for graph based problems - a transition from continuous to discrete

NASA Astrophysics Data System (ADS)

Sur, Chiranjib; Shukla, Anupam

2018-03-01

Bacteria Foraging Optimisation Algorithm is a collective behaviour-based meta-heuristics searching depending on the social influence of the bacteria co-agents in the search space of the problem. The algorithm faces tremendous hindrance in terms of its application for discrete problems and graph-based problems due to biased mathematical modelling and dynamic structure of the algorithm. This had been the key factor to revive and introduce the discrete form called Discrete Bacteria Foraging Optimisation (DBFO) Algorithm for discrete problems which exceeds the number of continuous domain problems represented by mathematical and numerical equations in real life. In this work, we have mainly simulated a graph-based road multi-objective optimisation problem and have discussed the prospect of its utilisation in other similar optimisation problems and graph-based problems. The various solution representations that can be handled by this DBFO has also been discussed. The implications and dynamics of the various parameters used in the DBFO are illustrated from the point view of the problems and has been a combination of both exploration and exploitation. The result of DBFO has been compared with Ant Colony Optimisation and Intelligent Water Drops Algorithms. Important features of DBFO are that the bacteria agents do not depend on the local heuristic information but estimates new exploration schemes depending upon the previous experience and covered path analysis. This makes the algorithm better in combination generation for graph-based problems and combination generation for NP hard problems.

Adapting an Ant Colony Metaphor for Multi-Robot Chemical Plume Tracing

PubMed Central

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments. PMID:22666056

Adapting an ant colony metaphor for multi-robot chemical plume tracing.

PubMed

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments.

A pheromone-rate-based analysis on the convergence time of ACO algorithm.

PubMed

Huang, Han; Wu, Chun-Guo; Hao, Zhi-Feng

2009-08-01

Ant colony optimization (ACO) has widely been applied to solve combinatorial optimization problems in recent years. There are few studies, however, on its convergence time, which reflects how many iteration times ACO algorithms spend in converging to the optimal solution. Based on the absorbing Markov chain model, we analyze the ACO convergence time in this paper. First, we present a general result for the estimation of convergence time to reveal the relationship between convergence time and pheromone rate. This general result is then extended to a two-step analysis of the convergence time, which includes the following: 1) the iteration time that the pheromone rate spends on reaching the objective value and 2) the convergence time that is calculated with the objective pheromone rate in expectation. Furthermore, four brief ACO algorithms are investigated by using the proposed theoretical results as case studies. Finally, the conclusions of the case studies that the pheromone rate and its deviation determine the expected convergence time are numerically verified with the experiment results of four one-ant ACO algorithms and four ten-ant ACO algorithms.

Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

NASA Astrophysics Data System (ADS)

Hou, Huirang; Zheng, Dandan; Nie, Laixiao

2015-04-01

For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until -10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method.

Army ants algorithm for rare event sampling of delocalized nonadiabatic transitions by trajectory surface hopping and the estimation of sampling errors by the bootstrap method.

PubMed

Nangia, Shikha; Jasper, Ahren W; Miller, Thomas F; Truhlar, Donald G

2004-02-22

The most widely used algorithm for Monte Carlo sampling of electronic transitions in trajectory surface hopping (TSH) calculations is the so-called anteater algorithm, which is inefficient for sampling low-probability nonadiabatic events. We present a new sampling scheme (called the army ants algorithm) for carrying out TSH calculations that is applicable to systems with any strength of coupling. The army ants algorithm is a form of rare event sampling whose efficiency is controlled by an input parameter. By choosing a suitable value of the input parameter the army ants algorithm can be reduced to the anteater algorithm (which is efficient for strongly coupled cases), and by optimizing the parameter the army ants algorithm may be efficiently applied to systems with low-probability events. To demonstrate the efficiency of the army ants algorithm, we performed atom-diatom scattering calculations on a model system involving weakly coupled electronic states. Fully converged quantum mechanical calculations were performed, and the probabilities for nonadiabatic reaction and nonreactive deexcitation (quenching) were found to be on the order of 10(-8). For such low-probability events the anteater sampling scheme requires a large number of trajectories ( approximately 10(10)) to obtain good statistics and converged semiclassical results. In contrast by using the new army ants algorithm converged results were obtained by running 10(5) trajectories. Furthermore, the results were found to be in excellent agreement with the quantum mechanical results. Sampling errors were estimated using the bootstrap method, which is validated for use with the army ants algorithm. (c) 2004 American Institute of Physics.

Ant algorithms for discrete optimization.

PubMed

Dorigo, M; Di Caro, G; Gambardella, L M

1999-01-01

This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a discussion of related work and of some of the most important aspects of the ACO metaheuristic.

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP.

PubMed

Mohsen, Abdulqader M

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality.

A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system

NASA Astrophysics Data System (ADS)

Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun

2014-11-01

In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.

Production scheduling with ant colony optimization

NASA Astrophysics Data System (ADS)

Chernigovskiy, A. S.; Kapulin, D. V.; Noskova, E. E.; Yamskikh, T. N.; Tsarev, R. Yu

2017-10-01

The optimum solution of the production scheduling problem for manufacturing processes at an enterprise is crucial as it allows one to obtain the required amount of production within a specified time frame. Optimum production schedule can be found using a variety of optimization algorithms or scheduling algorithms. Ant colony optimization is one of well-known techniques to solve the global multi-objective optimization problem. In the article, the authors present a solution of the production scheduling problem by means of an ant colony optimization algorithm. A case study of the algorithm efficiency estimated against some others production scheduling algorithms is presented. Advantages of the ant colony optimization algorithm and its beneficial effect on the manufacturing process are provided.

Model Specification Searches Using Ant Colony Optimization Algorithms

ERIC Educational Resources Information Center

Marcoulides, George A.; Drezner, Zvi

2003-01-01

Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.

Ancient village fire escape path planning based on improved ant colony algorithm

NASA Astrophysics Data System (ADS)

Xia, Wei; Cao, Kang; Hu, QianChuan

2017-06-01

The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.

Dynamic routing and spectrum assignment based on multilayer virtual topology and ant colony optimization in elastic software-defined optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun

2017-07-01

Elastic software-defined optical networks greatly improve the flexibility of the optical switching network while it has brought challenges to the routing and spectrum assignment (RSA). A multilayer virtual topology model is proposed to solve RSA problems. Two RSA algorithms based on the virtual topology are proposed, which are the ant colony optimization (ACO) algorithm of minimum consecutiveness loss and the ACO algorithm of maximum spectrum consecutiveness. Due to the computing power of the control layer in the software-defined network, the routing algorithm avoids the frequent link-state information between routers. Based on the effect of the spectrum consecutiveness loss on the pheromone in the ACO, the path and spectrum of the minimal impact on the network are selected for the service request. The proposed algorithms have been compared with other algorithms. The results show that the proposed algorithms can reduce the blocking rate by at least 5% and perform better in spectrum efficiency. Moreover, the proposed algorithms can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness.

GOClonto: an ontological clustering approach for conceptualizing PubMed abstracts.

PubMed

Zheng, Hai-Tao; Borchert, Charles; Kim, Hong-Gee

2010-02-01

Concurrent with progress in biomedical sciences, an overwhelming of textual knowledge is accumulating in the biomedical literature. PubMed is the most comprehensive database collecting and managing biomedical literature. To help researchers easily understand collections of PubMed abstracts, numerous clustering methods have been proposed to group similar abstracts based on their shared features. However, most of these methods do not explore the semantic relationships among groupings of documents, which could help better illuminate the groupings of PubMed abstracts. To address this issue, we proposed an ontological clustering method called GOClonto for conceptualizing PubMed abstracts. GOClonto uses latent semantic analysis (LSA) and gene ontology (GO) to identify key gene-related concepts and their relationships as well as allocate PubMed abstracts based on these key gene-related concepts. Based on two PubMed abstract collections, the experimental results show that GOClonto is able to identify key gene-related concepts and outperforms the STC (suffix tree clustering) algorithm, the Lingo algorithm, the Fuzzy Ants algorithm, and the clustering based TRS (tolerance rough set) algorithm. Moreover, the two ontologies generated by GOClonto show significant informative conceptual structures.

Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

NASA Astrophysics Data System (ADS)

Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

2018-03-01

Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP

PubMed Central

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality. PMID:27999590

Selecting Cases for Intensive Analysis: A Diversity of Goals and Methods

ERIC Educational Resources Information Center

Gerring, John; Cojocaru, Lee

2016-01-01

This study revisits the task of case selection in case study research, proposing a new typology of strategies that is explicit, disaggregated, and relatively comprehensive. A secondary goal is to explore the prospects for case selection by "algorithm," aka "ex ante," "automatic," "quantitative,"…

Study on bi-directional pedestrian movement using ant algorithms

NASA Astrophysics Data System (ADS)

Sibel, Gokce; Ozhan, Kayacan

2016-01-01

A cellular automata model is proposed to simulate bi-directional pedestrian flow. Pedestrian movement is investigated by using ant algorithms. Ants communicate with each other by dropping a chemical, called a pheromone, on the substrate while crawling forward. Similarly, it is considered that oppositely moving pedestrians drop ‘visual pheromones’ on their way and the visual pheromones might cause attractive or repulsive interactions. This pheromenon is introduced into modelling the pedestrians’ walking preference. In this way, the decision-making process of pedestrians will be based on ‘the instinct of following’. At some densities, the relationships of velocity-density and flux-density are analyzed for different evaporation rates of visual pheromones. Lane formation and phase transition are observed for certain evaporation rates of visual pheromones.

Solving NP-Hard Problems with Physarum-Based Ant Colony System.

PubMed

Liu, Yuxin; Gao, Chao; Zhang, Zili; Lu, Yuxiao; Chen, Shi; Liang, Mingxin; Tao, Li

2017-01-01

NP-hard problems exist in many real world applications. Ant colony optimization (ACO) algorithms can provide approximate solutions for those NP-hard problems, but the performance of ACO algorithms is significantly reduced due to premature convergence and weak robustness, etc. With these observations in mind, this paper proposes a Physarum-based pheromone matrix optimization strategy in ant colony system (ACS) for solving NP-hard problems such as traveling salesman problem (TSP) and 0/1 knapsack problem (0/1 KP). In the Physarum-inspired mathematical model, one of the unique characteristics is that critical tubes can be reserved in the process of network evolution. The optimized updating strategy employs the unique feature and accelerates the positive feedback process in ACS, which contributes to the quick convergence of the optimal solution. Some experiments were conducted using both benchmark and real datasets. The experimental results show that the optimized ACS outperforms other meta-heuristic algorithms in accuracy and robustness for solving TSPs. Meanwhile, the convergence rate and robustness for solving 0/1 KPs are better than those of classical ACS.

A seismic fault recognition method based on ant colony optimization

NASA Astrophysics Data System (ADS)

Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong

2018-05-01

Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.

A Global Approach to the Optimal Trajectory Based on an Improved Ant Colony Algorithm for Cold Spray

NASA Astrophysics Data System (ADS)

Cai, Zhenhua; Chen, Tingyang; Zeng, Chunnian; Guo, Xueping; Lian, Huijuan; Zheng, You; Wei, Xiaoxu

2016-12-01

This paper is concerned with finding a global approach to obtain the shortest complete coverage trajectory on complex surfaces for cold spray applications. A slicing algorithm is employed to decompose the free-form complex surface into several small pieces of simple topological type. The problem of finding the optimal arrangement of the pieces is translated into a generalized traveling salesman problem (GTSP). Owing to its high searching capability and convergence performance, an improved ant colony algorithm is then used to solve the GTSP. Through off-line simulation, a robot trajectory is generated based on the optimized result. The approach is applied to coat real components with a complex surface by using the cold spray system with copper as the spraying material.

Ant colony algorithm for clustering in portfolio optimization

NASA Astrophysics Data System (ADS)

Subekti, R.; Sari, E. R.; Kusumawati, R.

2018-03-01

This research aims to describe portfolio optimization using clustering methods with ant colony approach. Two stock portfolios of LQ45 Indonesia is proposed based on the cluster results obtained from ant colony optimization (ACO). The first portfolio consists of assets with ant colony displacement opportunities beyond the defined probability limits of the researcher, where the weight of each asset is determined by mean-variance method. The second portfolio consists of two assets with the assumption that each asset is a cluster formed from ACO. The first portfolio has a better performance compared to the second portfolio seen from the Sharpe index.

Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

PubMed Central

Liu, Xiaoli; Chen, Hong-Xin; Kim, Jinxie

2014-01-01

A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline. PMID:25025089

Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

NASA Astrophysics Data System (ADS)

Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

2018-04-01

Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Genrang; Lin, ZhengChun

The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

Optimization research of railway passenger transfer scheme based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Ni, Xiang

2018-05-01

The optimization research of railway passenger transfer scheme can provide strong support for railway passenger transport system, and its essence is path search. This paper realized the calculation of passenger transfer scheme for high speed railway when giving the time and stations of departure and arrival. The specific method that used were generating a passenger transfer service network of high-speed railway, establishing optimization model and searching by Ant Colony Algorithm. Finally, making analysis on the scheme from LanZhouxi to BeiJingXi which were based on high-speed railway network of China in 2017. The results showed that the transfer network and model had relatively high practical value and operation efficiency.

Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

NASA Astrophysics Data System (ADS)

Qiu, J. P.; Niu, D. X.

Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

Finite grade pheromone ant colony optimization for image segmentation

NASA Astrophysics Data System (ADS)

Yuanjing, F.; Li, Y.; Liangjun, K.

2008-06-01

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

Joint optimization of maintenance, buffers and machines in manufacturing lines

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Nourelfath, Mustapha

2018-01-01

This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.

Honey Bees Inspired Optimization Method: The Bees Algorithm.

PubMed

Yuce, Baris; Packianather, Michael S; Mastrocinque, Ernesto; Pham, Duc Truong; Lambiase, Alfredo

2013-11-06

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

Ante mortem identification of BSE from serum using infrared spectroscopy

NASA Astrophysics Data System (ADS)

Schmitt, Jürgen; Lasch, Peter; Beekes, Michael; Udelhoven, Thomas; Eiden, Michael; Fabian, Heinz; Petrich, Wolfgang H.; Naumann, Dieter

2004-07-01

In our former studies a diagnostic approach for the detection of transmissible spongiform encephalopaties (TSE) based on FT-IR spectroscopy in combination with artificial neural networks was described, based on a controlled animal study with terminally ill Syrian hamsters and control animals. As a consequence of the bovine spongiform encephalopathy (BSE) crisis in Europe, the development of a disgnostic ante mortem test for cattle has become a matter of great scientific importance and public interest. Since 1986 more than 180,000 clinical cases of BSE have been observed in the UK alone. Most of these cases were confirmed by post mortem examination of brain tissue. However, BSE-related risk assessment and risk-management would greatly benefit from ante mortem testing on living animals. For example, a serum-based test could allow for screening of the cattle population, thus, even a BSE eradication program would be conceivable. Here we report on a novel method for ante mortem BSE testing, which combines infrared spectroscopy of serum samples with multivariate pattern recognition analysis. A classification algorithm was trained using infrared spectra of sera from more than 800 animals from a field study (including BSE positive, healthy controls and animals suffering from viral or bacterial infections). In two validation studies sensitivities of 85% and 87% and specificities of 84% and 91% were achieved, respectively. The combination of classification algorithms increased sensitivity and specificity to 96% and 92%, respectively.

A novel global Harmony Search method based on Ant Colony Optimisation algorithm

NASA Astrophysics Data System (ADS)

Fouad, Allouani; Boukhetala, Djamel; Boudjema, Fares; Zenger, Kai; Gao, Xiao-Zhi

2016-03-01

The Global-best Harmony Search (GHS) is a stochastic optimisation algorithm recently developed, which hybridises the Harmony Search (HS) method with the concept of swarm intelligence in the particle swarm optimisation (PSO) to enhance its performance. In this article, a new optimisation algorithm called GHSACO is developed by incorporating the GHS with the Ant Colony Optimisation algorithm (ACO). Our method introduces a novel improvisation process, which is different from that of the GHS in the following aspects. (i) A modified harmony memory (HM) representation and conception. (ii) The use of a global random switching mechanism to monitor the choice between the ACO and GHS. (iii) An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The proposed GHSACO algorithm has been applied to various benchmark functions and constrained optimisation problems. Simulation results demonstrate that it can find significantly better solutions when compared with the original HS and some of its variants.

Application of cellular automatons and ant algorithms in avionics

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Selvesiuk, N. I.; Platoshin, G. A.; Semenova, E. V.

2018-03-01

The paper considers two algorithms for searching quasi-optimal solutions of discrete optimization problems with regard to the tasks of avionics placing. The first one solves the problem of optimal placement of devices by installation locations, the second one is for the problem of finding the shortest route between devices. Solutions are constructed using a cellular automaton and the ant colony algorithm.

A distributed algorithm to maintain and repair the trail networks of arboreal ants.

PubMed

Chandrasekhar, Arjun; Gordon, Deborah M; Navlakha, Saket

2018-06-18

We study how the arboreal turtle ant (Cephalotes goniodontus) solves a fundamental computing problem: maintaining a trail network and finding alternative paths to route around broken links in the network. Turtle ants form a routing backbone of foraging trails linking several nests and temporary food sources. This species travels only in the trees, so their foraging trails are constrained to lie on a natural graph formed by overlapping branches and vines in the tangled canopy. Links between branches, however, can be ephemeral, easily destroyed by wind, rain, or animal movements. Here we report a biologically feasible distributed algorithm, parameterized using field data, that can plausibly describe how turtle ants maintain the routing backbone and find alternative paths to circumvent broken links in the backbone. We validate the ability of this probabilistic algorithm to circumvent simulated breaks in synthetic and real-world networks, and we derive an analytic explanation for why certain features are crucial to improve the algorithm's success. Our proposed algorithm uses fewer computational resources than common distributed graph search algorithms, and thus may be useful in other domains, such as for swarm computing or for coordinating molecular robots.

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

Ant-cuckoo colony optimization for feature selection in digital mammogram.

PubMed

Jona, J B; Nagaveni, N

2014-01-15

Digital mammogram is the only effective screening method to detect the breast cancer. Gray Level Co-occurrence Matrix (GLCM) textural features are extracted from the mammogram. All the features are not essential to detect the mammogram. Therefore identifying the relevant feature is the aim of this work. Feature selection improves the classification rate and accuracy of any classifier. In this study, a new hybrid metaheuristic named Ant-Cuckoo Colony Optimization a hybrid of Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for feature selection in Digital Mammogram. ACO is a good metaheuristic optimization technique but the drawback of this algorithm is that the ant will walk through the path where the pheromone density is high which makes the whole process slow hence CS is employed to carry out the local search of ACO. Support Vector Machine (SVM) classifier with Radial Basis Kernal Function (RBF) is done along with the ACO to classify the normal mammogram from the abnormal mammogram. Experiments are conducted in miniMIAS database. The performance of the new hybrid algorithm is compared with the ACO and PSO algorithm. The results show that the hybrid Ant-Cuckoo Colony Optimization algorithm is more accurate than the other techniques.

Attractors in Sequence Space: Agent-Based Exploration of MHC I Binding Peptides.

PubMed

Jäger, Natalie; Wisniewska, Joanna M; Hiss, Jan A; Freier, Anja; Losch, Florian O; Walden, Peter; Wrede, Paul; Schneider, Gisbert

2010-01-12

Ant Colony Optimization (ACO) is a meta-heuristic that utilizes a computational analogue of ant trail pheromones to solve combinatorial optimization problems. The size of the ant colony and the representation of the ants' pheromone trails is unique referring to the given optimization problem. In the present study, we employed ACO to generate novel peptides that stabilize MHC I protein on the plasma membrane of a murine lymphoma cell line. A jury of feedforward neural network classifiers served as fitness function for peptide design by ACO. Bioactive murine MHC I H-2K(b) stabilizing as well as nonstabilizing octapeptides were designed, synthesized and tested. These peptides reveal residue motifs that are relevant for MHC I receptor binding. We demonstrate how the performance of the implemented ACO algorithm depends on the colony size and the size of the search space. The actual peptide design process by ACO constitutes a search path in sequence space that can be visualized as trajectories on a self-organizing map (SOM). By projecting the sequence space on a SOM we visualize the convergence of the different solutions that emerge during the optimization process in sequence space. The SOM representation reveals attractors in sequence space for MHC I binding peptides. The combination of ACO and SOM enables systematic peptide optimization. This technique allows for the rational design of various types of bioactive peptides with minimal experimental effort. Here, we demonstrate its successful application to the design of MHC-I binding and nonbinding peptides which exhibit substantial bioactivity in a cell-based assay. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An efficient, large-scale, non-lattice-detection algorithm for exhaustive structural auditing of biomedical ontologies.

PubMed

Zhang, Guo-Qiang; Xing, Guangming; Cui, Licong

2018-04-01

One of the basic challenges in developing structural methods for systematic audition on the quality of biomedical ontologies is the computational cost usually involved in exhaustive sub-graph analysis. We introduce ANT-LCA, a new algorithm for computing all non-trivial lowest common ancestors (LCA) of each pair of concepts in the hierarchical order induced by an ontology. The computation of LCA is a fundamental step for non-lattice approach for ontology quality assurance. Distinct from existing approaches, ANT-LCA only computes LCAs for non-trivial pairs, those having at least one common ancestor. To skip all trivial pairs that may be of no practical interest, ANT-LCA employs a simple but innovative algorithmic strategy combining topological order and dynamic programming to keep track of non-trivial pairs. We provide correctness proofs and demonstrate a substantial reduction in computational time for two largest biomedical ontologies: SNOMED CT and Gene Ontology (GO). ANT-LCA achieved an average computation time of 30 and 3 sec per version for SNOMED CT and GO, respectively, about 2 orders of magnitude faster than the best known approaches. Our algorithm overcomes a fundamental computational barrier in sub-graph based structural analysis of large ontological systems. It enables the implementation of a new breed of structural auditing methods that not only identifies potential problematic areas, but also automatically suggests changes to fix the issues. Such structural auditing methods can lead to more effective tools supporting ontology quality assurance work. Copyright © 2018 Elsevier Inc. All rights reserved.

X-Ray microtomography for ant taxonomy: An exploration and case study with two new Terataner (Hymenoptera, Formicidae, Myrmicinae) species from Madagascar

PubMed Central

Fischer, Georg; Liu, Cong; Audisio, Tracy L.; Alpert, Gary D.; Fisher, Brian L.; Economo, Evan P.

2017-01-01

We explore the potential of x-ray micro computed tomography (μCT) for the field of ant taxonomy by using it to enhance the descriptions of two remarkable new species of the ant genus Terataner: T. balrog sp. n. and T. nymeria sp. n.. We provide an illustrated worker-based species identification key for all species found on Madagascar, as well as detailed taxonomic descriptions, which include diagnoses, discussions, measurements, natural history data, high-quality montage images and distribution maps for both new species. In addition to conventional morphological examination, we have used virtual reconstructions based on volumetric μCT scanning data for the species descriptions. We also include 3D PDFs, still images of virtual reconstructions, and 3D rotation videos for both holotype workers and one paratype queen. The complete μCT datasets have been made available online (Dryad, https://datadryad.org) and represent the first cybertypes in ants (and insects). We discuss the potential of μCT scanning and critically assess the usefulness of cybertypes for ant taxonomy. PMID:28328931

Item Selection for the Development of Short Forms of Scales Using an Ant Colony Optimization Algorithm

ERIC Educational Resources Information Center

Leite, Walter L.; Huang, I-Chan; Marcoulides, George A.

2008-01-01

This article presents the use of an ant colony optimization (ACO) algorithm for the development of short forms of scales. An example 22-item short form is developed for the Diabetes-39 scale, a quality-of-life scale for diabetes patients, using a sample of 265 diabetes patients. A simulation study comparing the performance of the ACO algorithm and…

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Janich, Karl W.

2005-01-01

The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.

MGA trajectory planning with an ACO-inspired algorithm

NASA Astrophysics Data System (ADS)

Ceriotti, Matteo; Vasile, Massimiliano

2010-11-01

Given a set of celestial bodies, the problem of finding an optimal sequence of swing-bys, deep space manoeuvres (DSM) and transfer arcs connecting the elements of the set is combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore, the design of an optimal multiple gravity assist (MGA) trajectory is a NP-hard mixed combinatorial-continuous problem. Its automated solution would greatly improve the design of future space missions, allowing the assessment of a large number of alternative mission options in a short time. This work proposes to formulate the complete automated design of a multiple gravity assist trajectory as an autonomous planning and scheduling problem. The resulting scheduled plan will provide the optimal planetary sequence and a good estimation of the set of associated optimal trajectories. The trajectory model consists of a sequence of celestial bodies connected by two-dimensional transfer arcs containing one DSM. For each transfer arc, the position of the planet and the spacecraft, at the time of arrival, are matched by varying the pericentre of the preceding swing-by, or the magnitude of the launch excess velocity, for the first arc. For each departure date, this model generates a full tree of possible transfers from the departure to the destination planet. Each leaf of the tree represents a planetary encounter and a possible way to reach that planet. An algorithm inspired by ant colony optimization (ACO) is devised to explore the space of possible plans. The ants explore the tree from departure to destination adding one node at the time: every time an ant is at a node, a probability function is used to select a feasible direction. This approach to automatic trajectory planning is applied to the design of optimal transfers to Saturn and among the Galilean moons of Jupiter. Solutions are compared to those found through more traditional genetic-algorithm techniques.

Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem.

PubMed

Zamdborg, Leonid; Holloway, David M; Merelo, Juan J; Levchenko, Vladimir F; Spirov, Alexander V

2015-06-10

Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of "genomic parasites", such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators that adapt in response to an evolutionary problem in the course of co-evolution with their hosts.

Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem

PubMed Central

Zamdborg, Leonid; Holloway, David M.; Merelo, Juan J.; Levchenko, Vladimir F.; Spirov, Alexander V.

2015-01-01

Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of “genomic parasites”, such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators that adapt in response to an evolutionary problem in the course of co-evolution with their hosts. PMID:25767296

Using ant-behavior-based simulation model AntWeb to improve website organization

NASA Astrophysics Data System (ADS)

Li, Weigang; Pinheiro Dib, Marcos V.; Teles, Wesley M.; Morais de Andrade, Vlaudemir; Alves de Melo, Alba C. M.; Cariolano, Judas T.

2002-03-01

Some web usage mining algorithms showed the potential application to find the difference among the organizations expected by visitors to the website. However, there are still no efficient method and criterion for a web administrator to measure the performance of the modification. In this paper, we developed an AntWeb, a model inspired by ants' behavior to simulate the sequence of visiting the website, in order to measure the efficient of the web structure. We implemented a web usage mining algorithm using backtrack to the intranet website of the Politec Informatic Ltd., Brazil. We defined throughput (the number of visitors to reach their target pages per time unit relates to the total number of visitors) as an index to measure the website's performance. We also used the link in a web page to represent the effect of visitors' pheromone trails. For every modification in the website organization, for example, putting a link from the expected location to the target object, the simulation reported the value of throughput as a quick answer about this modification. The experiment showed the stability of our simulation model, and a positive modification to the intranet website of the Politec.

Efficient distribution of toy products using ant colony optimization algorithm

NASA Astrophysics Data System (ADS)

Hidayat, S.; Nurpraja, C. A.

2017-12-01

CV Atham Toys (CVAT) produces wooden toys and furniture, comprises 13 small and medium industries. CVAT always attempt to deliver customer orders on time but delivery costs are high. This is because of inadequate infrastructure such that delivery routes are long, car maintenance costs are high, while fuel subsidy by the government is still temporary. This study seeks to minimize the cost of product distribution based on the shortest route using one of five Ant Colony Optimization (ACO) algorithms to solve the Vehicle Routing Problem (VRP). This study concludes that the best of the five is the Ant Colony System (ACS) algorithm. The best route in 1st week gave a total distance of 124.11 km at a cost of Rp 66,703.75. The 2nd week route gave a total distance of 132.27 km at a cost of Rp 71,095.13. The 3rd week best route gave a total distance of 122.70 km with a cost of Rp 65,951.25. While the 4th week gave a total distance of 132.27 km at a cost of Rp 74,083.63. Prior to this study there was no effort to calculate these figures.

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

An improved ant colony optimization algorithm with fault tolerance for job scheduling in grid computing systems

PubMed Central

Idris, Hajara; Junaidu, Sahalu B.; Adewumi, Aderemi O.

2017-01-01

The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user’s Quality of Service (QoS) requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO) algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user’s QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time. PMID:28545075

Inverse estimation of the spheroidal particle size distribution using Ant Colony Optimization algorithms in multispectral extinction technique

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Wang, Yuqing; Ruan, Liming

2014-10-01

Four improved Ant Colony Optimization (ACO) algorithms, i.e. the probability density function based ACO (PDF-ACO) algorithm, the Region ACO (RACO) algorithm, Stochastic ACO (SACO) algorithm and Homogeneous ACO (HACO) algorithm, are employed to estimate the particle size distribution (PSD) of the spheroidal particles. The direct problems are solved by the extended Anomalous Diffraction Approximation (ADA) and the Lambert-Beer law. Three commonly used monomodal distribution functions i.e. the Rosin-Rammer (R-R) distribution function, the normal (N-N) distribution function, and the logarithmic normal (L-N) distribution function are estimated under dependent model. The influence of random measurement errors on the inverse results is also investigated. All the results reveal that the PDF-ACO algorithm is more accurate than the other three ACO algorithms and can be used as an effective technique to investigate the PSD of the spheroidal particles. Furthermore, the Johnson's SB (J-SB) function and the modified beta (M-β) function are employed as the general distribution functions to retrieve the PSD of spheroidal particles using PDF-ACO algorithm. The investigation shows a reasonable agreement between the original distribution function and the general distribution function when only considering the variety of the length of the rotational semi-axis.

Hybrid real-code ant colony optimisation for constrained mechanical design

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Bureerat, Sujin

2016-01-01

This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

Congestion control and routing over satellite networks

NASA Astrophysics Data System (ADS)

Cao, Jinhua

Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE) method and then develop a novel on-demand routing system named Cross Entropy Accelerated Ant Routing System (CEAARS) for regular constellation LEO satellite networks. By implementing simulations on an Iridium-like satellite network, we compare the proposed CEAARS algorithm with the two approaches to adaptive routing protocols on the Internet: distance-vector (DV) and link-state (LS), as well as with the original Cross Entropy Ant Routing System (CEARS). DV algorithms are based on distributed Bellman Ford algorithm, and LS algorithms are implementation of Dijkstras single source shortest path. The results show that CEAARS not only remarkably improves the convergence speed of achieving optimal or suboptimal paths, but also reduces the number of overhead ants (management packets).

Exploring with PAM: Prospecting ANTS Missions for Solar System Surveys

NASA Technical Reports Server (NTRS)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.

2003-01-01

ANTS (Autonomous Nano-Technology Swarm), a large (1000 member) swarm of nano to picoclass (10 to 1 kg) totally autonomous spacecraft, are being developed as a NASA advanced mission concept. ANTS, based on a hierarchical insect social order, use an evolvable, self-similar, hierarchical neural system in which individual spacecraft represent the highest level nodes. ANTS uses swarm intelligence attained through collective, cooperative interactions of the nodes at all levels of the system. At the highest levels this can take the form of cooperative, collective behavior among the individual spacecraft in a very large constellation. The ANTS neural architecture is designed for totally autonomous operation of complex systems including spacecraft constellations. The ANTS (Autonomous Nano Technology Swarm) concept has a number of possible applications. A version of ANTS designed for surveying and determining the resource potential of the asteroid belt, called PAM (Prospecting ANTS Mission), is examined here.

Rate Adaptive Based Resource Allocation with Proportional Fairness Constraints in OFDMA Systems

PubMed Central

Yin, Zhendong; Zhuang, Shufeng; Wu, Zhilu; Ma, Bo

2015-01-01

Orthogonal frequency division multiple access (OFDMA), which is widely used in the wireless sensor networks, allows different users to obtain different subcarriers according to their subchannel gains. Therefore, how to assign subcarriers and power to different users to achieve a high system sum rate is an important research area in OFDMA systems. In this paper, the focus of study is on the rate adaptive (RA) based resource allocation with proportional fairness constraints. Since the resource allocation is a NP-hard and non-convex optimization problem, a new efficient resource allocation algorithm ACO-SPA is proposed, which combines ant colony optimization (ACO) and suboptimal power allocation (SPA). To reduce the computational complexity, the optimization problem of resource allocation in OFDMA systems is separated into two steps. For the first one, the ant colony optimization algorithm is performed to solve the subcarrier allocation. Then, the suboptimal power allocation algorithm is developed with strict proportional fairness, and the algorithm is based on the principle that the sums of power and the reciprocal of channel-to-noise ratio for each user in different subchannels are equal. To support it, plenty of simulation results are presented. In contrast with root-finding and linear methods, the proposed method provides better performance in solving the proportional resource allocation problem in OFDMA systems. PMID:26426016

Using Ant Colony Optimization for Routing in VLSI Chips

NASA Astrophysics Data System (ADS)

Arora, Tamanna; Moses, Melanie

2009-04-01

Rapid advances in VLSI technology have increased the number of transistors that fit on a single chip to about two billion. A frequent problem in the design of such high performance and high density VLSI layouts is that of routing wires that connect such large numbers of components. Most wire-routing problems are computationally hard. The quality of any routing algorithm is judged by the extent to which it satisfies routing constraints and design objectives. Some of the broader design objectives include minimizing total routed wire length, and minimizing total capacitance induced in the chip, both of which serve to minimize power consumed by the chip. Ant Colony Optimization algorithms (ACO) provide a multi-agent framework for combinatorial optimization by combining memory, stochastic decision and strategies of collective and distributed learning by ant-like agents. This paper applies ACO to the NP-hard problem of finding optimal routes for interconnect routing on VLSI chips. The constraints on interconnect routing are used by ants as heuristics which guide their search process. We found that ACO algorithms were able to successfully incorporate multiple constraints and route interconnects on suite of benchmark chips. On an average, the algorithm routed with total wire length 5.5% less than other established routing algorithms.

All-Optical Implementation of the Ant Colony Optimization Algorithm

PubMed Central

Hu, Wenchao; Wu, Kan; Shum, Perry Ping; Zheludev, Nikolay I.; Soci, Cesare

2016-01-01

We report all-optical implementation of the optimization algorithm for the famous “ant colony” problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems. PMID:27222098

Ex Ante Research Explored: Numbers, Types and Use of Ex Ante Policy Studies by the Dutch Government

ERIC Educational Resources Information Center

Haarhuis, Carolien Maria Klein; Smit, Monika

2017-01-01

Ex ante research can contribute to evidence-informed policies. In this article, we explore numbers and types of ex ante studies as well as their use. First, we took stock of a potentially wide range of ex ante studies published by the Dutch government between 2005 and 2011, applying a systematic approach. Though unevenly distributed across…

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

[Application of rational ant colony optimization to improve the reproducibility degree of laser three-dimensional copy].

PubMed

Cui, Xiao-Yan; Huo, Zhong-Gang; Xin, Zhong-Hua; Tian, Xiao; Zhang, Xiao-Dong

2013-07-01

Three-dimensional (3D) copying of artificial ears and pistol printing are pushing laser three-dimensional copying technique to a new page. Laser three-dimensional scanning is a fresh field in laser application, and plays an irreplaceable part in three-dimensional copying. Its accuracy is the highest among all present copying techniques. Reproducibility degree marks the agreement of copied object with the original object on geometry, being the most important index property in laser three-dimensional copying technique. In the present paper, the error of laser three-dimensional copying was analyzed. The conclusion is that the data processing to the point cloud of laser scanning is the key technique to reduce the error and increase the reproducibility degree. The main innovation of this paper is as follows. On the basis of traditional ant colony optimization, rational ant colony optimization algorithm proposed by the author was applied to the laser three-dimensional copying as a new algorithm, and was put into practice. Compared with customary algorithm, rational ant colony optimization algorithm shows distinct advantages in data processing of laser three-dimensional copying, reducing the error and increasing the reproducibility degree of the copy.

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

Swarm Intelligence Optimization and Its Applications

NASA Astrophysics Data System (ADS)

Ding, Caichang; Lu, Lu; Liu, Yuanchao; Peng, Wenxiu

Swarm Intelligence is a computational and behavioral metaphor for solving distributed problems inspired from biological examples provided by social insects such as ants, termites, bees, and wasps and by swarm, herd, flock, and shoal phenomena in vertebrates such as fish shoals and bird flocks. An example of successful research direction in Swarm Intelligence is ant colony optimization (ACO), which focuses on combinatorial optimization problems. Ant algorithms can be viewed as multi-agent systems (ant colony), where agents (individual ants) solve required tasks through cooperation in the same way that ants create complex social behavior from the combined efforts of individuals.

The Ants Have It!

ERIC Educational Resources Information Center

Daugherty, Belinda

2001-01-01

Uses the GEMS guide, "Ants at Home Underground", to explore the life of ants and teach about them in a classroom setting. The activity applies students' knowledge of ants and students learn about ant colonies, what ants eat, and how they live. (SAH)

Application of ant colony optimization to optimal foragaing theory: comparison of simulation and field results

USDA-ARS?s Scientific Manuscript database

Ant Colony Optimization (ACO) refers to the family of algorithms inspired by the behavior of real ants and used to solve combinatorial problems such as the Traveling Salesman Problem (TSP).Optimal Foraging Theory (OFT) is an evolutionary principle wherein foraging organisms or insect parasites seek ...

Verification of NASA Emergent Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy K. C. S.; Truszkowski, Walt; Rash, James; Hinchey, Mike

2004-01-01

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. This mission, the prospective ANTS (Autonomous Nano Technology Swarm) mission, will comprise of 1,000 autonomous robotic agents designed to cooperate in asteroid exploration. The emergent properties of swarm type missions make them powerful, but at the same time are more difficult to design and assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of future swarm-based missions. The advantage of using formal methods is their ability to mathematically assure the behavior of a swarm, emergent or otherwise. The ANT mission is being used as an example and case study for swarm-based missions for which to experiment and test current formal methods with intelligent swam. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior.

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems

PubMed Central

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

PubMed

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

An Adaptive Pheromone Updation of the Ant-System using LMS Technique

NASA Astrophysics Data System (ADS)

Paul, Abhishek; Mukhopadhyay, Sumitra

2010-10-01

We propose a modified model of pheromone updation for Ant-System, entitled as Adaptive Ant System (AAS), using the properties of basic Adaptive Filters. Here, we have exploited the properties of Least Mean Square (LMS) algorithm for the pheromone updation to find out the best minimum tour for the Travelling Salesman Problem (TSP). TSP library has been used for the selection of benchmark problem and the proposed AAS determines the minimum tour length for the problems containing large number of cities. Our algorithm shows effective results and gives least tour length in most of the cases as compared to other existing approaches.

The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated decision making.

PubMed

Hoover, Kevin M; Bubak, Andrew N; Law, Isaac J; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J

2016-06-01

Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant's brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.

Optic disc detection using ant colony optimization

NASA Astrophysics Data System (ADS)

Dias, Marcy A.; Monteiro, Fernando C.

2012-09-01

The retinal fundus images are used in the treatment and diagnosis of several eye diseases, such as diabetic retinopathy and glaucoma. This paper proposes a new method to detect the optic disc (OD) automatically, due to the fact that the knowledge of the OD location is essential to the automatic analysis of retinal images. Ant Colony Optimization (ACO) is an optimization algorithm inspired by the foraging behaviour of some ant species that has been applied in image processing for edge detection. Recently, the ACO was used in fundus images to detect edges, and therefore, to segment the OD and other anatomical retinal structures. We present an algorithm for the detection of OD in the retina which takes advantage of the Gabor wavelet transform, entropy and ACO algorithm. Forty images of the retina from DRIVE database were used to evaluate the performance of our method.

Predicting Flood in Perlis Using Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Nadia Sabri, Syaidatul; Saian, Rizauddin

2017-06-01

Flood forecasting is widely being studied in order to reduce the effect of flood such as loss of property, loss of life and contamination of water supply. Usually flood occurs due to continuous heavy rainfall. This study used a variant of Ant Colony Optimization (ACO) algorithm named the Ant-Miner to develop the classification prediction model to predict flood. However, since Ant-Miner only accept discrete data, while rainfall data is a time series data, a pre-processing steps is needed to discretize the rainfall data initially. This study used a technique called the Symbolic Aggregate Approximation (SAX) to convert the rainfall time series data into discrete data. As an addition, Simple K-Means algorithm was used to cluster the data produced by SAX. The findings show that the predictive accuracy of the classification prediction model is more than 80%.

A Stochastic Inversion Method for Potential Field Data: Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Liu, Tianyou

2014-07-01

Simulating natural ants' foraging behavior, the ant colony optimization (ACO) algorithm performs excellently in combinational optimization problems, for example the traveling salesman problem and the quadratic assignment problem. However, the ACO is seldom used to inverted for gravitational and magnetic data. On the basis of the continuous and multi-dimensional objective function for potential field data optimization inversion, we present the node partition strategy ACO (NP-ACO) algorithm for inversion of model variables of fixed shape and recovery of physical property distributions of complicated shape models. We divide the continuous variables into discrete nodes and ants directionally tour the nodes by use of transition probabilities. We update the pheromone trails by use of Gaussian mapping between the objective function value and the quantity of pheromone. It can analyze the search results in real time and promote the rate of convergence and precision of inversion. Traditional mapping, including the ant-cycle system, weaken the differences between ant individuals and lead to premature convergence. We tested our method by use of synthetic data and real data from scenarios involving gravity and magnetic anomalies. The inverted model variables and recovered physical property distributions were in good agreement with the true values. The ACO algorithm for binary representation imaging and full imaging can recover sharper physical property distributions than traditional linear inversion methods. The ACO has good optimization capability and some excellent characteristics, for example robustness, parallel implementation, and portability, compared with other stochastic metaheuristics.

A tunable algorithm for collective decision-making.

PubMed

Pratt, Stephen C; Sumpter, David J T

2006-10-24

Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.

Reinforcement interval type-2 fuzzy controller design by online rule generation and q-value-aided ant colony optimization.

PubMed

Juang, Chia-Feng; Hsu, Chia-Hung

2009-12-01

This paper proposes a new reinforcement-learning method using online rule generation and Q-value-aided ant colony optimization (ORGQACO) for fuzzy controller design. The fuzzy controller is based on an interval type-2 fuzzy system (IT2FS). The antecedent part in the designed IT2FS uses interval type-2 fuzzy sets to improve controller robustness to noise. There are initially no fuzzy rules in the IT2FS. The ORGQACO concurrently designs both the structure and parameters of an IT2FS. We propose an online interval type-2 rule generation method for the evolution of system structure and flexible partitioning of the input space. Consequent part parameters in an IT2FS are designed using Q -values and the reinforcement local-global ant colony optimization algorithm. This algorithm selects the consequent part from a set of candidate actions according to ant pheromone trails and Q-values, both of which are updated using reinforcement signals. The ORGQACO design method is applied to the following three control problems: 1) truck-backing control; 2) magnetic-levitation control; and 3) chaotic-system control. The ORGQACO is compared with other reinforcement-learning methods to verify its efficiency and effectiveness. Comparisons with type-1 fuzzy systems verify the noise robustness property of using an IT2FS.

Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

NASA Astrophysics Data System (ADS)

Ge, Junwei; Cai, Yu; Fang, Yiqiu

2018-05-01

This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

Dynamic vehicle routing with time windows in theory and practice.

PubMed

Yang, Zhiwei; van Osta, Jan-Paul; van Veen, Barry; van Krevelen, Rick; van Klaveren, Richard; Stam, Andries; Kok, Joost; Bäck, Thomas; Emmerich, Michael

2017-01-01

The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon's benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment.

Adaptive algorithms of position and energy reconstruction in Anger-camera type detectors: experimental data processing in ANTS

NASA Astrophysics Data System (ADS)

Morozov, A.; Defendi, I.; Engels, R.; Fraga, F. A. F.; Fraga, M. M. F. R.; Gongadze, A.; Guerard, B.; Jurkovic, M.; Kemmerling, G.; Manzin, G.; Margato, L. M. S.; Niko, H.; Pereira, L.; Petrillo, C.; Peyaud, A.; Piscitelli, F.; Raspino, D.; Rhodes, N. J.; Sacchetti, F.; Schooneveld, E. M.; Solovov, V.; Van Esch, P.; Zeitelhack, K.

2013-05-01

The software package ANTS (Anger-camera type Neutron detector: Toolkit for Simulations), developed for simulation of Anger-type gaseous detectors for thermal neutron imaging was extended to include a module for experimental data processing. Data recorded with a sensor array containing up to 100 photomultiplier tubes (PMT) or silicon photomultipliers (SiPM) in a custom configuration can be loaded and the positions and energies of the events can be reconstructed using the Center-of-Gravity, Maximum Likelihood or Least Squares algorithm. A particular strength of the new module is the ability to reconstruct the light response functions and relative gains of the photomultipliers from flood field illumination data using adaptive algorithms. The performance of the module is demonstrated with simulated data generated in ANTS and experimental data recorded with a 19 PMT neutron detector. The package executables are publicly available at http://coimbra.lip.pt/~andrei/

The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated decision making

PubMed Central

Hoover, Kevin M.; Bubak, Andrew N.; Law, Isaac J.; Yaeger, Jazmine D. W.; Renner, Kenneth J.; Swallow, John G.; Greene, Michael J.

2016-01-01

Abstract Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant’s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions. PMID:29491915

Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR.

PubMed

Tustison, Nicholas J; Shrinidhi, K L; Wintermark, Max; Durst, Christopher R; Kandel, Benjamin M; Gee, James C; Grossman, Murray C; Avants, Brian B

2015-04-01

Segmenting and quantifying gliomas from MRI is an important task for diagnosis, planning intervention, and for tracking tumor changes over time. However, this task is complicated by the lack of prior knowledge concerning tumor location, spatial extent, shape, possible displacement of normal tissue, and intensity signature. To accommodate such complications, we introduce a framework for supervised segmentation based on multiple modality intensity, geometry, and asymmetry feature sets. These features drive a supervised whole-brain and tumor segmentation approach based on random forest-derived probabilities. The asymmetry-related features (based on optimal symmetric multimodal templates) demonstrate excellent discriminative properties within this framework. We also gain performance by generating probability maps from random forest models and using these maps for a refining Markov random field regularized probabilistic segmentation. This strategy allows us to interface the supervised learning capabilities of the random forest model with regularized probabilistic segmentation using the recently developed ANTsR package--a comprehensive statistical and visualization interface between the popular Advanced Normalization Tools (ANTs) and the R statistical project. The reported algorithmic framework was the top-performing entry in the MICCAI 2013 Multimodal Brain Tumor Segmentation challenge. The challenge data were widely varying consisting of both high-grade and low-grade glioma tumor four-modality MRI from five different institutions. Average Dice overlap measures for the final algorithmic assessment were 0.87, 0.78, and 0.74 for "complete", "core", and "enhanced" tumor components, respectively.

An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem

DTIC Science & Technology

2015-01-01

programming formulation of traveling salesman problems , Journal of the ACM, 7(4), 326-329. Montemanni, R., Gambardella, L. M., Rizzoli, A.E., Donati. A.V... salesman problem . BioSystem, 43(1), 73-81. Dror, M., Trudeau, P., 1989. Savings by split delivery routing. Transportation Science, 23, 141- 145. Dror, M...An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to solve the Split Delivery Vehicle Routing Problem Authors: Gautham Rajappa

A multilevel ant colony optimization algorithm for classical and isothermic DNA sequencing by hybridization with multiplicity information available.

PubMed

Kwarciak, Kamil; Radom, Marcin; Formanowicz, Piotr

2016-04-01

The classical sequencing by hybridization takes into account a binary information about sequence composition. A given element from an oligonucleotide library is or is not a part of the target sequence. However, the DNA chip technology has been developed and it enables to receive a partial information about multiplicity of each oligonucleotide the analyzed sequence consist of. Currently, it is not possible to assess the exact data of such type but even partial information should be very useful. Two realistic multiplicity information models are taken into consideration in this paper. The first one, called "one and many" assumes that it is possible to obtain information if a given oligonucleotide occurs in a reconstructed sequence once or more than once. According to the second model, called "one, two and many", one is able to receive from biochemical experiment information if a given oligonucleotide is present in an analyzed sequence once, twice or at least three times. An ant colony optimization algorithm has been implemented to verify the above models and to compare with existing algorithms for sequencing by hybridization which utilize the additional information. The proposed algorithm solves the problem with any kind of hybridization errors. Computational experiment results confirm that using even the partial information about multiplicity leads to increased quality of reconstructed sequences. Moreover, they also show that the more precise model enables to obtain better solutions and the ant colony optimization algorithm outperforms the existing ones. Test data sets and the proposed ant colony optimization algorithm are available on: http://bioserver.cs.put.poznan.pl/download/ACO4mSBH.zip. Copyright © 2016 Elsevier Ltd. All rights reserved.

Composite collective decision-making

PubMed Central

Czaczkes, Tomer J.; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen

2015-01-01

Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms. PMID:26019155

TACD: a transportable ant colony discrimination model for corporate bankruptcy prediction

NASA Astrophysics Data System (ADS)

Lalbakhsh, Pooia; Chen, Yi-Ping Phoebe

2017-05-01

This paper presents a transportable ant colony discrimination strategy (TACD) to predict corporate bankruptcy, a topic of vital importance that is attracting increasing interest in the field of economics. The proposed algorithm uses financial ratios to build a binary prediction model for companies with the two statuses of bankrupt and non-bankrupt. The algorithm takes advantage of an improved version of continuous ant colony optimisation (CACO) at the core, which is used to create an accurate, simple and understandable linear model for discrimination. This also enables the algorithm to work with continuous values, leading to more efficient learning and adaption by avoiding data discretisation. We conduct a comprehensive performance evaluation on three real-world data sets under a stratified cross-validation strategy. In three different scenarios, TACD is compared with 11 other bankruptcy prediction strategies. We also discuss the efficiency of the attribute selection methods used in the experiments. In addition to its simplicity and understandability, statistical significance tests prove the efficiency of TACD against the other prediction algorithms in both measures of AUC and accuracy.

Autonomous Agents on Expedition: Humans and Progenitor Ants and Planetary Exploration

NASA Astrophysics Data System (ADS)

Rilee, M. L.; Clark, P. E.; Curtis, S. A.; Truszkowski, W. F.

2002-01-01

The Autonomous Nano-Technology Swarm (ANTS) is an advanced mission architecture based on a social insect analog of many specialized spacecraft working together to achieve mission goals. The principal mission concept driving the ANTS architecture is a Main Belt Asteroid Survey in the 2020s that will involve a thousand or more nano-technology enabled, artificially intelligent, autonomous pico-spacecraft (< 1 kg). The objective of this survey is to construct a compendium of composition, shape, and other physical parameter observations of a significant fraction of asteroid belt objects. Such an atlas will be of primary scientific importance for the understanding of Solar System origins and evolution and will lay the foundation for future exploration and capitalization of space. As the capabilities enabling ANTS are developed over the next two decades, these capabilities will need to be proven. Natural milestones for this process include the deployment of progenitors to ANTS on human expeditions to space and remote missions with interfaces for human interaction and control. These progenitors can show up in a variety of forms ranging from spacecraft subsystems and advanced handheld sensors, through complete prototypical ANTS spacecraft. A critical capability to be demonstrated is reliable, long-term autonomous operations across the ANTS architecture. High level, mission-oriented behaviors are to be managed by a control / communications layer of the swarm, whereas common low level functions required of all spacecraft, e.g. attitude control and guidance and navigation, are handled autonomically on each spacecraft. At the higher levels of mission planning and social interaction deliberative techniques are to be used. For the asteroid survey, ANTS acts as a large community of cooperative agents while for precursor missions there arises the intriguing possibility of Progenitor ANTS and humans acting together as agents. For optimal efficiency and responsiveness for individual spacecraft at the lowest levels of control we have been studying control methods based on nonlinear dynamical systems. We describe the critically important autonomous control architecture of the ANTS mission concept and a sequence of partial implementations that feature increasingly autonomous behaviors. The scientific and engineering roles that these Progenitor ANTS could play in human missions or remote missions with near real time human interactions, particularly to the Moon and Mars, will be discussed.

Improved discrete swarm intelligence algorithms for endmember extraction from hyperspectral remote sensing images

NASA Astrophysics Data System (ADS)

Su, Yuanchao; Sun, Xu; Gao, Lianru; Li, Jun; Zhang, Bing

2016-10-01

Endmember extraction is a key step in hyperspectral unmixing. A new endmember extraction framework is proposed for hyperspectral endmember extraction. The proposed approach is based on the swarm intelligence (SI) algorithm, where discretization is used to solve the SI algorithm because pixels in a hyperspectral image are naturally defined within a discrete space. Moreover, a "distance" factor is introduced into the objective function to limit the endmember numbers which is generally limited in real scenarios, while traditional SI algorithms likely produce superabundant spectral signatures, which generally belong to the same classes. Three endmember extraction methods are proposed based on the artificial bee colony, ant colony optimization, and particle swarm optimization algorithms. Experiments with both simulated and real hyperspectral images indicate that the proposed framework can improve the accuracy of endmember extraction.

An element search ant colony technique for solving virtual machine placement problem

NASA Astrophysics Data System (ADS)

Srija, J.; Rani John, Rose; Kanaga, Grace Mary, Dr.

2017-09-01

The data centres in the cloud environment play a key role in providing infrastructure for ubiquitous computing, pervasive computing, mobile computing etc. This computing technique tries to utilize the available resources in order to provide services. Hence maintaining the resource utilization without wastage of power consumption has become a challenging task for the researchers. In this paper we propose the direct guidance ant colony system for effective mapping of virtual machines to the physical machine with maximal resource utilization and minimal power consumption. The proposed algorithm has been compared with the existing ant colony approach which is involved in solving virtual machine placement problem and thus the proposed algorithm proves to provide better result than the existing technique.

Ant colony system algorithm for the optimization of beer fermentation control.

PubMed

Xiao, Jie; Zhou, Ze-Kui; Zhang, Guang-Xin

2004-12-01

Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture were constructed. An optimal one was chosen at last. Optimal temperature profile maximized the final ethanol production and minimized the byproducts concentration and spoilage risk. The satisfactory results obtained did not require much computation effort.

Multiple-hopping trajectories near a rotating asteroid

NASA Astrophysics Data System (ADS)

Shen, Hong-Xin; Zhang, Tian-Jiao; Li, Zhao; Li, Heng-Nian

2017-03-01

We present a study of the transfer orbits connecting landing points of irregular-shaped asteroids. The landing points do not touch the surface of the asteroids and are chosen several meters above the surface. The ant colony optimization technique is used to calculate the multiple-hopping trajectories near an arbitrary irregular asteroid. This new method has three steps which are as follows: (1) the search of the maximal clique of candidate target landing points; (2) leg optimization connecting all landing point pairs; and (3) the hopping sequence optimization. In particular this method is applied to asteroids 433 Eros and 216 Kleopatra. We impose a critical constraint on the target landing points to allow for extensive exploration of the asteroid: the relative distance between all the arrived target positions should be larger than a minimum allowed value. Ant colony optimization is applied to find the set and sequence of targets, and the differential evolution algorithm is used to solve for the hopping orbits. The minimum-velocity increment tours of hopping trajectories connecting all the landing positions are obtained by ant colony optimization. The results from different size asteroids indicate that the cost of the minimum velocity-increment tour depends on the size of the asteroids.

Swarm Intelligence for Urban Dynamics Modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

2009-04-16

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Swarm Intelligence for Urban Dynamics Modelling

NASA Astrophysics Data System (ADS)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

2009-04-01

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

A Family of ACO Routing Protocols for Mobile Ad Hoc Networks.

PubMed

Rupérez Cañas, Delfín; Sandoval Orozco, Ana Lucila; García Villalba, Luis Javier; Kim, Tai-Hoon

2017-05-22

In this work, an ACO routing protocol for mobile ad hoc networks based on AntHocNet is specified. As its predecessor, this new protocol, called AntOR, is hybrid in the sense that it contains elements from both reactive and proactive routing. Specifically, it combines a reactive route setup process with a proactive route maintenance and improvement process. Key aspects of the AntOR protocol are the disjoint-link and disjoint-node routes, separation between the regular pheromone and the virtual pheromone in the diffusion process and the exploration of routes, taking into consideration the number of hops in the best routes. In this work, a family of ACO routing protocols based on AntOR is also specified. These protocols are based on protocol successive refinements. In this work, we also present a parallelized version of AntOR that we call PAntOR. Using programming multiprocessor architectures based on the shared memory protocol, PAntOR allows running tasks in parallel using threads. This parallelization is applicable in the route setup phase, route local repair process and link failure notification. In addition, a variant of PAntOR that consists of having more than one interface, which we call PAntOR-MI (PAntOR-Multiple Interface), is specified. This approach parallelizes the sending of broadcast messages by interface through threads.

Revolutionizing Remote Exploration with ANTS

NASA Astrophysics Data System (ADS)

Clark, P. E.; Rilee, M. L.; Curtis, S.; Truszkowski, W.

2002-05-01

We are developing the Autonomous Nano-Technology Swarm (ANTS) architecture based on an insect colony analogue for the cost-effective, efficient, systematic survey of remote or inaccessible areas with multiple object targets, including planetary surface, marine, airborne, and space environments. The mission context is the exploration in the 2020s of the most compelling remaining targets in the solar system: main belt asteroids. Main belt asteroids harbor important clues to Solar System origins and evolution which are central to NASA's goals in Space Science. Asteroids are smaller than planets, but their number is far greater, and their combined surface area likely dwarfs the Earth's. An asteroid survey will dramatically increase our understanding of the local resources available for the Human Exploration and Development of Space. During the mission composition, shape, gravity, and orbit parameters could be returned to Earth for perhaps several thousand asteroids. A survey of this area will rival the great explorations that encircled this globe, opened up the New World, and laid the groundwork for the progress and challenges of the last centuries. The ANTS architecture for a main belt survey consists of a swarm of as many as a thousand or more highly specialized pico-spacecraft that form teams to survey as many as one hundred asteroids a month. Multi-level autonomy is critical for ANTS and the objective of the proposed study is to work through the implications and constraints this entails. ANTS couples biologically inspired autonomic control for basic functions to higher level artificial intelligence that together enable individual spacecraft to operate as specialized, cooperative, social agents. This revolutionary approach postulates highly advanced, but familiar, components integrated and operated in a way that uniquely transcends any evolutionary extrapolation of existing trends and enables thousand-spacecraft missions.

An ant colony optimization based feature selection for web page classification.

PubMed

Saraç, Esra; Özel, Selma Ayşe

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

An improved harmony search algorithm for emergency inspection scheduling

NASA Astrophysics Data System (ADS)

Kallioras, Nikos A.; Lagaros, Nikos D.; Karlaftis, Matthew G.

2014-11-01

The ability of nature-inspired search algorithms to efficiently handle combinatorial problems, and their successful implementation in many fields of engineering and applied sciences, have led to the development of new, improved algorithms. In this work, an improved harmony search (IHS) algorithm is presented, while a holistic approach for solving the problem of post-disaster infrastructure management is also proposed. The efficiency of IHS is compared with that of the algorithms of particle swarm optimization, differential evolution, basic harmony search and the pure random search procedure, when solving the districting problem that is the first part of post-disaster infrastructure management. The ant colony optimization algorithm is employed for solving the associated routing problem that constitutes the second part. The comparison is based on the quality of the results obtained, the computational demands and the sensitivity on the algorithmic parameters.

PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm.

PubMed

Zaidman, Daniel; Wolfson, Haim J

2016-08-01

Design of protein-protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5-15 amino acid long), are natural candidates for inhibition of protein-protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein-protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space ([Formula: see text]) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/. danielza@post.tau.ac.il; wolfson@tau.ac.il. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems.

PubMed

Mavrovouniotis, Michalis; Muller, Felipe M; Yang, Shengxiang

2016-06-13

For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms have proved to be powerful methods to tackle such problems due to their adaptation capabilities. It has been shown that the integration of local search operators can significantly improve the performance of ACO. In this paper, a memetic ACO algorithm, where a local search operator (called unstring and string) is integrated into ACO, is proposed to address DTSPs. The best solution from ACO is passed to the local search operator, which removes and inserts cities in such a way that improves the solution quality. The proposed memetic ACO algorithm is designed to address both symmetric and asymmetric DTSPs. The experimental results show the efficiency of the proposed memetic algorithm for addressing DTSPs in comparison with other state-of-the-art algorithms.

Application of ant colony algorithm in path planning of the data center room robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Ma, Jianming; Wang, Ying

2017-05-01

According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.

A modify ant colony optimization for the grid jobs scheduling problem with QoS requirements

NASA Astrophysics Data System (ADS)

Pu, Xun; Lu, XianLiang

2011-10-01

Job scheduling with customers' quality of service (QoS) requirement is challenging in grid environment. In this paper, we present a modify Ant colony optimization (MACO) for the Job scheduling problem in grid. Instead of using the conventional construction approach to construct feasible schedules, the proposed algorithm employs a decomposition method to satisfy the customer's deadline and cost requirements. Besides, a new mechanism of service instances state updating is embedded to improve the convergence of MACO. Experiments demonstrate the effectiveness of the proposed algorithm.

Composite collective decision-making.

PubMed

Czaczkes, Tomer J; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen

2015-06-22

Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

Detection and Length Estimation of Linear Scratch on Solid Surfaces Using an Angle Constrained Ant Colony Technique

NASA Astrophysics Data System (ADS)

Pal, Siddharth; Basak, Aniruddha; Das, Swagatam

In many manufacturing areas the detection of surface defects is one of the most important processes in quality control. Currently in order to detect small scratches on solid surfaces most of the industries working on material manufacturing rely on visual inspection primarily. In this article we propose a hybrid computational intelligence technique to automatically detect a linear scratch from a solid surface and estimate its length (in pixel unit) simultaneously. The approach is based on a swarm intelligence algorithm called Ant Colony Optimization (ACO) and image preprocessing with Wiener and Sobel filters as well as the Canny edge detector. The ACO algorithm is mostly used to compensate for the broken parts of the scratch. Our experimental results confirm that the proposed technique can be used for detecting scratches from noisy and degraded images, even when it is very difficult for conventional image processing to distinguish the scratch area from its background.

Scope of Various Random Number Generators in Ant System Approach for TSP

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam Ali

2007-01-01

Experimented on heuristic, based on an ant system approach for traveling Salesman problem, are several quasi and pseudo-random number generators. This experiment is to explore if any particular generator is most desirable. Such an experiment on large samples has the potential to rank the performance of the generators for the foregoing heuristic. This is just to seek an answer to the controversial performance ranking of the generators in probabilistic/statically sense.

Anthills in School Ecology

ERIC Educational Resources Information Center

Pawson, J. Marke

1975-01-01

Suggests experiments with field ants which can demonstrate the effect an organism has on its surroundings. The ecological aspects explored are plant distribution on the ant hills and the differences between ant hills and the undisturbed soil surrounding. (BR)

A Family of ACO Routing Protocols for Mobile Ad Hoc Networks

PubMed Central

Rupérez Cañas, Delfín; Sandoval Orozco, Ana Lucila; García Villalba, Luis Javier; Kim, Tai-hoon

2017-01-01

In this work, an ACO routing protocol for mobile ad hoc networks based on AntHocNet is specified. As its predecessor, this new protocol, called AntOR, is hybrid in the sense that it contains elements from both reactive and proactive routing. Specifically, it combines a reactive route setup process with a proactive route maintenance and improvement process. Key aspects of the AntOR protocol are the disjoint-link and disjoint-node routes, separation between the regular pheromone and the virtual pheromone in the diffusion process and the exploration of routes, taking into consideration the number of hops in the best routes. In this work, a family of ACO routing protocols based on AntOR is also specified. These protocols are based on protocol successive refinements. In this work, we also present a parallelized version of AntOR that we call PAntOR. Using programming multiprocessor architectures based on the shared memory protocol, PAntOR allows running tasks in parallel using threads. This parallelization is applicable in the route setup phase, route local repair process and link failure notification. In addition, a variant of PAntOR that consists of having more than one interface, which we call PAntOR-MI (PAntOR-Multiple Interface), is specified. This approach parallelizes the sending of broadcast messages by interface through threads. PMID:28531159

A Hybrid Ant Colony Optimization Algorithm for the Extended Capacitated Arc Routing Problem.

PubMed

Li-Ning Xing; Rohlfshagen, P; Ying-Wu Chen; Xin Yao

2011-08-01

The capacitated arc routing problem (CARP) is representative of numerous practical applications, and in order to widen its scope, we consider an extended version of this problem that entails both total service time and fixed investment costs. We subsequently propose a hybrid ant colony optimization (ACO) algorithm (HACOA) to solve instances of the extended CARP. This approach is characterized by the exploitation of heuristic information, adaptive parameters, and local optimization techniques: Two kinds of heuristic information, arc cluster information and arc priority information, are obtained continuously from the solutions sampled to guide the subsequent optimization process. The adaptive parameters ease the burden of choosing initial values and facilitate improved and more robust results. Finally, local optimization, based on the two-opt heuristic, is employed to improve the overall performance of the proposed algorithm. The resulting HACOA is tested on four sets of benchmark problems containing a total of 87 instances with up to 140 nodes and 380 arcs. In order to evaluate the effectiveness of the proposed method, some existing capacitated arc routing heuristics are extended to cope with the extended version of this problem; the experimental results indicate that the proposed ACO method outperforms these heuristics.

Ant Colony Optimization Algorithm for Centralized Dynamic Channel Allocation in Multi-Cell OFDMA Systems

NASA Astrophysics Data System (ADS)

Kim, Hyo-Su; Kim, Dong-Hoi

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

NASA Astrophysics Data System (ADS)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

PubMed Central

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem. PMID:24489491

An improved hierarchical genetic algorithm for sheet cutting scheduling with process constraints.

PubMed

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony--hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem.

Exploring with PAM: Prospecting ANTS Missions for Solar System Surveys

NASA Astrophysics Data System (ADS)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.

2003-03-01

ANTS (Autonomous Nano Technology Swarm of hundreds of picoclass autonomous spacecraft) have many applications. A version designed for surveying and the resource potential of the asteroid belt, called PAM (Prospecting ANTS Mission), is examined here.

How territoriality and host-tree taxa determine the structure of ant mosaics.

PubMed

Dejean, Alain; Ryder, Suzanne; Bolton, Barry; Compin, Arthur; Leponce, Maurice; Azémar, Frédéric; Céréghino, Régis; Orivel, Jérôme; Corbara, Bruno

2015-06-01

Very large colonies of territorially dominant arboreal ants (TDAAs), whose territories are distributed in a mosaic pattern in the canopies of many tropical rainforests and tree crop plantations, have a generally positive impact on their host trees. We studied the canopy of an old Gabonese rainforest (ca 4.25 ha sampled, corresponding to 206 "large" trees) at a stage just preceding forest maturity (the Caesalpinioideae dominated; the Burseraceae were abundant). The tree crowns sheltered colonies from 13 TDAAs plus a co-dominant species out of the 25 ant species recorded. By mapping the TDAAs' territories and using a null model co-occurrence analysis, we confirmed the existence of an ant mosaic. Thanks to a large sampling set and the use of the self-organizing map algorithm (SOM), we show that the distribution of the trees influences the structure of the ant mosaic, suggesting that each tree taxon attracts certain TDAA species rather than others. The SOM also improved our knowledge of the TDAAs' ecological niches, showing that these ant species are ecologically distinct from each other based on their relationships with their supporting trees. Therefore, TDAAs should not systematically be placed in the same functional group even when they belong to the same genus. We conclude by reiterating that, in addition to the role played by TDAAs' territorial competition, host trees contribute to structuring ant mosaics through multiple factors, including host-plant selection by TDAAs, the age of the trees, the presence of extrafloral nectaries, and the taxa of the associated hemipterans.

How territoriality and host-tree taxa determine the structure of ant mosaics

NASA Astrophysics Data System (ADS)

Dejean, Alain; Ryder, Suzanne; Bolton, Barry; Compin, Arthur; Leponce, Maurice; Azémar, Frédéric; Céréghino, Régis; Orivel, Jérôme; Corbara, Bruno

2015-06-01

Very large colonies of territorially dominant arboreal ants (TDAAs), whose territories are distributed in a mosaic pattern in the canopies of many tropical rainforests and tree crop plantations, have a generally positive impact on their host trees. We studied the canopy of an old Gabonese rainforest (ca 4.25 ha sampled, corresponding to 206 "large" trees) at a stage just preceding forest maturity (the Caesalpinioideae dominated; the Burseraceae were abundant). The tree crowns sheltered colonies from 13 TDAAs plus a co-dominant species out of the 25 ant species recorded. By mapping the TDAAs' territories and using a null model co-occurrence analysis, we confirmed the existence of an ant mosaic. Thanks to a large sampling set and the use of the self-organizing map algorithm (SOM), we show that the distribution of the trees influences the structure of the ant mosaic, suggesting that each tree taxon attracts certain TDAA species rather than others. The SOM also improved our knowledge of the TDAAs' ecological niches, showing that these ant species are ecologically distinct from each other based on their relationships with their supporting trees. Therefore, TDAAs should not systematically be placed in the same functional group even when they belong to the same genus. We conclude by reiterating that, in addition to the role played by TDAAs' territorial competition, host trees contribute to structuring ant mosaics through multiple factors, including host-plant selection by TDAAs, the age of the trees, the presence of extrafloral nectaries, and the taxa of the associated hemipterans.

Swarmathon 2017

NASA Image and Video Library

2017-04-19

In the Swarmathon competition at the Kennedy Space Center Visitor Complex, students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of AprilTag cubes, similar to barcodes. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food. In the spaceport's second annual Swarmathon, 20 teams representing 22 minority serving universities and community colleges were invited to develop software code to operate these innovative robots known as "Swarmies" to help find resources when astronauts explore distant locations, such as the moon or Mars.

Swarmathon 2017

NASA Image and Video Library

2017-04-20

In the Swarmathon competition at the Kennedy Space Center Visitor Complex, students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of cubes with AprilTags, similar to barcodes. Teams developed search algorithms for innovative robots known as "Swarmies" to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food. In the spaceport's second annual Swarmathon, 20 teams representing 22 minority serving universities and community colleges were invited to participate. Similar robots could help find resources when astronauts explore distant locations, such as the moon or Mars.

Swarmathon 2018

NASA Image and Video Library

2018-04-18

In the Swarmathon competition at the Kennedy Space Center Visitor Complex, students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of AprilTag cubes, similar to barcodes. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food. In the spaceport's third annual Swarmathon, 23 teams represented 24 minority serving universities and community colleges were invited to develop software code to operate these innovative robots known as "Swarmies" to help find resources when astronauts explore distant locations, such as the Moon or Mars.

Swarmathon 2018

NASA Image and Video Library

2018-04-17

In the Swarmathon competition at the Kennedy Space Center Visitor Complex, students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of AprilTag cubes, similar to barcodes. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food. In the spaceport's third annual Swarmathon, 23 teams represented 24 minority serving universities and community colleges were invited to develop software code to operate these innovative robots known as "Swarmies" to help find resources when astronauts explore distant locations, such as the Moon or Mars.

An imperialist competitive algorithm for virtual machine placement in cloud computing

NASA Astrophysics Data System (ADS)

Jamali, Shahram; Malektaji, Sepideh; Analoui, Morteza

2017-05-01

Cloud computing, the recently emerged revolution in IT industry, is empowered by virtualisation technology. In this paradigm, the user's applications run over some virtual machines (VMs). The process of selecting proper physical machines to host these virtual machines is called virtual machine placement. It plays an important role on resource utilisation and power efficiency of cloud computing environment. In this paper, we propose an imperialist competitive-based algorithm for the virtual machine placement problem called ICA-VMPLC. The base optimisation algorithm is chosen to be ICA because of its ease in neighbourhood movement, good convergence rate and suitable terminology. The proposed algorithm investigates search space in a unique manner to efficiently obtain optimal placement solution that simultaneously minimises power consumption and total resource wastage. Its final solution performance is compared with several existing methods such as grouping genetic and ant colony-based algorithms as well as bin packing heuristic. The simulation results show that the proposed method is superior to other tested algorithms in terms of power consumption, resource wastage, CPU usage efficiency and memory usage efficiency.

Optimization on Paddy Crops in Central Java (with Solver, SVD on Least Square and ACO (Ant Colony Algorithm))

NASA Astrophysics Data System (ADS)

Parhusip, H. A.; Trihandaru, S.; Susanto, B.; Prasetyo, S. Y. J.; Agus, Y. H.; Simanjuntak, B. H.

2017-03-01

Several algorithms and objective functions on paddy crops have been studied to get optimal paddy crops in Central Java based on the data given from Surakarta and Boyolali. The algorithms are linear solver, least square and Ant Colony Algorithms (ACO) to develop optimization procedures on paddy crops modelled with Modified GSTAR (Generalized Space-Time Autoregressive) and nonlinear models where the nonlinear models are quadratic and power functions. The studied data contain paddy crops from Surakarta and Boyolali determining the best period of planting in the year 1992-2012 for Surakarta where 3 periods for planting are known and the optimal amount of paddy crops in Boyolali in the year 2008-2013. Having these analyses may guide the local agriculture government to give a decision on rice sustainability in its region. The best period for planting in Surakarta is observed, i.e. the best period is in September-December based on the data 1992-2012 by considering the planting area, the cropping area, and the paddy crops are the most important factors to be taken into account. As a result, we can refer the paddy crops in this best period (about 60.4 thousand tons per year) as the optimal results in 1992-2012 where the used objective function is quadratic. According to the research, the optimal paddy crops in Boyolali about 280 thousand tons per year where the studied factors are the amount of rainfalls, the harvested area and the paddy crops in 2008-2013. In this case, linear and power functions are studied to be the objective functions. Compared to all studied algorithms, the linear solver is still recommended to be an optimization tool for a local agriculture government to predict paddy crops in future.

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

PubMed

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John Bo

2008-10-29

We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024-1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581-590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6 degrees C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, epsilon of 0.21) and an RMSE of 45.1 degrees C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3 degrees C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5 degrees C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors.

An Ant Colony Optimization algorithm for solving the fixed destination multi-depot multiple traveling salesman problem with non-random parameters

NASA Astrophysics Data System (ADS)

Ramadhani, T.; Hertono, G. F.; Handari, B. D.

2017-07-01

The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a single city (depot) will be determined. If there is more than one depot and salesmen start from and return to the same depot, then the problem is called Fixed Destination Multi-depot Multiple Traveling Salesman Problem (MMTSP). In this paper, MMTSP will be solved using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic optimization algorithm which is derived from the behavior of ants in finding the shortest route(s) from the anthill to a form of nourishment. In solving the MMTSP, the algorithm is observed with respect to different chosen cities as depots and non-randomly three parameters of MMTSP: m, K, L, those represents the number of salesmen, the fewest cities that must be visited by a salesman, and the most number of cities that can be visited by a salesman, respectively. The implementation is observed with four dataset from TSPLIB. The results show that the different chosen cities as depots and the three parameters of MMTSP, in which m is the most important parameter, affect the solution.

An Ant Colony Optimization Based Feature Selection for Web Page Classification

PubMed Central

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods. PMID:25136678

The MAGIC-5 CAD for nodule detection in low dose and thin slice lung CTs

NASA Astrophysics Data System (ADS)

Cerello, Piergiorgio; MAGIC-5 Collaboration

2010-11-01

Lung cancer is the leading cause of cancer-related mortality in developed countries. Only 10-15% of all men and women diagnosed with lung cancer live 5 years after the diagnosis. However, the 5-year survival rate for patients diagnosed in the early asymptomatic stage of the disease can reach 70%. Early-stage lung cancers can be diagnosed by detecting non-calcified small pulmonary nodules with computed tomography (CT). Computer-aided detection (CAD) could support radiologists in the analysis of the large amount of noisy images generated in screening programs, where low-dose and thin-slice settings are used. The MAGIC-5 project, funded by the Istituto Nazionale di Fisica Nucleare (INFN, Italy) and Ministero dell'Università e della Ricerca (MUR, Italy), developed a multi-method approach based on three CAD algorithms to be used in parallel with a merging of their results: the Channeler Ant Model (CAM), based on Virtual Ant Colonies, the Dot-Enhancement/Pleura Surface Normals/VBNA (DE-PSN-VBNA), and the Region Growing Volume Plateau (RGVP). Preliminary results show quite good performances, to be improved with the refining of the single algorithm and the added value of the results merging.

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

Testing the museum versus cradle tropical biological diversity hypothesis: phylogeny, diversification, and ancestral biogeographic range evolution of the ants.

PubMed

Moreau, Corrie S; Bell, Charles D

2013-08-01

Ants are one of the most ecologically and numerically dominant group of terrestrial organisms with most species diversity currently found in tropical climates. Several explanations for the disparity of biological diversity in the tropics compared to temperate regions have been proposed including that the tropics may act as a "museum" where older lineages persist through evolutionary time or as a "cradle" where new species continue to be generated. We infer the molecular phylogenetic relationships of 295 ant specimens including members of all 21 extant subfamilies to explore the evolutionary diversification and biogeography of the ants. By constraining the topology and age of the root node while using 45 fossils as minimum constraints, we converge on an age of 139-158 Mya for the modern ants. Further diversification analyses identified 10 periods with a significant change in the tempo of diversification of the ants, although these shifts did not appear to correspond to ancestral biogeographic range shifts. Likelihood-based historical biogeographic reconstructions suggest that the Neotropics were important in early ant diversification (e.g., Cretaceous). This finding coupled with the extremely high-current species diversity suggests that the Neotropics have acted as both a museum and cradle for ant diversity. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Improved multi-objective ant colony optimization algorithm and its application in complex reasoning

NASA Astrophysics Data System (ADS)

Wang, Xinqing; Zhao, Yang; Wang, Dong; Zhu, Huijie; Zhang, Qing

2013-09-01

The problem of fault reasoning has aroused great concern in scientific and engineering fields. However, fault investigation and reasoning of complex system is not a simple reasoning decision-making problem. It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints. So far, little research has been carried out in this field. This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes. Three optimization objectives are considered simultaneously: maximum probability of average fault, maximum average importance, and minimum average complexity of test. Under the constraints of both known symptoms and the causal relationship among different components, a multi-objective optimization mathematical model is set up, taking minimizing cost of fault reasoning as the target function. Since the problem is non-deterministic polynomial-hard(NP-hard), a modified multi-objective ant colony algorithm is proposed, in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives. At last, a Pareto optimal set is acquired. Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set, through which the final fault causes can be identified according to decision-making demands, thus realize fault reasoning of the multi-constraint and multi-objective complex system. Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model, which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.

Skull removal in MR images using a modified artificial bee colony optimization algorithm.

PubMed

Taherdangkoo, Mohammad

2014-01-01

Removal of the skull from brain Magnetic Resonance (MR) images is an important preprocessing step required for other image analysis techniques such as brain tissue segmentation. In this paper, we propose a new algorithm based on the Artificial Bee Colony (ABC) optimization algorithm to remove the skull region from brain MR images. We modify the ABC algorithm using a different strategy for initializing the coordinates of scout bees and their direction of search. Moreover, we impose an additional constraint to the ABC algorithm to avoid the creation of discontinuous regions. We found that our algorithm successfully removed all bony skull from a sample of de-identified MR brain images acquired from different model scanners. The obtained results of the proposed algorithm compared with those of previously introduced well known optimization algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) demonstrate the superior results and computational performance of our algorithm, suggesting its potential for clinical applications.

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

Individual Rules for Trail Pattern Formation in Argentine Ants (Linepithema humile)

PubMed Central

Perna, Andrea; Granovskiy, Boris; Garnier, Simon; Nicolis, Stamatios C.; Labédan, Marjorie; Theraulaz, Guy; Fourcassié, Vincent; Sumpter, David J. T.

2012-01-01

We studied the formation of trail patterns by Argentine ants exploring an empty arena. Using a novel imaging and analysis technique we estimated pheromone concentrations at all spatial positions in the experimental arena and at different times. Then we derived the response function of individual ants to pheromone concentrations by looking at correlations between concentrations and changes in speed or direction of the ants. Ants were found to turn in response to local pheromone concentrations, while their speed was largely unaffected by these concentrations. Ants did not integrate pheromone concentrations over time, with the concentration of pheromone in a 1 cm radius in front of the ant determining the turning angle. The response to pheromone was found to follow a Weber's Law, such that the difference between quantities of pheromone on the two sides of the ant divided by their sum determines the magnitude of the turning angle. This proportional response is in apparent contradiction with the well-established non-linear choice function used in the literature to model the results of binary bridge experiments in ant colonies (Deneubourg et al. 1990). However, agent based simulations implementing the Weber's Law response function led to the formation of trails and reproduced results reported in the literature. We show analytically that a sigmoidal response, analogous to that in the classical Deneubourg model for collective decision making, can be derived from the individual Weber-type response to pheromone concentrations that we have established in our experiments when directional noise around the preferred direction of movement of the ants is assumed. PMID:22829756

Bio-mimic optimization strategies in wireless sensor networks: a survey.

PubMed

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

Agents, assemblers, and ANTS: scheduling assembly with market and biological software mechanisms

NASA Astrophysics Data System (ADS)

Toth-Fejel, Tihamer T.

2000-06-01

Nanoscale assemblers will need robust, scalable, flexible, and well-understood mechanisms such as software agents to control them. This paper discusses assemblers and agents, and proposes a taxonomy of their possible interaction. Molecular assembly is seen as a special case of general assembly, subject to many of the same issues, such as the advantages of convergent assembly, and the problem of scheduling. This paper discusses the contract net architecture of ANTS, an agent-based scheduling application under development. It also describes an algorithm for least commitment scheduling, which uses probabilistic committed capacity profiles of resources over time, along with realistic costs, to provide an abstract search space over which the agents can wander to quickly find optimal solutions.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

NASA Astrophysics Data System (ADS)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

An ultra-low power wireless sensor network for bicycle torque performance measurements.

PubMed

Gharghan, Sadik K; Nordin, Rosdiadee; Ismail, Mahamod

2015-05-21

In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach.

An Ultra-Low Power Wireless Sensor Network for Bicycle Torque Performance Measurements

PubMed Central

Gharghan, Sadik K.; Nordin, Rosdiadee; Ismail, Mahamod

2015-01-01

In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach. PMID:26007728

3D Printer Instrumentation to Create Varied Geometries of Robotic Limbs and Heterogeneous Granular Media

DTIC Science & Technology

2015-05-20

Transfer Robo Ant The 3D printer was used to rapidly prototype a robot ant . The robot ant was used to model the behavior of the fire ant and to model...computer models and 3D printed ant robots are shown below. Snake Bot We used the 3D printed to rapidly design a modular, easily-modified snake...living organism (modern mudskippers, a terrestrial fish) and extinct early tetrapods (e.g. Ichthyostega, Acanthostega) while allowing us to explore

Acanthopria and Mimopriella parasitoid wasps (Diapriidae) attack Cyphomyrmex fungus-growing ants (Formicidae, Attini)

NASA Astrophysics Data System (ADS)

Fernández-Marín, Hermógenes; Zimmerman, Jess K.; Wcislo, William T.

2006-01-01

New World diapriine wasps are abundant and diverse, but the biology of most species is unknown. We provide the first description of the biology of diapriine wasps, Acanthopria spp. and Mimopriella sp., which attack the larvae of Cyphomyrmex fungus-growing ants. In Puerto Rico, the koinobiont parasitoids Acanthopria attack Cyphomyrmex minutus, while in Panama at least four morphospecies of Acanthopria and one of Mimopriella attack Cyphomyrmex rimosus. Of the total larvae per colony, 0 100% were parasitized, and 27 70% of the colonies per population were parasitized. Parasitism rate and colony size were negatively correlated for C. rimosus but not for C. minutus. Worker ants grasped at, bit, and in some cases, killed adult wasps that emerged in artificial nests or tried to enter natural nests. Parasitoid secondary sex ratios were female-biased for eclosing wasps, while field collections showed a male-biased sex ratio. Based on their abundance and success in attacking host ants, these minute wasps present excellent opportunities to explore how natural enemies impact ant colony demography and population biology.

Empirical scoring functions for advanced protein-ligand docking with PLANTS.

PubMed

Korb, Oliver; Stützle, Thomas; Exner, Thomas E

2009-01-01

In this paper we present two empirical scoring functions, PLANTS(CHEMPLP) and PLANTS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). They are related, regarding their functional form, to parts of already published scoring functions and force fields. The parametrization procedure described here was able to identify several parameter settings showing an excellent performance for the task of pose prediction on two test sets comprising 298 complexes in total. Up to 87% of the complexes of the Astex diverse set and 77% of the CCDC/Astex clean listnc (noncovalently bound complexes of the clean list) could be reproduced with root-mean-square deviations of less than 2 A with respect to the experimentally determined structures. A comparison with the state-of-the-art docking tool GOLD clearly shows that this is, especially for the druglike Astex diverse set, an improvement in pose prediction performance. Additionally, optimized parameter settings for the search algorithm were identified, which can be used to balance pose prediction reliability and search speed.

Swarmathon 2017

NASA Image and Video Library

2017-04-19

A sign at the Kennedy Space Center Visitor Complex announces the second annual Swarmathon competition. Students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of cubes with AprilTags, similar to barcodes. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food. In the spaceport's second annual Swarmathon, 20 teams representing 22 minority serving universities and community colleges were invited to develop software code to operate these innovative robots known as "Swarmies" to help find resources when astronauts explore distant locations, such as the moon or Mars.

Exploring whether and how ants affect reproductive fitness in Senna mexicana var. chapmanii

USDA-ARS?s Scientific Manuscript database

Extrafloral nectar (EFN) mediates food-for-protection mutualisms between plants and ants. Ant-plant mutualisms are keystone associations, occurring within a complex web of biotic interactions. As such, these interactions may affect plant fitness in a number of ways, both positive and negative. In S...

Experiences applying Formal Approaches in the Development of Swarm-Based Space Exploration Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher A.; Hinchey, Michael G.; Truszkowski, Walter F.; Rash, James L.

2006-01-01

NASA is researching advanced technologies for future exploration missions using intelligent swarms of robotic vehicles. One of these missions is the Autonomous Nan0 Technology Swarm (ANTS) mission that will explore the asteroid belt using 1,000 cooperative autonomous spacecraft. The emergent properties of intelligent swarms make it a potentially powerful concept, but at the same time more difficult to design and ensure that the proper behaviors will emerge. NASA is investigating formal methods and techniques for verification of such missions. The advantage of using formal methods is the ability to mathematically verify the behavior of a swarm, emergent or otherwise. Using the ANTS mission as a case study, we have evaluated multiple formal methods to determine their effectiveness in modeling and ensuring desired swarm behavior. This paper discusses the results of this evaluation and proposes an integrated formal method for ensuring correct behavior of future NASA intelligent swarms.

Refraction law and Fermat principle: a project using the ant colony optimization algorithm for undergraduate students in physics

NASA Astrophysics Data System (ADS)

Vuong, Q. L.; Rigaut, C.; Gossuin, Y.

2018-07-01

A programming project for undergraduate students in physics is proposed in this work. Its goal is to check the Snell–Descartes law of refraction using the Fermat principle and the ant colony optimization algorithm. The project involves basic mathematics and physics and is adapted to students with basic programming skills. More advanced tools can be used (but are not mandatory) as parallelization or object-oriented programming, which makes the project also suitable for more experienced students. We propose two tests to validate the program. Our algorithm is able to find solutions which are close to the theoretical predictions. Two quantities are defined to study its convergence and the quality of the solutions. It is also shown that the choice of the values of the simulation parameters is important to efficiently obtain precise results.

Predictability and Prediction for an Experimental Cultural Market

NASA Astrophysics Data System (ADS)

Colbaugh, Richard; Glass, Kristin; Ormerod, Paul

Individuals are often influenced by the behavior of others, for instance because they wish to obtain the benefits of coordinated actions or infer otherwise inaccessible information. In such situations this social influence decreases the ex ante predictability of the ensuing social dynamics. We claim that, interestingly, these same social forces can increase the extent to which the outcome of a social process can be predicted very early in the process. This paper explores this claim through a theoretical and empirical analysis of the experimental music market described and analyzed in [1]. We propose a very simple model for this music market, assess the predictability of market outcomes through formal analysis of the model, and use insights derived through this analysis to develop algorithms for predicting market share winners, and their ultimate market shares, in the very early stages of the market. The utility of these predictive algorithms is illustrated through analysis of the experimental music market data sets [2].

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction

PubMed Central

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John BO

2008-01-01

Background We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024–1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581–590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Results Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6°C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, ε of 0.21) and an RMSE of 45.1°C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3°C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5°C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. Conclusion With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors. PMID:18959785

A Survey of Formal Methods for Intelligent Swarms

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Hinchey, Mike; Rouff, Chrustopher A.

2004-01-01

Swarms of intelligent autonomous spacecraft, involving complex behaviors and interactions, are being proposed for future space exploration missions. Such missions provide greater flexibility and offer the possibility of gathering more science data than traditional single spacecraft missions. The emergent properties of swarms make these missions powerful, but simultaneously far more difficult to design, and to assure that the proper behaviors will emerge. These missions are also considerably more complex than previous types of missions, and NASA, like other organizations, has little experience in developing or in verifying and validating these types of missions. A significant challenge when verifying and validating swarms of intelligent interacting agents is how to determine that the possible exponential interactions and emergent behaviors are producing the desired results. Assuring correct behavior and interactions of swarms will be critical to mission success. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm types of missions NASA is considering. The ANTS mission will use a swarm of picospacecraft that will fly from Earth orbit to the Asteroid Belt. Using an insect colony analogy, ANTS will be composed of specialized workers for asteroid exploration. Exploration would consist of cataloguing the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. To perform this task, ANTS would carry miniaturized instruments, such as imagers, spectrometers, and detectors. Since ANTS and other similar missions are going to consist of autonomous spacecraft that may be out of contact with the earth for extended periods of time, and have low bandwidths due to weight constraints, it will be difficult to observe improper behavior and to correct any errors after launch. Providing V&V (verification and validation) for this type of mission is new to NASA, and represents the cutting edge in system correctness, and requires higher levels of assurance than other (traditional) missions that use a single or small number of spacecraft that are deterministic in nature and have near continuous communication access. One of the highest possible levels of assurance comes from the application of formal methods. Formal methods are mathematics-based tools and techniques for specifying and verifying (software and hardware) systems. They are particularly useful for specifying complex parallel systems, such as exemplified by the ANTS mission, where the entire system is difficult for a single person to fully understand, a problem that is multiplied with multiple developers. Once written, a formal specification can be used to prove properties of a system (e.g., the underlying system will go from one state to another or not into a specific state) and check for particular types of errors (e.g., race or livelock conditions). A formal specification can also be used as input to a model checker for further validation. This report gives the results of a survey of formal methods techniques for verification and validation of space missions that use swarm technology. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft using the ANTS mission as an example system. This report is the first result of the project to determine formal approaches that are promising for formally specifying swarm-based systems. From this survey, the most promising approaches were selected and are discussed relative to their possible application to the ANTS mission. Future work will include the application of an integrated approach, based on the selected approaches identified in this report, to the formal specification of the ANTS mission.

DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maiden, Wendy M.

Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and stillmore » serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.« less

Brain tissue segmentation in MR images based on a hybrid of MRF and social algorithms.

PubMed

Yousefi, Sahar; Azmi, Reza; Zahedi, Morteza

2012-05-01

Effective abnormality detection and diagnosis in Magnetic Resonance Images (MRIs) requires a robust segmentation strategy. Since manual segmentation is a time-consuming task which engages valuable human resources, automatic MRI segmentations received an enormous amount of attention. For this goal, various techniques have been applied. However, Markov Random Field (MRF) based algorithms have produced reasonable results in noisy images compared to other methods. MRF seeks a label field which minimizes an energy function. The traditional minimization method, simulated annealing (SA), uses Monte Carlo simulation to access the minimum solution with heavy computation burden. For this reason, MRFs are rarely used in real time processing environments. This paper proposed a novel method based on MRF and a hybrid of social algorithms that contain an ant colony optimization (ACO) and a Gossiping algorithm which can be used for segmenting single and multispectral MRIs in real time environments. Combining ACO with the Gossiping algorithm helps find the better path using neighborhood information. Therefore, this interaction causes the algorithm to converge to an optimum solution faster. Several experiments on phantom and real images were performed. Results indicate that the proposed algorithm outperforms the traditional MRF and hybrid of MRF-ACO in speed and accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

An open source multivariate framework for n-tissue segmentation with evaluation on public data.

PubMed

Avants, Brian B; Tustison, Nicholas J; Wu, Jue; Cook, Philip A; Gee, James C

2011-12-01

We introduce Atropos, an ITK-based multivariate n-class open source segmentation algorithm distributed with ANTs ( http://www.picsl.upenn.edu/ANTs). The Bayesian formulation of the segmentation problem is solved using the Expectation Maximization (EM) algorithm with the modeling of the class intensities based on either parametric or non-parametric finite mixtures. Atropos is capable of incorporating spatial prior probability maps (sparse), prior label maps and/or Markov Random Field (MRF) modeling. Atropos has also been efficiently implemented to handle large quantities of possible labelings (in the experimental section, we use up to 69 classes) with a minimal memory footprint. This work describes the technical and implementation aspects of Atropos and evaluates its performance on two different ground-truth datasets. First, we use the BrainWeb dataset from Montreal Neurological Institute to evaluate three-tissue segmentation performance via (1) K-means segmentation without use of template data; (2) MRF segmentation with initialization by prior probability maps derived from a group template; (3) Prior-based segmentation with use of spatial prior probability maps derived from a group template. We also evaluate Atropos performance by using spatial priors to drive a 69-class EM segmentation problem derived from the Hammers atlas from University College London. These evaluation studies, combined with illustrative examples that exercise Atropos options, demonstrate both performance and wide applicability of this new platform-independent open source segmentation tool.

An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data

PubMed Central

Tustison, Nicholas J.; Wu, Jue; Cook, Philip A.; Gee, James C.

2012-01-01

We introduce Atropos, an ITK-based multivariate n-class open source segmentation algorithm distributed with ANTs (http://www.picsl.upenn.edu/ANTs). The Bayesian formulation of the segmentation problem is solved using the Expectation Maximization (EM) algorithm with the modeling of the class intensities based on either parametric or non-parametric finite mixtures. Atropos is capable of incorporating spatial prior probability maps (sparse), prior label maps and/or Markov Random Field (MRF) modeling. Atropos has also been efficiently implemented to handle large quantities of possible labelings (in the experimental section, we use up to 69 classes) with a minimal memory footprint. This work describes the technical and implementation aspects of Atropos and evaluates its performance on two different ground-truth datasets. First, we use the BrainWeb dataset from Montreal Neurological Institute to evaluate three-tissue segmentation performance via (1) K-means segmentation without use of template data; (2) MRF segmentation with initialization by prior probability maps derived from a group template; (3) Prior-based segmentation with use of spatial prior probability maps derived from a group template. We also evaluate Atropos performance by using spatial priors to drive a 69-class EM segmentation problem derived from the Hammers atlas from University College London. These evaluation studies, combined with illustrative examples that exercise Atropos options, demonstrate both performance and wide applicability of this new platform-independent open source segmentation tool. PMID:21373993

Asteroid Exploration with Autonomic Systems

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Rouff, Christopher; Hinchey, Mike

2004-01-01

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. The prospective ANTS (Autonomous Nano Technology Swarm) mission comprises autonomous agents including worker agents (small spacecra3) designed to cooperate in asteroid exploration under the overall authoriq of at least one ruler agent (a larger spacecraft) whose goal is to cause science data to be returned to Earth. The ANTS team (ruler plus workers and messenger agents), but not necessarily any individual on the team, will exhibit behaviors that qualify it as an autonomic system, where an autonomic system is defined as a system that self-reconfigures, self-optimizes, self-heals, and self-protects. Autonomic system concepts lead naturally to realistic, scalable architectures rich in capabilities and behaviors. In-depth consideration of a major mission like ANTS in terms of autonomic systems brings new insights into alternative definitions of autonomic behavior. This paper gives an overview of the ANTS mission and discusses the autonomic properties of the mission.

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

PubMed

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

PubMed Central

Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2014-01-01

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

Image Edge Tracking via Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Li, Ruowei; Wu, Hongkun; Liu, Shilong; Rahman, M. A.; Liu, Sanchi; Kwok, Ngai Ming

2018-04-01

A good edge plot should use continuous thin lines to describe the complete contour of the captured object. However, the detection of weak edges is a challenging task because of the associated low pixel intensities. Ant Colony Optimization (ACO) has been employed by many researchers to address this problem. The algorithm is a meta-heuristic method developed by mimicking the natural behaviour of ants. It uses iterative searches to find the optimal solution that cannot be found via traditional optimization approaches. In this work, ACO is employed to track and repair broken edges obtained via conventional Sobel edge detector to produced a result with more connected edges.

Scope of Various Random Number Generators in ant System Approach for TSP

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam Ali

2007-01-01

Experimented on heuristic, based on an ant system approach for traveling salesman problem, are several quasi- and pseudo-random number generators. This experiment is to explore if any particular generator is most desirable. Such an experiment on large samples has the potential to rank the performance of the generators for the foregoing heuristic. This is mainly to seek an answer to the controversial issue "which generator is the best in terms of quality of the result (accuracy) as well as cost of producing the result (time/computational complexity) in a probabilistic/statistical sense."

Swarmathon 2018

NASA Image and Video Library

2018-04-17

Students from Montgomery College in Rockville in Maryland, follow the progress of their Swarmie robots during the Swarmathon competition at the Kennedy Space Center Visitor Complex. Students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of AprilTag cubes, similar to barcodes. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food. In the spaceport's third annual Swarmathon, 23 teams represented 24 minority serving universities and community colleges were invited to develop software code to operate these innovative robots known as "Swarmies" to help find resources when astronauts explore distant locations, such as the Moon or Mars.

Swarmathon 2018

NASA Image and Video Library

2018-04-18

In the Swarmathon competition at the Kennedy Space Center Visitor Complex, students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of AprilTag cubes, similar to barcodes. To add to the challenge, obstacles in the form of simulated rocks were placed in the completion arena. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food. In the spaceport's third annual Swarmathon, 23 teams represented 24 minority serving universities and community colleges were invited to develop software code to operate these innovative robots known as "Swarmies" to help find resources when astronauts explore distant locations, such as the Moon or Mars.

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

PubMed

Granger, Brian R; Chang, Yi-Chien; Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-04-01

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

A solution quality assessment method for swarm intelligence optimization algorithms.

PubMed

Zhang, Zhaojun; Wang, Gai-Ge; Zou, Kuansheng; Zhang, Jianhua

2014-01-01

Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. It greatly limits the application in practical problems. A solution quality assessment method for intelligent optimization is proposed in this paper. It is an experimental analysis method based on the analysis of search space and characteristic of algorithm itself. Instead of "value performance," the "ordinal performance" is used as evaluation criteria in this method. The feasible solutions were clustered according to distance to divide solution samples into several parts. Then, solution space and "good enough" set can be decomposed based on the clustering results. Last, using relative knowledge of statistics, the evaluation result can be got. To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO), particle swarm optimization (PSO), and artificial fish swarm algorithm (AFS) were taken to solve traveling salesman problem. Computational results indicate the feasibility of proposed method.

A Modified Mean Gray Wolf Optimization Approach for Benchmark and Biomedical Problems.

PubMed

Singh, Narinder; Singh, S B

2017-01-01

A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant. The results obtained are compared with many other meta-heuristic approaches, ie, gray wolf optimization, particle swarm optimization, population-based incremental learning, ant colony optimization, etc. The results show that the performance of modified variant is able to find best solutions in terms of high level of accuracy in classification and improved local optima avoidance.

Record Dynamics in Ants

PubMed Central

Richardson, Thomas O.; Robinson, Elva J. H.; Christensen, Kim; Jensen, Henrik J.; Franks, Nigel R.; Sendova-Franks, Ana B.

2010-01-01

The success of social animals (including ourselves) can be attributed to efficiencies that arise from a division of labour. Many animal societies have a communal nest which certain individuals must leave to perform external tasks, for example foraging or patrolling. Staying at home to care for young or leaving to find food is one of the most fundamental divisions of labour. It is also often a choice between safety and danger. Here we explore the regulation of departures from ant nests. We consider the extreme situation in which no one returns and show experimentally that exiting decisions seem to be governed by fluctuating record signals and ant-ant interactions. A record signal is a new ‘high water mark’ in the history of a system. An ant exiting the nest only when the record signal reaches a level it has never perceived before could be a very effective mechanism to postpone, until the last possible moment, a potentially fatal decision. We also show that record dynamics may be involved in first exits by individually tagged ants even when their nest mates are allowed to re-enter the nest. So record dynamics may play a role in allocating individuals to tasks, both in emergencies and in everyday life. The dynamics of several complex but purely physical systems are also based on record signals but this is the first time they have been experimentally shown in a biological system. PMID:20300174

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

NASA Astrophysics Data System (ADS)

Luo, Yabo; Waden, Yongo P.

2017-06-01

Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

Power plant maintenance scheduling using ant colony optimization: an improved formulation

NASA Astrophysics Data System (ADS)

Foong, Wai Kuan; Maier, Holger; Simpson, Angus

2008-04-01

It is common practice in the hydropower industry to either shorten the maintenance duration or to postpone maintenance tasks in a hydropower system when there is expected unserved energy based on current water storage levels and forecast storage inflows. It is therefore essential that a maintenance scheduling optimizer can incorporate the options of shortening the maintenance duration and/or deferring maintenance tasks in the search for practical maintenance schedules. In this article, an improved ant colony optimization-power plant maintenance scheduling optimization (ACO-PPMSO) formulation that considers such options in the optimization process is introduced. As a result, both the optimum commencement time and the optimum outage duration are determined for each of the maintenance tasks that need to be scheduled. In addition, a local search strategy is presented in this article to boost the robustness of the algorithm. When tested on a five-station hydropower system problem, the improved formulation is shown to be capable of allowing shortening of maintenance duration in the event of expected demand shortfalls. In addition, the new local search strategy is also shown to have significantly improved the optimization ability of the ACO-PPMSO algorithm.

Integrating geological uncertainty in long-term open pit mine production planning by ant colony optimization

NASA Astrophysics Data System (ADS)

Gilani, Seyed-Omid; Sattarvand, Javad

2016-02-01

Meeting production targets in terms of ore quantity and quality is critical for a successful mining operation. In-situ grade uncertainty causes both deviations from production targets and general financial deficits. A new stochastic optimization algorithm based on ant colony optimization (ACO) approach is developed herein to integrate geological uncertainty described through a series of the simulated ore bodies. Two different strategies were developed based on a single predefined probability value (Prob) and multiple probability values (Pro bnt) , respectively in order to improve the initial solutions that created by deterministic ACO procedure. Application at the Sungun copper mine in the northwest of Iran demonstrate the abilities of the stochastic approach to create a single schedule and control the risk of deviating from production targets over time and also increase the project value. A comparison between two strategies and traditional approach illustrates that the multiple probability strategy is able to produce better schedules, however, the single predefined probability is more practical in projects requiring of high flexibility degree.

The dynamics of ant mosaics in tropical rainforests characterized using the Self-Organizing Map algorithm.

PubMed

Dejean, Alain; Azémar, Frédéric; Céréghino, Régis; Leponce, Maurice; Corbara, Bruno; Orivel, Jérôme; Compin, Arthur

2016-08-01

Ants, the most abundant taxa among canopy-dwelling animals in tropical rainforests, are mostly represented by territorially dominant arboreal ants (TDAs) whose territories are distributed in a mosaic pattern (arboreal ant mosaics). Large TDA colonies regulate insect herbivores, with implications for forestry and agronomy. What generates these mosaics in vegetal formations, which are dynamic, still needs to be better understood. So, from empirical research based on 3 Cameroonian tree species (Lophira alata, Ochnaceae; Anthocleista vogelii, Gentianaceae; and Barteria fistulosa, Passifloraceae), we used the Self-Organizing Map (SOM, neural network) to illustrate the succession of TDAs as their host trees grow and age. The SOM separated the trees by species and by size for L. alata, which can reach 60 m in height and live several centuries. An ontogenic succession of TDAs from sapling to mature trees is shown, and some ecological traits are highlighted for certain TDAs. Also, because the SOM permits the analysis of data with many zeroes with no effect of outliers on the overall scatterplot distributions, we obtained ecological information on rare species. Finally, the SOM permitted us to show that functional groups cannot be selected at the genus level as congeneric species can have very different ecological niches, something particularly true for Crematogaster spp., which include a species specifically associated with B. fistulosa, nondominant species and TDAs. Therefore, the SOM permitted the complex relationships between TDAs and their growing host trees to be analyzed, while also providing new information on the ecological traits of the ant species involved. © 2015 Institute of Zoology, Chinese Academy of Sciences.

Spatial-Temporal Reasoning Applications of Computational Intelligence in the Game of Go and Computer Networks

DTIC Science & Technology

2012-01-01

dimensionality, Tesauro used a backpropagation- based , three-layer neural network and implemented the outcome from a self-play game as the reinforcement signal...a school of fish, flock of birds, and colony of ants. Our literature review reveals that no one has used PSO to train the neural network ...trained with a variant of PSO called cellular PSO (CPSO). CSRN is a supervised learning neural network (SLNN). The proposed algorithm for the

Gene selection for cancer classification with the help of bees.

PubMed

Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

2016-08-10

Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

DOE PAGES

Granger, Brian R.; Chang, Yi -Chien; Wang, Yan; ...

2016-04-15

Here, the complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique meta-graph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction networkmore » between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.« less

Ant-like task allocation and recruitment in cooperative robots

NASA Astrophysics Data System (ADS)

Krieger, Michael J. B.; Billeter, Jean-Bernard; Keller, Laurent

2000-08-01

One of the greatest challenges in robotics is to create machines that are able to interact with unpredictable environments in real time. A possible solution may be to use swarms of robots behaving in a self-organized manner, similar to workers in an ant colony. Efficient mechanisms of division of labour, in particular series-parallel operation and transfer of information among group members, are key components of the tremendous ecological success of ants. Here we show that the general principles regulating division of labour in ant colonies indeed allow the design of flexible, robust and effective robotic systems. Groups of robots using ant-inspired algorithms of decentralized control techniques foraged more efficiently and maintained higher levels of group energy than single robots. But the benefits of group living decreased in larger groups, most probably because of interference during foraging. Intriguingly, a similar relationship between group size and efficiency has been documented in social insects. Moreover, when food items were clustered, groups where robots could recruit other robots in an ant-like manner were more efficient than groups without information transfer, suggesting that group dynamics of swarms of robots may follow rules similar to those governing social insects.

Optimizing Robinson Operator with Ant Colony Optimization As a Digital Image Edge Detection Method

NASA Astrophysics Data System (ADS)

Yanti Nasution, Tarida; Zarlis, Muhammad; K. M Nasution, Mahyuddin

2017-12-01

Edge detection serves to identify the boundaries of an object against a background of mutual overlap. One of the classic method for edge detection is operator Robinson. Operator Robinson produces a thin, not assertive and grey line edge. To overcome these deficiencies, the proposed improvements to edge detection method with the approach graph with Ant Colony Optimization algorithm. The repairs may be performed are thicken the edge and connect the edges cut off. Edge detection research aims to do optimization of operator Robinson with Ant Colony Optimization then compare the output and generated the inferred extent of Ant Colony Optimization can improve result of edge detection that has not been optimized and improve the accuracy of the results of Robinson edge detection. The parameters used in performance measurement of edge detection are morphology of the resulting edge line, MSE and PSNR. The result showed that Robinson and Ant Colony Optimization method produces images with a more assertive and thick edge. Ant Colony Optimization method is able to be used as a method for optimizing operator Robinson by improving the image result of Robinson detection average 16.77 % than classic Robinson result.

Discovering the knowledge creation process of an expert group in women-friendly policy: The policy case of Seoul City.

PubMed

Oh, Young Sam; Nam, SungHee; Kim, Yuna

2016-01-01

This research explores how expert knowledge is created in the process of women-friendly policy making, based on actor network theory (ANT). To address this purpose, this study uses the "Women's Happiness in the City of Seoul" policy initiated by the local government of Seoul as one example of policy development. Research findings demonstrate that knowledge creation in expert groups followed the four stages suggested by ANT. In addition, this study found that various types of knowledge emerged from individual experts. This research elucidates the process of knowledge creation and its meanings for women-friendly policy.

Multi-objective ACO algorithms to minimise the makespan and the total rejection cost on BPMs with arbitrary job weights

NASA Astrophysics Data System (ADS)

Jia, Zhao-hong; Pei, Ming-li; Leung, Joseph Y.-T.

2017-12-01

In this paper, we investigate the batch-scheduling problem with rejection on parallel machines with non-identical job sizes and arbitrary job-rejected weights. If a job is rejected, the corresponding penalty has to be paid. Our objective is to minimise the makespan of the processed jobs and the total rejection cost of the rejected jobs. Based on the selected multi-objective optimisation approaches, two problems, P1 and P2, are considered. In P1, the two objectives are linearly combined into one single objective. In P2, the two objectives are simultaneously minimised and the Pareto non-dominated solution set is to be found. Based on the ant colony optimisation (ACO), two algorithms, called LACO and PACO, are proposed to address the two problems, respectively. Two different objective-oriented pheromone matrices and heuristic information are designed. Additionally, a local optimisation algorithm is adopted to improve the solution quality. Finally, simulated experiments are conducted, and the comparative results verify the effectiveness and efficiency of the proposed algorithms, especially on large-scale instances.

Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model

NASA Astrophysics Data System (ADS)

Deng, Guang-Feng; Lin, Woo-Tsong

This work presents Ant Colony Optimization (ACO), which was initially developed to be a meta-heuristic for combinatorial optimization, for solving the cardinality constraints Markowitz mean-variance portfolio model (nonlinear mixed quadratic programming problem). To our knowledge, an efficient algorithmic solution for this problem has not been proposed until now. Using heuristic algorithms in this case is imperative. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the ACO is much more robust and effective than Particle swarm optimization (PSO), especially for low-risk investment portfolios.

3D sensor placement strategy using the full-range pheromone ant colony system

NASA Astrophysics Data System (ADS)

Shuo, Feng; Jingqing, Jia

2016-07-01

An optimized sensor placement strategy will be extremely beneficial to ensure the safety and cost reduction considerations of structural health monitoring (SHM) systems. The sensors must be placed such that important dynamic information is obtained and the number of sensors is minimized. The practice is to select individual sensor directions by several 1D sensor methods and the triaxial sensors are placed in these directions for monitoring. However, this may lead to non-optimal placement of many triaxial sensors. In this paper, a new method, called FRPACS, is proposed based on the ant colony system (ACS) to solve the optimal placement of triaxial sensors. The triaxial sensors are placed as single units in an optimal fashion. And then the new method is compared with other algorithms using Dalian North Bridge. The computational precision and iteration efficiency of the FRPACS has been greatly improved compared with the original ACS and EFI method.

ANTS: Exploring the Solar System with an Autonomous Nanotechnology Swarm

NASA Technical Reports Server (NTRS)

Clark, P. E.; Curtis, S.; Rilee, M.; Truszkowski, W.; Marr, G.

2002-01-01

ANTS (Autonomous Nano-Technology Swarm), a NASA advanced mission concept, calls for a large (1000 member) swarm of pico-class (1 kg) totally autonomous spacecraft to prospect the asteroid belt. Additional information is contained in the original extended abstract.

Pericarpial nectary-visiting ants do not provide fruit protection against pre-dispersal seed predators regardless of ant species composition and resource availability

PubMed Central

Ré Jorge, Leonardo; Benitez-Vieyra, Santiago; Amorim, Felipe W.

2017-01-01

Extrafloral nectaries can occur in both vegetative and reproductive plant structures. In many Rubiaceae species in the Brazilian Cerrado, after corolla abscission, the floral nectary continues to secret nectar throughout fruit development originating post-floral pericarpial nectaries which commonly attract many ant species. The occurrence of such nectar secreting structures might be strategic for fruit protection against seed predators, as plants are expected to invest higher on more valuable and vulnerable parts. Here, we performed ant exclusion experiments to investigate whether the interaction with ants mediated by the pericarpial nectaries of Tocoyena formosa affects plant reproductive success by reducing the number of pre-dispersal seed predators. We also assessed whether ant protection was dependent on ant species composition and resource availability. Although most of the plants were visited by large and aggressive ant species, such as Ectatomma tuberculatum and species of the genus Camponotus, ants did not protect fruits against seed predators. Furthermore, the result of the interaction was neither related to ant species composition nor to the availability of resources. We suggest that these results may be related to the nature and behavior of the most important seed predators, like Hemicolpus abdominalis weevil which the exoskeleton toughness prevent it from being predated by most ant species. On the other hand, not explored factors, such as reward quality, local ant abundance, ant colony characteristics and/or the presence of alternative energetic sources could also account for variations in ant frequency, composition, and finally ant protective effects, highlighting the conditionality of facultative plant-ant mutualisms. PMID:29211790

ANTS/PAM: Future Exploration of the Asteroid Belt

NASA Astrophysics Data System (ADS)

Clark, P. E.; Curtis, S. A.; Rilee, M. L.; Cheung, C. Y.

2004-05-01

The Autonomous Nano-Technology Swarm (ANTS) is applied to the Prospecting Asteroid Mission (PAM) concept, as part of a NASA RASC study. The ANTS architecture is inspired by success of social insect colonies, based on the division of labor within the colonies: 1) within their specialties, individual specialists generally outperform general-ists, and 2) with sufficiently efficient social interaction and coordination, the group of specialists generally outper-forms the group of generalists. ANTS as applied to PAM involves a thousand individual specialist `sciencecraft', one subswarm per target, in an environment where detection and tracking of irregular, infrequent targets is a major chal-lenge. Workers, carry and operate eight to nine different scientific instruments, including spectrometers, ranging and radio science devices, imagers. The remaining specialists, Messenger/Rulers, provide communication and coordina-tion. The non-expendable propulsion system is based on autonomously deployable and configurable solar sails, a system suitable to a low gravity environment. The design of the neural basis function requires a minimum of 4 or 5 specialists for collective decision making. Allowing for ten instrument specialist teams and compensating for antici-pated high attrition, we calculate an initial minimum of 100 per subswarm should allow characterization of hundreds of asteroids. The difficulty in observing irregular, rapidly moving, poorly illuminated objects is largely overcome by the ANT sciencecraft capability to optimize conditions for each instrument. Components are composed of carbon nanotubules reversibly deployable from NEMS nodes, allowing 100 times decrease in packaging volume. 1000 smart 10 centimeter, 1 kg cubic boxes create a 1000 kg 1 meter cube.

Cuticular hydrocarbons correlate with queen reproductive status in native and invasive Argentine ants (Linepithema humile, Mayr).

PubMed

Abril, Sílvia; Diaz, Mireia; Lenoir, Alain; Ivon Paris, Carolina; Boulay, Raphaël; Gómez, Crisanto

2018-01-01

In insect societies, chemical communication plays an important role in colony reproduction and individual social status. Many studies have indicated that cuticular hydrocarbons (CHCs) are the main chemical compounds encoding reproductive status. However, these studies have largely focused on queenless or monogynous species whose workers are capable of egg laying and have mainly explored the mechanisms underlying queen-worker or worker-worker reproductive conflicts. Less is known about what occurs in highly polygynous ant species with permanently sterile workers. Here, we used the Argentine ant as a model to examine the role of CHCs in communicating reproductive information in such insect societies. The Argentine ant is unicolonial, highly polygynous, and polydomous. We identified several CHCs whose presence and levels were correlated with queen age, reproductive status, and fertility. Our results also provide new insights into queen executions in the Argentine ant, a distinctive feature displayed by this species in its introduced range. Each spring, just before new sexuals appear, workers eliminate up to 90% of the mated queens in their colonies. We discovered that queens that survived execution had different CHC profiles from queens present before and during execution. More specifically, levels of some CHCs were higher in the survivors, suggesting that workers could eliminate queens based on their chemical profiles. In addition, queen CHC profiles differed based on season and species range (native vs. introduced). Overall, the results of this study provide new evidence that CHCs serve as queen signals and do more than just regulate worker reproduction.

Cuticular hydrocarbons correlate with queen reproductive status in native and invasive Argentine ants (Linepithema humile, Mayr)

PubMed Central

Diaz, Mireia; Lenoir, Alain; Ivon Paris, Carolina; Boulay, Raphaël; Gómez, Crisanto

2018-01-01

In insect societies, chemical communication plays an important role in colony reproduction and individual social status. Many studies have indicated that cuticular hydrocarbons (CHCs) are the main chemical compounds encoding reproductive status. However, these studies have largely focused on queenless or monogynous species whose workers are capable of egg laying and have mainly explored the mechanisms underlying queen-worker or worker-worker reproductive conflicts. Less is known about what occurs in highly polygynous ant species with permanently sterile workers. Here, we used the Argentine ant as a model to examine the role of CHCs in communicating reproductive information in such insect societies. The Argentine ant is unicolonial, highly polygynous, and polydomous. We identified several CHCs whose presence and levels were correlated with queen age, reproductive status, and fertility. Our results also provide new insights into queen executions in the Argentine ant, a distinctive feature displayed by this species in its introduced range. Each spring, just before new sexuals appear, workers eliminate up to 90% of the mated queens in their colonies. We discovered that queens that survived execution had different CHC profiles from queens present before and during execution. More specifically, levels of some CHCs were higher in the survivors, suggesting that workers could eliminate queens based on their chemical profiles. In addition, queen CHC profiles differed based on season and species range (native vs. introduced). Overall, the results of this study provide new evidence that CHCs serve as queen signals and do more than just regulate worker reproduction. PMID:29470506

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0

PubMed Central

Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-01-01

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT’s unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the “symbiotic layout” of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu. PMID:27081850

Biomechanical simulations of costo-vertebral and anterior vertebral body tethers for the fusionless treatment of pediatric scoliosis.

PubMed

Aubin, Carl-Éric; Clin, Julien; Rawlinson, Jeremy

2018-01-01

Compression-based fusionless tethers are an alternative to conventional surgical treatments of pediatric scoliosis. Anterior approaches place an anterior (ANT) tether on the anterolateral convexity of the deformed spine to modify growth. Posterior, or costo-vertebral (CV), approaches have not been assessed for biomechanical and corrective effectiveness. The objective was to biomechanically assess CV and ANT tethers using six patient-specific, finite element models of adolescent scoliotic patients (11.9 ± 0.7 years, Cobb 34° ± 10°). A validated algorithm simulated the growth and Hueter-Volkmann growth modulation over a period of 2 years with the CV and ANT tethers at two initial tensions (100, 200 N). The models without tethering also simulated deformity progression with Cobb angle increasing from 34° to 56°, axial rotation 11° to 13°, and kyphosis 28° to 32° (mean values). With the CV tether, the Cobb angle was reduced to 27° and 20° for tensions of 100 and 200 N, respectively, kyphosis to 21° and 19°, and no change in axial rotation. With the ANT tether, Cobb was reduced to 32° and 9° for 100 and 200 N, respectively, kyphosis unchanged, and axial rotation to 3° and 0°. While the CV tether mildly corrected the coronal curve over a 2-year growth period, it had sagittal lordosing effect, particularly with increasing initial axial rotation (>15°). The ANT tether achieved coronal correction, maintained kyphosis, and reduced the axial rotation, but over-correction was simulated at higher initial tensions. This biomechanical study captured the differences between a CV and ANT tether and indicated the variability arising from the patient-specific characteristics. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:254-264, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

PubMed

Li, Xuejun; Xu, Jia; Yang, Yun

2015-01-01

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems

PubMed Central

Li, Xuejun; Xu, Jia; Yang, Yun

2015-01-01

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts. PMID:26357510

Ant colony optimisation inversion of surface and borehole magnetic data under lithological constraints

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Liu, Tianyou; Xi, Yufei; Cai, Jianchao; Zhang, Henglei

2015-01-01

The ant colony optimisation algorithm has successfully been used to invert for surface magnetic data. However, the resolution of the distributions of the recovered physical property for deeply buried magnetic sources is not generally very high because of geophysical ambiguities. We use three approaches to deal with this problem. First, the observed surface magnetic data are taken together with the three-component borehole magnetic anomalies to recover the distributions of the physical properties. This cooperative inversion strategy improves the resolution of the inversion results in the vertical direction. Additionally, as the ant colony tours the discrete nodes, we force it to visit the nodes with physical properties that agree with the drilled lithologies. These lithological constraints reduce the non-uniqueness of the inversion problem. Finally, we also implement a K-means cluster analysis for the distributions of the magnetic cells after each iteration, in order to separate the distributions of magnetisation intensity instead of concentrating the distribution in a single area. We tested our method using synthetic data and found that all tests returned favourable results. In the case study of the Mengku iron-ore deposit in northwest China, the recovered distributions of magnetisation are in good agreement with the locations and shapes of the magnetite orebodies as inferred by drillholes. Uncertainty analysis shows that the ant colony algorithm is robust in the presence of noise and that the proposed approaches significantly improve the quality of the inversion results.

Ant Navigation: Fractional Use of the Home Vector

PubMed Central

Cheung, Allen; Hiby, Lex; Narendra, Ajay

2012-01-01

Home is a special location for many animals, offering shelter from the elements, protection from predation, and a common place for gathering of the same species. Not surprisingly, many species have evolved efficient, robust homing strategies, which are used as part of each and every foraging journey. A basic strategy used by most animals is to take the shortest possible route home by accruing the net distances and directions travelled during foraging, a strategy well known as path integration. This strategy is part of the navigation toolbox of ants occupying different landscapes. However, when there is a visual discrepancy between test and training conditions, the distance travelled by animals relying on the path integrator varies dramatically between species: from 90% of the home vector to an absolute distance of only 50 cm. We here ask what the theoretically optimal balance between PI-driven and landmark-driven navigation should be. In combination with well-established results from optimal search theory, we show analytically that this fractional use of the home vector is an optimal homing strategy under a variety of circumstances. Assuming there is a familiar route that an ant recognizes, theoretically optimal search should always begin at some fraction of the home vector, depending on the region of familiarity. These results are shown to be largely independent of the search algorithm used. Ant species from different habitats appear to have optimized their navigation strategy based on the availability and nature of navigational information content in their environment. PMID:23209744

Optimal management of substrates in anaerobic co-digestion: An ant colony algorithm approach.

PubMed

Verdaguer, Marta; Molinos-Senante, María; Poch, Manel

2016-04-01

Sewage sludge (SWS) is inevitably produced in urban wastewater treatment plants (WWTPs). The treatment of SWS on site at small WWTPs is not economical; therefore, the SWS is typically transported to an alternative SWS treatment center. There is increased interest in the use of anaerobic digestion (AnD) with co-digestion as an SWS treatment alternative. Although the availability of different co-substrates has been ignored in most of the previous studies, it is an essential issue for the optimization of AnD co-digestion. In a pioneering approach, this paper applies an Ant-Colony-Optimization (ACO) algorithm that maximizes the generation of biogas through AnD co-digestion in order to optimize the discharge of organic waste from different waste sources in real-time. An empirical application is developed based on a virtual case study that involves organic waste from urban WWTPs and agrifood activities. The results illustrate the dominate role of toxicity levels in selecting contributions to the AnD input. The methodology and case study proposed in this paper demonstrate the usefulness of the ACO approach in supporting a decision process that contributes to improving the sustainability of organic waste and SWS management. Copyright © 2016 Elsevier Ltd. All rights reserved.

PSO/ACO algorithm-based risk assessment of human neural tube defects in Heshun County, China.

PubMed

Liao, Yi Lan; Wang, Jin Feng; Wu, Ji Lei; Wang, Jiao Jiao; Zheng, Xiao Ying

2012-10-01

To develop a new technique for assessing the risk of birth defects, which are a major cause of infant mortality and disability in many parts of the world. The region of interest in this study was Heshun County, the county in China with the highest rate of neural tube defects (NTDs). A hybrid particle swarm optimization/ant colony optimization (PSO/ACO) algorithm was used to quantify the probability of NTDs occurring at villages with no births. The hybrid PSO/ACO algorithm is a form of artificial intelligence adapted for hierarchical classification. It is a powerful technique for modeling complex problems involving impacts of causes. The algorithm was easy to apply, with the accuracy of the results being 69.5%±7.02% at the 95% confidence level. The proposed method is simple to apply, has acceptable fault tolerance, and greatly enhances the accuracy of calculations. Copyright © 2012 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.

PubMed

Rani, R Ranjani; Ramyachitra, D

2016-12-01

Multiple sequence alignment (MSA) is a widespread approach in computational biology and bioinformatics. MSA deals with how the sequences of nucleotides and amino acids are sequenced with possible alignment and minimum number of gaps between them, which directs to the functional, evolutionary and structural relationships among the sequences. Still the computation of MSA is a challenging task to provide an efficient accuracy and statistically significant results of alignments. In this work, the Bacterial Foraging Optimization Algorithm was employed to align the biological sequences which resulted in a non-dominated optimal solution. It employs Multi-objective, such as: Maximization of Similarity, Non-gap percentage, Conserved blocks and Minimization of gap penalty. BAliBASE 3.0 benchmark database was utilized to examine the proposed algorithm against other methods In this paper, two algorithms have been proposed: Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC) and Bacterial Foraging Optimization Algorithm. It was found that Hybrid Genetic Algorithm with Artificial Bee Colony performed better than the existing optimization algorithms. But still the conserved blocks were not obtained using GA-ABC. Then BFO was used for the alignment and the conserved blocks were obtained. The proposed Multi-Objective Bacterial Foraging Optimization Algorithm (MO-BFO) was compared with widely used MSA methods Clustal Omega, Kalign, MUSCLE, MAFFT, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC). The final results show that the proposed MO-BFO algorithm yields better alignment than most widely used methods. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives

NASA Astrophysics Data System (ADS)

Oesterle, Jonathan; Lionel, Amodeo

2018-06-01

The current competitive situation increases the importance of realistically estimating product costs during the early phases of product and assembly line planning projects. In this article, several multi-objective algorithms using difference dominance rules are proposed to solve the problem associated with the selection of the most effective combination of product and assembly lines. The list of developed algorithms includes variants of ant colony algorithms, evolutionary algorithms and imperialist competitive algorithms. The performance of each algorithm and dominance rule is analysed by five multi-objective quality indicators and fifty problem instances. The algorithms and dominance rules are ranked using a non-parametric statistical test.

Beneficial Effects of Ants and Spiders on the Reproductive Value of Eriotheca gracilipes (Malvaceae) in a Tropical Savanna

PubMed Central

2015-01-01

Predators affect plant fitness when they forage on them and reduce the action of herbivores. Our study evaluates the complementary effects of spiders and ants that visit the extrafloral nectaries of Eriotheca gracilipes (Malvaceae) on the production of fruits and viable seeds of these savanna trees. Four experimental groups were established: control group – with free access of spiders and ants; exclusion group – spiders and ants excluded; ant group – absence of spiders; and spider group – absence of ants. The presence of ants reduced the spider richness; however, the presence of spiders did not affect the ant richness. A significantly higher number of fruits per buds were found in the presence of spiders alone or spiders and ants together (control group) compared with the absence of both predators (exclusion group). The number of seeds per fruits and seed viability were higher in the control group. This is the first study showing that spiders and ants may exert a positive and complementary effect on the reproductive value of an extrafloral nectaried plant. Mostly the impact of ants and/or spiders on herbivores is considered, whereas our study reinforces the importance of evaluating the effect of multiple predators simultaneously, exploring how the interactions among predators with distinct skills may affect the herbivores and the plants on which they forage. PMID:26168036

Beneficial Effects of Ants and Spiders on the Reproductive Value of Eriotheca gracilipes (Malvaceae) in a Tropical Savanna.

PubMed

Stefani, Vanessa; Pires, Tayna Lopes; Torezan-Silingardi, Helena Maura; Del-Claro, Kleber

2015-01-01

Predators affect plant fitness when they forage on them and reduce the action of herbivores. Our study evaluates the complementary effects of spiders and ants that visit the extrafloral nectaries of Eriotheca gracilipes (Malvaceae) on the production of fruits and viable seeds of these savanna trees. Four experimental groups were established: control group - with free access of spiders and ants; exclusion group - spiders and ants excluded; ant group - absence of spiders; and spider group - absence of ants. The presence of ants reduced the spider richness; however, the presence of spiders did not affect the ant richness. A significantly higher number of fruits per buds were found in the presence of spiders alone or spiders and ants together (control group) compared with the absence of both predators (exclusion group). The number of seeds per fruits and seed viability were higher in the control group. This is the first study showing that spiders and ants may exert a positive and complementary effect on the reproductive value of an extrafloral nectaried plant. Mostly the impact of ants and/or spiders on herbivores is considered, whereas our study reinforces the importance of evaluating the effect of multiple predators simultaneously, exploring how the interactions among predators with distinct skills may affect the herbivores and the plants on which they forage.

An Effective Mechanism for Virtual Machine Placement using Aco in IAAS Cloud

NASA Astrophysics Data System (ADS)

Shenbaga Moorthy, Rajalakshmi; Fareentaj, U.; Divya, T. K.

2017-08-01

Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machine Placement (OVMP). Such mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. In order to provide appropriate resources to the clients an optimal virtual machine placement algorithm is proposed. Virtual machine placement is NP-Hard problem. Such NP-Hard problem can be solved using heuristic algorithm. In this paper, Ant Colony Optimization based virtual machine placement is proposed. Our proposed system focuses on minimizing the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment and the response time of each cloud provider is monitored periodically, in such a way to minimize delay in providing the resources to the users. The performance of the proposed algorithm is compared with greedy mechanism. The proposed algorithm is simulated in Eclipse IDE. The results clearly show that the proposed algorithm minimizes the cost, response time and also number of migrations.

Application-specific coarse-grained reconfigurable array: architecture and design methodology

NASA Astrophysics Data System (ADS)

Zhou, Li; Liu, Dongpei; Zhang, Jianfeng; Liu, Hengzhu

2015-06-01

Coarse-grained reconfigurable arrays (CGRAs) have shown potential for application in embedded systems in recent years. Numerous reconfigurable processing elements (PEs) in CGRAs provide flexibility while maintaining high performance by exploring different levels of parallelism. However, a difference remains between the CGRA and the application-specific integrated circuit (ASIC). Some application domains, such as software-defined radios (SDRs), require flexibility with performance demand increases. More effective CGRA architectures are expected to be developed. Customisation of a CGRA according to its application can improve performance and efficiency. This study proposes an application-specific CGRA architecture template composed of generic PEs (GPEs) and special PEs (SPEs). The hardware of the SPE can be customised to accelerate specific computational patterns. An automatic design methodology that includes pattern identification and application-specific function unit generation is also presented. A mapping algorithm based on ant colony optimisation is provided. Experimental results on the SDR target domain show that compared with other ordinary and application-specific reconfigurable architectures, the CGRA generated by the proposed method performs more efficiently for given applications.

Experimentally testing and assessing the predictive power of species assembly rules for tropical canopy ants

PubMed Central

Fayle, Tom M; Eggleton, Paul; Manica, Andrea; Yusah, Kalsum M; Foster, William A

2015-01-01

Understanding how species assemble into communities is a key goal in ecology. However, assembly rules are rarely tested experimentally, and their ability to shape real communities is poorly known. We surveyed a diverse community of epiphyte-dwelling ants and found that similar-sized species co-occurred less often than expected. Laboratory experiments demonstrated that invasion was discouraged by the presence of similarly sized resident species. The size difference for which invasion was less likely was the same as that for which wild species exhibited reduced co-occurrence. Finally we explored whether our experimentally derived assembly rules could simulate realistic communities. Communities simulated using size-based species assembly exhibited diversities closer to wild communities than those simulated using size-independent assembly, with results being sensitive to the combination of rules employed. Hence, species segregation in the wild can be driven by competitive species assembly, and this process is sufficient to generate observed species abundance distributions for tropical epiphyte-dwelling ants. PMID:25622647

A multipath routing protocol based on clustering and ant colony optimization for wireless sensor networks.

PubMed

Yang, Jing; Xu, Mai; Zhao, Wei; Xu, Baoguo

2010-01-01

For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively.

ALI (Autonomous Lunar Investigator): Revolutionary Approach to Exploring the Moon with Addressable Reconfigurable Technology

NASA Technical Reports Server (NTRS)

Clark, P. E.; Curtis, S. A.; Rilee, M. L.; Floyd, S. R.

2005-01-01

Addressable Reconfigurable Technology (ART) based structures: Mission Concepts based on Addressable Reconfigurable Technology (ART), originally studied for future ANTS (Autonomous Nanotechnology Swarm) Space Architectures, are now being developed as rovers for nearer term use in lunar and planetary surface exploration. The architecture is based on the reconfigurable tetrahedron as a building block. Tetrahedra are combined to form space-filling networks, shaped for the required function. Basic structural components are highly modular, addressable arrays of robust nodes (tetrahedral apices) from which highly reconfigurable struts (tetrahedral edges), acting as supports or tethers, are efficiently reversibly deployed/stowed, transforming and reshaping the structures as required.

Adaptable Learning Pathway Generation with Ant Colony Optimization

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Looi, Chee-Kit

2009-01-01

One of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with…

Exploring the Intervention-Context Interface: A Case from a School-Based Nutrition Intervention

ERIC Educational Resources Information Center

Bisset, Sherri; Daniel, Mark; Potvin, Louise

2009-01-01

It has been acknowledged for several decades that programs interact with context. The nature of this interactivity, and how it defines a program, has not been adequately addressed. We view this lacuna as a function of the dominant theoretical perspectives guiding knowledge of program operations. We propose the actor-network theory (ANT) and its…

Ant colony optimization for solving university facility layout problem

NASA Astrophysics Data System (ADS)

Mohd Jani, Nurul Hafiza; Mohd Radzi, Nor Haizan; Ngadiman, Mohd Salihin

2013-04-01

Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance).

Mission planning optimization of video satellite for ground multi-object staring imaging

NASA Astrophysics Data System (ADS)

Cui, Kaikai; Xiang, Junhua; Zhang, Yulin

2018-03-01

This study investigates the emergency scheduling problem of ground multi-object staring imaging for a single video satellite. In the proposed mission scenario, the ground objects require a specified duration of staring imaging by the video satellite. The planning horizon is not long, i.e., it is usually shorter than one orbit period. A binary decision variable and the imaging order are used as the design variables, and the total observation revenue combined with the influence of the total attitude maneuvering time is regarded as the optimization objective. Based on the constraints of the observation time windows, satellite attitude adjustment time, and satellite maneuverability, a constraint satisfaction mission planning model is established for ground object staring imaging by a single video satellite. Further, a modified ant colony optimization algorithm with tabu lists (Tabu-ACO) is designed to solve this problem. The proposed algorithm can fully exploit the intelligence and local search ability of ACO. Based on full consideration of the mission characteristics, the design of the tabu lists can reduce the search range of ACO and improve the algorithm efficiency significantly. The simulation results show that the proposed algorithm outperforms the conventional algorithm in terms of optimization performance, and it can obtain satisfactory scheduling results for the mission planning problem.

Using ant colony optimization on the quadratic assignment problem to achieve low energy cost in geo-distributed data centers

NASA Astrophysics Data System (ADS)

Osei, Richard

There are many problems associated with operating a data center. Some of these problems include data security, system performance, increasing infrastructure complexity, increasing storage utilization, keeping up with data growth, and increasing energy costs. Energy cost differs by location, and at most locations fluctuates over time. The rising cost of energy makes it harder for data centers to function properly and provide a good quality of service. With reduced energy cost, data centers will have longer lasting servers/equipment, higher availability of resources, better quality of service, a greener environment, and reduced service and software costs for consumers. Some of the ways that data centers have tried to using to reduce energy costs include dynamically switching on and off servers based on the number of users and some predefined conditions, the use of environmental monitoring sensors, and the use of dynamic voltage and frequency scaling (DVFS), which enables processors to run at different combinations of frequencies with voltages to reduce energy cost. This thesis presents another method by which energy cost at data centers could be reduced. This method involves the use of Ant Colony Optimization (ACO) on a Quadratic Assignment Problem (QAP) in assigning user request to servers in geo-distributed data centers. In this paper, an effort to reduce data center energy cost involves the use of front portals, which handle users' requests, were used as ants to find cost effective ways to assign users requests to a server in heterogeneous geo-distributed data centers. The simulation results indicate that the ACO for Optimal Server Activation and Task Placement algorithm reduces energy cost on a small and large number of users' requests in a geo-distributed data center and its performance increases as the input data grows. In a simulation with 3 geo-distributed data centers, and user's resource request ranging from 25,000 to 25,000,000, the ACO algorithm was able to reduce energy cost on an average of $.70 per second. The ACO for Optimal Server Activation and Task Placement algorithm has proven to work as an alternative or improvement in reducing energy cost in geo-distributed data centers.

Autonomous sensor manager agents (ASMA)

NASA Astrophysics Data System (ADS)

Osadciw, Lisa A.

2004-04-01

Autonomous sensor manager agents are presented as an algorithm to perform sensor management within a multisensor fusion network. The design of the hybrid ant system/particle swarm agents is described in detail with some insight into their performance. Although the algorithm is designed for the general sensor management problem, a simulation example involving 2 radar systems is presented. Algorithmic parameters are determined by the size of the region covered by the sensor network, the number of sensors, and the number of parameters to be selected. With straight forward modifications, this algorithm can be adapted for most sensor management problems.

Contact rate modulates foraging efficiency in leaf cutting ants.

PubMed

Bouchebti, S; Ferrere, S; Vittori, K; Latil, G; Dussutour, A; Fourcassié, V

2015-12-21

Lane segregation is rarely observed in animals that move in bidirectional flows. Consequently, these animals generally experience a high rate of head-on collisions during their journeys. Although these collisions have a cost (each collision induces a delay resulting in a decrease of individual speed), they could also have a benefit by promoting information transfer between individuals. Here we explore the impact of head-on collisions in leaf-cutting ants moving on foraging trails by artificially decreasing the rate of head-on collisions between individuals. We show that head-on collisions do not influence the rate of recruitment in these ants but do influence foraging efficiency, i.e. the proportion of ants returning to the nest with a leaf fragment. Surprisingly, both unladen and laden ants returning to the nest participate in the modulation of foraging efficiency: foraging efficiency decreases when the rate of contacts with both nestbound laden or unladen ants decreases. These results suggest that outgoing ants are able to collect information from inbound ants even when these latter do not carry any leaf fragment and that this information can influence their foraging decisions when reaching the end of the trail.

Individual-Based Ant-Plant Networks: Diurnal-Nocturnal Structure and Species-Area Relationship

PubMed Central

Dáttilo, Wesley; Fagundes, Roberth; Gurka, Carlos A. Q.; Silva, Mara S. A.; Vieira, Marisa C. L.; Izzo, Thiago J.; Díaz-Castelazo, Cecília; Del-Claro, Kleber; Rico-Gray, Victor

2014-01-01

Despite the importance and increasing knowledge of ecological networks, sampling effort and intrapopulation variation has been widely overlooked. Using continuous daily sampling of ants visiting three plant species in the Brazilian Neotropical savanna, we evaluated for the first time the topological structure over 24 h and species-area relationships (based on the number of extrafloral nectaries available) in individual-based ant-plant networks. We observed that diurnal and nocturnal ant-plant networks exhibited the same pattern of interactions: a nested and non-modular pattern and an average level of network specialization. Despite the high similarity in the ants’ composition between the two collection periods, ant species found in the central core of highly interacting species totally changed between diurnal and nocturnal sampling for all plant species. In other words, this “night-turnover” suggests that the ecological dynamics of these ant-plant interactions can be temporally partitioned (day and night) at a small spatial scale. Thus, it is possible that in some cases processes shaping mutualistic networks formed by protective ants and plants may be underestimated by diurnal sampling alone. Moreover, we did not observe any effect of the number of extrafloral nectaries on ant richness and their foraging on such plants in any of the studied ant-plant networks. We hypothesize that competitively superior ants could monopolize individual plants and allow the coexistence of only a few other ant species, however, other alternative hypotheses are also discussed. Thus, sampling period and species-area relationship produces basic information that increases our confidence in how individual-based ant-plant networks are structured, and the need to consider nocturnal records in ant-plant network sampling design so as to decrease inappropriate inferences. PMID:24918750

Three-dimensional visualization and a deep-learning model reveal complex fungal parasite networks in behaviorally manipulated ants

PubMed Central

Fredericksen, Maridel A.; Zhang, Yizhe; Hazen, Missy L.; Loreto, Raquel G.; Mangold, Colleen A.; Chen, Danny Z.; Hughes, David P.

2017-01-01

Some microbes possess the ability to adaptively manipulate host behavior. To better understand how such microbial parasites control animal behavior, we examine the cell-level interactions between the species-specific fungal parasite Ophiocordyceps unilateralis sensu lato and its carpenter ant host (Camponotus castaneus) at a crucial moment in the parasite’s lifecycle: when the manipulated host fixes itself permanently to a substrate by its mandibles. The fungus is known to secrete tissue-specific metabolites and cause changes in host gene expression as well as atrophy in the mandible muscles of its ant host, but it is unknown how the fungus coordinates these effects to manipulate its host’s behavior. In this study, we combine techniques in serial block-face scanning-electron microscopy and deep-learning–based image segmentation algorithms to visualize the distribution, abundance, and interactions of this fungus inside the body of its manipulated host. Fungal cells were found throughout the host body but not in the brain, implying that behavioral control of the animal body by this microbe occurs peripherally. Additionally, fungal cells invaded host muscle fibers and joined together to form networks that encircled the muscles. These networks may represent a collective foraging behavior of this parasite, which may in turn facilitate host manipulation. PMID:29114054

Autonomous NanoTechnology Swarm (ANTS) Prospecting Asteroid Mission (PAM), Asteroid Proximity Operations

NASA Technical Reports Server (NTRS)

Marr, Greg; Cooley, Steve; Roithmayr, Carlos; Kay-Bunnell, Linda; Williams, Trevor

2004-01-01

The Autonomous NanoTechnology Swarm (ANTS) is a generic mission architecture based on spatially distributed spacecraft, autonomous and redundant components, and hierarchical organization. The ANTS Prospecting Asteroid Mission (PAM) is an ANTS application which will nominally use a swarm of 1000 spacecraft. There would be 10 types of "specialists" with common spacecraft buses. There would be 10 subswarms of approximately 100 spacecraft each or approximately 10 of each specialist in each swarm. The ANTS PAM primary objective is the exploration of the asteroid belt in search of resources and material with astrobiologically relevant origins and signatures. The ANTS PAM spacecraft will nominally be released from a station in an Earth-Moon L1 libration point orbit, and they will use Solar sails for propulsion. The sail structure would be highly flexible, capable of changing morphology to change cross-section for capture of sunlight or to form effective "tip vanes" for attitude control. ANTS PAM sails would be capable of full to partial deployment, to change effective sail area and center of pressure, and thus allow attitude control. Results of analysis of a transfer trajectory from Earth to a sample target asteroid will be presented. ANTS PAM will require continuous coverage of different asteroid locations as close as one to two asteroid "diameters" from the surface of the asteroid for periods of science data collection during asteroid proximity operations. Hovering spacecraft could meet the science data collection objectives. The results of hovering analysis will be presented. There are locations for which hovering is not possible, for example on the illuminated side of the asteroid. For cases where hovering is not possible, the results of utilizing asteroid formations to orbit the asteroid and achieve the desired asteroid viewing will be presented for sample asteroids. The ability of ANTS PAM to reduce the area of the solar sail during asteroid proximity operations is critical to the maintenance of orbiting formations for a period of time. Results of analysis of potential "traffic" problems during asteroid proximity operations will be presented.

An ant colony optimization heuristic for an integrated production and distribution scheduling problem

NASA Astrophysics Data System (ADS)

Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju

2014-04-01

Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.

The interplay between scent trails and group-mass recruitment systems in ants.

PubMed

Planqué, Robert; van den Berg, Jan Bouwe; Franks, Nigel R

2013-10-01

Large ant colonies invariably use effective scent trails to guide copious ant numbers to food sources. The success of mass recruitment hinges on the involvement of many colony members to lay powerful trails. However, many ant colonies start off as single queens. How do these same colonies forage efficiently when small, thereby overcoming the hurdles to grow large? In this paper, we study the case of combined group and mass recruitment displayed by some ant species. Using mathematical models, we explore to what extent early group recruitment may aid deployment of scent trails, making such trails available at much smaller colony sizes. We show that a competition between group and mass recruitment may cause oscillatory behaviour mediated by scent trails. This results in a further reduction of colony size to establish trails successfully.

Application of a Genetic Algorithm and Multi Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the Workplace

DTIC Science & Technology

2008-06-01

postponed the fulfillment of her own Masters Degree by at least 18 months so that I would have the opportunity to earn mine. She is smart , lovely...GENETIC ALGORITHM AND MULTI AGENT SYSTEM TO EXPLORE EMERGENT PATTERNS OF SOCIAL RATIONALITY AND A DISTRESS-BASED MODEL FOR DECEIT IN THE WORKPLACE...of a Genetic Algorithm and Mutli Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the

Cosmopolitics: towards a new articulation of politics, science and critique.

PubMed

Saito, Hiro

2015-09-01

This paper explores how Ulrich Beck's world-risk-society theory (WRST) and Bruno Latour's Actor-Network Theory (ANT) can be combined to advance a theory of cosmopolitics. On the one hand, WRST helps to examine 'cosmopolitan politics', how actors try to inject cosmopolitanism into existing political practices and institutions anchored in the logic of nationalism. On the other hand, ANT sheds light on 'cosmological politics', how scientists participate in the construction of reality as a reference point for political struggles. By combining the WRST and ANT perspectives, it becomes possible to achieve a more comprehensive understanding of cosmopolitics that takes into account both political and ontological dimensions. The proposed synthesis of WRST and ANT also calls for a renewal of critical theory by making social scientists aware of their performative involvement in cosmopolitics. This renewal prompts social scientists to explore how they can pragmatically support certain ideals of cosmopolitics through continuous dialogues with their objects of study, actors who inhabit different nations and different cosmoses. © London School of Economics and Political Science 2015.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Granger, Brian R.; Chang, Yi -Chien; Wang, Yan

Here, the complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique meta-graph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction networkmore » between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.« less

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

Landmark memories are more robust when acquired at the nest site than en route: experiments in desert ants.

PubMed

Bisch-Knaden, Sonja; Wehner, Rüdiger

2003-03-01

Foraging desert ants, Cataglyphis fortis, encounter different sequences of visual landmarks while navigating by path integration. This paper explores the question whether the storage of landmark information depends on the context in which the landmarks are learned during an ant's foraging journey. Two experimental set-ups were designed in which the ants experienced an artificial landmark panorama that was placed either around the nest entrance (nest marks) or along the vector route leading straight towards the feeder (route marks). The two training paradigms resulted in pronounced differences in the storage characteristics of the acquired landmark information: memory traces of nest marks were much more robust against extinction and/or suppression than those of route marks. In functional terms, this result is in accord with the observation that desert ants encounter new route marks during every foraging run but always pass the same landmarks when approaching the nest entrance.

Ant colony algorithm implementation in electron and photon Monte Carlo transport: application to the commissioning of radiosurgery photon beams.

PubMed

García-Pareja, S; Galán, P; Manzano, F; Brualla, L; Lallena, A M

2010-07-01

In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within approximately 3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.

Invasive Fire Ants Reduce Reproductive Success and Alter the Reproductive Strategies of a Native Vertebrate Insectivore

PubMed Central

Ligon, Russell A.; Siefferman, Lynn; Hill, Geoffrey E.

2011-01-01

Background Introduced organisms can alter ecosystems by disrupting natural ecological relationships. For example, red imported fire ants (Solenopsis invicta) have disrupted native arthropod communities throughout much of their introduced range. By competing for many of the same food resources as insectivorous vertebrates, fire ants also have the potential to disrupt vertebrate communities. Methodology/Principal Findings To explore the effects of fire ants on a native insectivorous vertebrate, we compared the reproductive success and strategies of eastern bluebirds (Sialia sialis) inhabiting territories with different abundances of fire ants. We also created experimental dyads of adjacent territories comprised of one territory with artificially reduced fire ant abundance (treated) and one territory that was unmanipulated (control). We found that more bluebird young fledged from treated territories than from adjacent control territories. Fire ant abundance also explained significant variation in two measures of reproductive success across the study population: number of fledglings and hatching success of second clutches. Furthermore, the likelihood of bluebird parents re-nesting in the same territory was negatively influenced by the abundance of foraging fire ants, and parents nesting in territories with experimentally reduced abundances of fire ants produced male-biased broods relative to pairs in adjacent control territories. Conclusions/Significance Introduced fire ants altered both the reproductive success (number of fledglings, hatching success) and strategies (decision to renest, offspring sex-ratio) of eastern bluebirds. These results illustrate the negative effects that invasive species can have on native biota, including species from taxonomically distant groups. PMID:21799904

Bilingualism Aids Conflict Resolution: Evidence from the ANT Task

ERIC Educational Resources Information Center

Costa, Albert; Hernandez, Mirea; Sebastian-Galles, Nuria

2008-01-01

The need of bilinguals to continuously control two languages during speech production may exert general effects on their attentional networks. To explore this issue we compared the performance of bilinguals and monolinguals in the attentional network task (ANT) developed by Fan et al. [Fan, J., McCandliss, B.D. Sommer, T., Raz, A., Posner, M.I.…

Ant colony optimization algorithm for signal coordination of oversaturated traffic networks.

DOT National Transportation Integrated Search

2010-05-01

Traffic congestion is a daily and growing problem of the modern era in mostly all major cities in the world. : Increasing traffic demand strains the existing transportation system, leading to oversaturated network : conditions, especially at peak hou...

Homophyly/kinship hypothesis: Natural communities, and predicting in networks

NASA Astrophysics Data System (ADS)

Li, Angsheng; Li, Jiankou; Pan, Yicheng

2015-02-01

It has been a longstanding challenge to understand natural communities in real world networks. We proposed a community finding algorithm based on fitness of networks, two algorithms for prediction, accurate prediction and confirmation of keywords for papers in the citation network Arxiv HEP-TH (high energy physics theory), and the measures of internal centrality, external de-centrality, internal and external slopes to characterize the structures of communities. We implemented our algorithms on 2 citation and 5 cooperation graphs. Our experiments explored and validated a homophyly/kinship principle of real world networks. The homophyly/kinship principle includes: (1) homophyly is the natural selection in real world networks, similar to Darwin's kinship selection in nature, (2) real world networks consist of natural communities generated by the natural selection of homophyly, (3) most individuals in a natural community share a short list of common attributes, (4) natural communities have an internal centrality (or internal heterogeneity) that a natural community has a few nodes dominating most of the individuals in the community, (5) natural communities have an external de-centrality (or external homogeneity) that external links of a natural community homogeneously distributed in different communities, and (6) natural communities of a given network have typical structures determined by the internal slopes, and have typical patterns of outgoing links determined by external slopes, etc. Our homophyly/kinship principle perfectly matches Darwin's observation that animals from ants to people form social groups in which most individuals work for the common good, and that kinship could encourage altruistic behavior. Our homophyly/kinship principle is the network version of Darwinian theory, and builds a bridge between Darwinian evolution and network science.

Bio-Inspired Polarized Skylight-Based Navigation Sensors: A Review

PubMed Central

Karman, Salmah B.; Diah, S. Zaleha M.; Gebeshuber, Ille C.

2012-01-01

Animal senses cover a broad range of signal types and signal bandwidths and have inspired various sensors and bioinstrumentation devices for biological and medical applications. Insects, such as desert ants and honeybees, for example, utilize polarized skylight pattern-based information in their navigation activities. They reliably return to their nests and hives from places many kilometers away. The insect navigation system involves the dorsal rim area in their compound eyes and the corresponding polarization sensitive neurons in the brain. The dorsal rim area is equipped with photoreceptors, which have orthogonally arranged small hair-like structures termed microvilli. These are the specialized sensors for the detection of polarized skylight patterns (e-vector orientation). Various research groups have been working on the development of novel navigation systems inspired by polarized skylight-based navigation in animals. Their major contributions are critically reviewed. One focus of current research activities is on imitating the integration path mechanism in desert ants. The potential for simple, high performance miniaturized bioinstrumentation that can assist people in navigation will be explored. PMID:23202158

Bio-inspired polarized skylight-based navigation sensors: a review.

PubMed

Karman, Salmah B; Diah, S Zaleha M; Gebeshuber, Ille C

2012-10-24

Animal senses cover a broad range of signal types and signal bandwidths and have inspired various sensors and bioinstrumentation devices for biological and medical applications. Insects, such as desert ants and honeybees, for example, utilize polarized skylight pattern-based information in their navigation activities. They reliably return to their nests and hives from places many kilometers away. The insect navigation system involves the dorsal rim area in their compound eyes and the corresponding polarization sensitive neurons in the brain. The dorsal rim area is equipped with photoreceptors, which have orthogonally arranged small hair-like structures termed microvilli. These are the specialized sensors for the detection of polarized skylight patterns (e-vector orientation). Various research groups have been working on the development of novel navigation systems inspired by polarized skylight-based navigation in animals. Their major contributions are critically reviewed. One focus of current research activities is on imitating the integration path mechanism in desert ants. The potential for simple, high performance miniaturized bioinstrumentation that can assist people in navigation will be explored.

Cooperative Mission Concepts Using Biomorphic Explorers

NASA Technical Reports Server (NTRS)

Thakoor, S.; Miralles, C.; Martin, T.; Kahn, R.; Zurek, R.

2000-01-01

Inspired by the immense variety of naturally curious explorers (insects, animals, and birds), their wellintegrated biological sensor-processor suites, efficiently packaged in compact but highly dexterous forms, and their complex, intriguing, cooperative behavior, this paper focuses on "Biomorphic Explorers", their defination/classification, their designs, and presents planetary exploration scenarios based on the designs. Judicious blend of bio-inspired concepts and recent advances in micro-air vehicles, microsensors, microinstruments, MEMS, and microprocessors clearly suggests that the time of small, dedicated, low cost explorers that capture some of the key features of biological systems has arrived. Just as even small insects like ants, termites, honey bees etc working cooperatively in colonies can achieve big tasks, the biomorphic explorers hold the potential for obtaining science in-accessible by current large singular exploration platforms.

A preliminary study to metaheuristic approach in multilayer radiation shielding optimization

NASA Astrophysics Data System (ADS)

Arif Sazali, Muhammad; Rashid, Nahrul Khair Alang Md; Hamzah, Khaidzir

2018-01-01

Metaheuristics are high-level algorithmic concepts that can be used to develop heuristic optimization algorithms. One of their applications is to find optimal or near optimal solutions to combinatorial optimization problems (COPs) such as scheduling, vehicle routing, and timetabling. Combinatorial optimization deals with finding optimal combinations or permutations in a given set of problem components when exhaustive search is not feasible. A radiation shield made of several layers of different materials can be regarded as a COP. The time taken to optimize the shield may be too high when several parameters are involved such as the number of materials, the thickness of layers, and the arrangement of materials. Metaheuristics can be applied to reduce the optimization time, trading guaranteed optimal solutions for near-optimal solutions in comparably short amount of time. The application of metaheuristics for radiation shield optimization is lacking. In this paper, we present a review on the suitability of using metaheuristics in multilayer shielding design, specifically the genetic algorithm and ant colony optimization algorithm (ACO). We would also like to propose an optimization model based on the ACO method.

KANTS: a stigmergic ant algorithm for cluster analysis and swarm art.

PubMed

Fernandes, Carlos M; Mora, Antonio M; Merelo, Juan J; Rosa, Agostinho C

2014-06-01

KANTS is a swarm intelligence clustering algorithm inspired by the behavior of social insects. It uses stigmergy as a strategy for clustering large datasets and, as a result, displays a typical behavior of complex systems: self-organization and global patterns emerging from the local interaction of simple units. This paper introduces a simplified version of KANTS and describes recent experiments with the algorithm in the context of a contemporary artistic and scientific trend called swarm art, a type of generative art in which swarm intelligence systems are used to create artwork or ornamental objects. KANTS is used here for generating color drawings from the input data that represent real-world phenomena, such as electroencephalogram sleep data. However, the main proposal of this paper is an art project based on well-known abstract paintings, from which the chromatic values are extracted and used as input. Colors and shapes are therefore reorganized by KANTS, which generates its own interpretation of the original artworks. The project won the 2012 Evolutionary Art, Design, and Creativity Competition.

Different types of maximum power point tracking techniques for renewable energy systems: A survey

NASA Astrophysics Data System (ADS)

Khan, Mohammad Junaid; Shukla, Praveen; Mustafa, Rashid; Chatterji, S.; Mathew, Lini

2016-03-01

Global demand for electricity is increasing while production of energy from fossil fuels is declining and therefore the obvious choice of the clean energy source that is abundant and could provide security for development future is energy from the sun. In this paper, the characteristic of the supply voltage of the photovoltaic generator is nonlinear and exhibits multiple peaks, including many local peaks and a global peak in non-uniform irradiance. To keep global peak, MPPT is the important component of photovoltaic systems. Although many review articles discussed conventional techniques such as P & O, incremental conductance, the correlation ripple control and very few attempts have been made with intelligent MPPT techniques. This document also discusses different algorithms based on fuzzy logic, Ant Colony Optimization, Genetic Algorithm, artificial neural networks, Particle Swarm Optimization Algorithm Firefly, Extremum seeking control method and hybrid methods applied to the monitoring of maximum value of power at point in systems of photovoltaic under changing conditions of irradiance.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

PubMed

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

PubMed Central

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-01-01

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633

Plants in Your Ants: Using Ant Mounds to Test Basic Ecological Principles

ERIC Educational Resources Information Center

Zettler, Jennifer A.; Collier, Alexander; Leidersdorf, Bil; Sanou, Missa Patrick

2010-01-01

Urban students often have limited access to field sites for ecological studies. Ubiquitous ants and their mounds can be used to study and test ecology-based questions. We describe how soil collected from ant mounds can be used to investigate how biotic factors (ants) can affect abiotic factors in the soil that can, in turn, influence plant growth.

Tracing the Rise of Ants - Out of the Ground

PubMed Central

Lucky, Andrea; Trautwein, Michelle D.; Guénard, Benoit S.; Weiser, Michael D.; Dunn, Robert R.

2013-01-01

The evolution of ants (Hymenoptera: Formicidae) is increasingly well-understood due to recent phylogenetic analyses, along with estimates of divergence times and diversification rates. Yet, leading hypotheses regarding the ancestral habitat of ants conflict with new findings that early ant lineages are cryptic and subterranean. Where the ants evolved, in respect to habitat, and how habitat shifts took place over time have not been formally tested. Here, we reconstruct the habitat transitions of crown-group ants through time, focusing on where they nest and forage (in the canopy, litter, or soil). Based on ancestral character reconstructions, we show that in contrast to the current consensus based on verbal arguments that ants evolved in tropical leaf litter, the soil is supported as the ancestral stratum of all ants. We also find subsequent movements up into the litter and, in some cases, into the canopy. Given the global importance of ants, because of their diversity, ecological influence and status as the most successful eusocial lineage on Earth, understanding the early evolution of this lineage provides insight into the factors that made this group so successful today. PMID:24386323

Software Piracy Detection Model Using Ant Colony Optimization Algorithm

NASA Astrophysics Data System (ADS)

Astiqah Omar, Nor; Zakuan, Zeti Zuryani Mohd; Saian, Rizauddin

2017-06-01

Internet enables information to be accessible anytime and anywhere. This scenario creates an environment whereby information can be easily copied. Easy access to the internet is one of the factors which contribute towards piracy in Malaysia as well as the rest of the world. According to a survey conducted by Compliance Gap BSA Global Software Survey in 2013 on software piracy, found out that 43 percent of the software installed on PCs around the world was not properly licensed, the commercial value of the unlicensed installations worldwide was reported to be 62.7 billion. Piracy can happen anywhere including universities. Malaysia as well as other countries in the world is faced with issues of piracy committed by the students in universities. Piracy in universities concern about acts of stealing intellectual property. It can be in the form of software piracy, music piracy, movies piracy and piracy of intellectual materials such as books, articles and journals. This scenario affected the owner of intellectual property as their property is in jeopardy. This study has developed a classification model for detecting software piracy. The model was developed using a swarm intelligence algorithm called the Ant Colony Optimization algorithm. The data for training was collected by a study conducted in Universiti Teknologi MARA (Perlis). Experimental results show that the model detection accuracy rate is better as compared to J48 algorithm.

Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

PubMed

Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

2015-02-10

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

Using Ants To Investigate the Environment.

ERIC Educational Resources Information Center

Hagevik, Rita A.

2003-01-01

Describes three inquiry-based activities designed for students to begin to understand complex environmental relationships in their own backyard. Includes investigations of ants, which allow students to establish a baseline survey of ant fauna, test the importance of ants in nutrient cycling and soil structure maintenances, and increase student…

RNA secondary structure prediction using soft computing.

PubMed

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

Evidence that insect herbivores are deterred by ant pheromones.

PubMed Central

Offenberg, Joachim; Nielsen, Mogens Gissel; MacIntosh, Donald J; Havanon, Sopon; Aksornkoae, Sanit

2004-01-01

It is well documented that ants can protect plants against insect herbivores, but the underlying mechanisms remain almost undocumented. We propose and test the pheromone avoidance hypothesis--an indirect mechanism where insect herbivores are repelled not only by ants but also by ant pheromones. Herbivores subjected to ant predation will experience a selective advantage if they evolve mechanisms enabling them to avoid feeding within ant territories. Such a mechanism could be based on the ability to detect and evade ant pheromones. Field observations and data from the literature showed that the ant Oecophylla smaragdina distributes persistent pheromones throughout its territory. In addition, a laboratory test showed that the beetle Rhyparida wallacei, which this ant preys on, was reluctant to feed on leaves sampled within ant territories compared with leaves sampled outside territories. Thus, this study provides an example of an ant-herbivore system conforming to the pheromone avoidance hypothesis. PMID:15801596

Concepts and applications of "natural computing" techniques in de novo drug and peptide design.

PubMed

Hiss, Jan A; Hartenfeller, Markus; Schneider, Gisbert

2010-05-01

Evolutionary algorithms, particle swarm optimization, and ant colony optimization have emerged as robust optimization methods for molecular modeling and peptide design. Such algorithms mimic combinatorial molecule assembly by using molecular fragments as building-blocks for compound construction, and relying on adaptation and emergence of desired pharmacological properties in a population of virtual molecules. Nature-inspired algorithms might be particularly suited for bioisosteric replacement or scaffold-hopping from complex natural products to synthetically more easily accessible compounds that are amenable to optimization by medicinal chemistry. The theory and applications of selected nature-inspired algorithms for drug design are reviewed, together with practical applications and a discussion of their advantages and limitations.

MONITORING CHANGES IN STRESSED ECOSYSTEMS USING SPATIAL PATTERNS OF ANT COMMUNITIES

EPA Science Inventory

We examined the feasibility of using changes in spatial patterns of ants-distribution on experimental plots as an indicator of response to environmental stress. We produced contour maps based on relative abundances of the three most common genera of ants based on pit-fall trap ca...

Desert ants achieve reliable recruitment across noisy interactions

PubMed Central

Razin, Nitzan; Eckmann, Jean-Pierre; Feinerman, Ofer

2013-01-01

We study how desert ants, Cataglyphis niger, a species that lacks pheromone-based recruitment mechanisms, inform each other about the presence of food. Our results are based on automated tracking that allows us to collect a large database of ant trajectories and interactions. We find that interactions affect an ant's speed within the nest. Fast ants tend to slow down, whereas slow ones increase their speed when encountering a faster ant. Faster ants tend to exit the nest more frequently than slower ones. So, if an ant gains enough speed through encounters with others, then she tends to leave the nest and look for food. On the other hand, we find that the probability for her to leave the nest depends only on her speed, but not on whether she had recently interacted with a recruiter that has found the food. This suggests a recruitment system in which ants communicate their state by very simple interactions. Based on this assumption, we estimate the information-theoretical channel capacity of the ants’ pairwise interactions. We find that the response to the speed of an interacting nest-mate is very noisy. The question is then how random interactions with ants within the nest can be distinguished from those interactions with a recruiter who has found food. Our measurements and model suggest that this distinction does not depend on reliable communication but on behavioural differences between ants that have found the food and those that have not. Recruiters retain high speeds throughout the experiment, regardless of the ants they interact with; non-recruiters communicate with a limited number of nest-mates and adjust their speed following these interactions. These simple rules lead to the formation of a bistable switch on the level of the group that allows the distinction between recruitment and random noise in the nest. A consequence of the mechanism we propose is a negative effect of ant density on exit rates and recruitment success. This is, indeed, confirmed by our measurements. PMID:23486172

Ant predation on herbivores through a multitrophic lens: how effects of ants on plant herbivore defense and natural enemies vary along temperature gradients.

PubMed

Rodríguez-Castañeda, G; Brehm, G; Fiedler, K; Dyer, L A

2016-04-01

Ants are keystone predators in terrestrial trophic cascades. Addressing ants' roles in multitrophic interactions across regional gradients is important for understanding mechanisms behind range limits of species. We present four hypotheses of trophic dynamics occurring when ants are rare: first, there is a shift in predator communities; second, plants decrease investments in ant attraction and increase production of secondary metabolites; third, lower herbivory at high elevations allows plants to tolerate herbivory; and fourth, distribution of ant-plants can be limited based on ant abundance. Conducting experiments on multitrophic effects of ants across elevational gradients, and incorporating these results to ecological niche modeling (ENM) will improve our knowledge of the impacts of global change on ants, trophic interactions, and biodiversity. Copyright © 2016 Elsevier Inc. All rights reserved.

Quantifying Ant Activity Using Vibration Measurements

PubMed Central

Oberst, Sebastian; Baro, Enrique Nava; Lai, Joseph C. S.; Evans, Theodore A.

2014-01-01

Ant behaviour is of great interest due to their sociality. Ant behaviour is typically observed visually, however there are many circumstances where visual observation is not possible. It may be possible to assess ant behaviour using vibration signals produced by their physical movement. We demonstrate through a series of bioassays with different stimuli that the level of activity of meat ants (Iridomyrmex purpureus) can be quantified using vibrations, corresponding to observations with video. We found that ants exposed to physical shaking produced the highest average vibration amplitudes followed by ants with stones to drag, then ants with neighbours, illuminated ants and ants in darkness. In addition, we devised a novel method based on wavelet decomposition to separate the vibration signal owing to the initial ant behaviour from the substrate response, which will allow signals recorded from different substrates to be compared directly. Our results indicate the potential to use vibration signals to classify some ant behaviours in situations where visual observation could be difficult. PMID:24658467

Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

USDA-ARS?s Scientific Manuscript database

A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...

An Improved Artificial Bee Colony-Based Approach for Zoning Protected Ecological Areas

PubMed Central

Shao, Jing; Yang, Lina; Peng, Ling; Chi, Tianhe; Wang, Xiaomeng

2015-01-01

China is facing ecological and environmental challenges as its urban growth rate continues to rise, and zoning protected ecological areas is recognized as an effective response measure. Zoning inherently involves both site attributes and aggregation attributes, and the combination of mathematical models and heuristic algorithms have proven advantageous. In this article, an improved artificial bee colony (IABC)-based approach is proposed for zoning protected ecological areas at a regional scale. Three main improvements were made: the first is the use of multiple strategies to generate the initial bee population of a specific quality and diversity, the second is an exploitation search procedure to generate neighbor solutions combining “replace” and “alter” operations, and the third is a “swap” strategy to enable a local search for the iterative optimal solution. The IABC algorithm was verified using simulated data. Then it was applied to define an optimum scheme of protected ecological areas of Sanya (in the Hainan province of China), and a reasonable solution was obtained. Finally, a comparison experiment with other methods (agent-based land allocation model, ant colony optimization, and density slicing) was conducted and demonstrated that the IABC algorithm was more effective and efficient than the other methods. Through this study, we aimed to provide a scientifically sound, practical approach for zoning procedures. PMID:26394148

Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms

PubMed Central

Hu, Zhongyi; Xiong, Tao

2013-01-01

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA) based memetic algorithm (FA-MA) to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature. PMID:24459425

Electricity load forecasting using support vector regression with memetic algorithms.

PubMed

Hu, Zhongyi; Bao, Yukun; Xiong, Tao

2013-01-01

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA) based memetic algorithm (FA-MA) to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature.

Preliminary in vitro insights into the use of natural fungal pathogens of leaf-cutting ants as biocontrol agents.

PubMed

Folgarait, Patricia; Gorosito, Norma; Poulsen, Michael; Currie, Cameron R

2011-09-01

Leaf-cutting ants are one of the main herbivores of the Neotropics, where they represent an important agricultural pest. These ants are particularly difficult to control because of the complex network of microbial symbionts. Leaf-cutting ants have traditionally been controlled through pesticide application, but there is a need for alternative, more environmentally friendly, control methods such as biological control. Potential promising biocontrol candidates include the microfungi Escovopsis spp. (anamorphic Hypocreales), which are specialized pathogens of the fungi the ants cultivate for food. These pathogens are suppressed through ant behaviors and ant-associated antibiotic-producing Actinobacteria. In order to be an effective biocontrol agent, Escovopsis has to overcome these defenses. Here, we evaluate, using microbial in vitro assays, whether defenses in the ant-cultivated fungus strain (Leucoagaricus sp.) and Actinobacteria from the ant pest Acromyrmex lundii have the potential to limit the use of Escovopsis in biocontrol. We also explore, for the first time, possible synergistic biocontrol between Escovopsis and the entomopathogenic fungus Lecanicillium lecanii. All strains of Escovopsis proved to overgrow A. lundii cultivar in less than 7 days, with the Escovopsis strain isolated from a different leaf-cutting ant species being the most efficient. Escovopsis challenged with a Streptomyces strain isolated from A. lundii did not exhibit significant growth inhibition. Both results are encouraging for the use of Escovopsis as a biocontrol agent. Although we found that L. lecanii can suppress the growth of the cultivar, it also had a negative impact on Escovopsis, making the success of simultaneous use of these two fungi for biocontrol of A. lundii questionable.

Evaluation of the attention network test using vibrotactile stimulations.

PubMed

Salzer, Yael; Oron-Gilad, Tal; Henik, Avishai

2015-06-01

We report a vibrotactile version of the attention network test (ANT)-the tactile ANT (T-ANT). It has been questioned whether attentional components are modality specific or not. The T-ANT explores alertness, orienting, cognitive control, and their relationships, similar to its visual counterpart, in the tactile modality. The unique features of the T-ANT are in utilizing stimuli on a single plane-the torso-and replacing the original imperative flanker task with a tactile Simon task. Subjects wore a waist belt mounted with two vibrotactile stimulators situated on the back and positioned to the right and left of the spinal column. They responded by pressing keys with their right or left hand in reaction to the type of vibrotactile stimulation (pulsed/continuous signal). On a single trial, an alerting tone was followed by a short tactile (informative/noninformative) peripheral cue and an imperative tactile Simon task target. The T-ANT was compared with a variant of the ANT in which the flanker task was replaced with a visual Simon task. Experimental data showed effects of orienting over control only when the peripheral cues were informative. In contrast to the visual task, interactions between alertness and control or alertness and orienting were not found in the tactile task. A possible rationale for these results is discussed. The T-ANT allows examination of attentional processes among patients with tactile attentional deficits and patients with eyesight deficits who cannot take part in visual tasks. Technological advancement would enable implementation of the T-ANT in brain-imaging studies.

78 FR 70530 - Notice of Determination; New and Revised Treatments for the Imported Fire Ant Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-26

...] Notice of Determination; New and Revised Treatments for the Imported Fire Ant Program AGENCY: Animal and... adding or revising certain treatment schedules for the Imported Fire Ant Program in the Plant Protection... imported fire ant program. Based on the treatment evaluation document, the environmental assessment, and...

Combining sky and earth: desert ants (Melophorus bagoti) show weighted integration of celestial and terrestrial cues.

PubMed

Legge, Eric L G; Wystrach, Antoine; Spetch, Marcia L; Cheng, Ken

2014-12-01

Insects typically use celestial sources of directional information for path integration, and terrestrial panoramic information for view-based navigation. Here we set celestial and terrestrial sources of directional information in conflict for homing desert ants (Melophorus bagoti). In the first experiment, ants learned to navigate out of a round experimental arena with a distinctive artificial panorama. On crucial tests, we rotated the arena to create a conflict between the artificial panorama and celestial information. In a second experiment, ants at a feeder in their natural visually-cluttered habitat were displaced prior to their homing journey so that the dictates of path integration (feeder to nest direction) based on a celestial compass conflicted with the dictates of view-based navigation (release point to nest direction) based on the natural terrestrial panorama. In both experiments, ants generally headed in a direction intermediate to the dictates of celestial and terrestrial information. In the second experiment, the ants put more weight on the terrestrial cues when they provided better directional information. We conclude that desert ants weight and integrate the dictates of celestial and terrestrial information in determining their initial heading, even when the two directional cues are highly discrepant. © 2014. Published by The Company of Biologists Ltd.

Application of Chitosan-Zinc Oxide Nanoparticles for Lead Extraction From Water Samples by Combining Ant Colony Optimization with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Khajeh, M.; Pourkarami, A.; Arefnejad, E.; Bohlooli, M.; Khatibi, A.; Ghaffari-Moghaddam, M.; Zareian-Jahromi, S.

2017-09-01

Chitosan-zinc oxide nanoparticles (CZPs) were developed for solid-phase extraction. Combined artificial neural network-ant colony optimization (ANN-ACO) was used for the simultaneous preconcentration and determination of lead (Pb2+) ions in water samples prior to graphite furnace atomic absorption spectrometry (GF AAS). The solution pH, mass of adsorbent CZPs, amount of 1-(2-pyridylazo)-2-naphthol (PAN), which was used as a complexing agent, eluent volume, eluent concentration, and flow rates of sample and eluent were used as input parameters of the ANN model, and the percentage of extracted Pb2+ ions was used as the output variable of the model. A multilayer perception network with a back-propagation learning algorithm was used to fit the experimental data. The optimum conditions were obtained based on the ACO. Under the optimized conditions, the limit of detection for Pb2+ ions was found to be 0.078 μg/L. This procedure was also successfully used to determine the amounts of Pb2+ ions in various natural water samples.

Glass-like dynamics in confined and congested ant traffic.

PubMed

Gravish, Nick; Gold, Gregory; Zangwill, Andrew; Goodisman, Michael A D; Goldman, Daniel I

2015-09-07

The collective movement of animal groups often occurs in confined spaces. As animal groups are challenged to move at high density, their mobility dynamics may resemble the flow of densely packed non-living soft materials such as colloids, grains, or polymers. However, unlike inert soft-materials, self-propelled collective living systems often display social interactions whose influence on collective mobility are only now being explored. In this paper, we study the mobility of bi-directional traffic flow in a social insect (the fire ant Solenopsis invicta) as we vary the diameter of confining foraging tunnels. In all tunnel diameters, we observe the emergence of spatially heterogeneous regions of fast and slow traffic that are induced through two phenomena: physical obstruction, arising from the inability of individual ants to interpenetrate, and time-delay resulting from social interaction in which ants stop to briefly antennate. Density correlation functions reveal that the relaxation dynamics of high density traffic fluctuations scale linearly with fluctuation size and are sensitive to tunnel diameter. We separate the roles of physical obstruction and social interactions in traffic flow using cellular automata based simulation. Social interaction between ants is modeled as a dwell time (Tint) over which interacting ants remain stationary in the tunnel. Investigation over a range of densities and Tint reveals that the slowing dynamics of collective motion in social living systems are consistent with dynamics near a fragile glass transition in inert soft-matter systems. In particular, flow is relatively insensitive to density until a critical density is reached. As social interaction affinity is increased (increasing Tint) traffic dynamics change and resemble a strong glass transition. Thus, social interactions play an important role in the mobility of collective living systems at high density. Our experiments and model demonstrate that the concepts of soft-matter physics aid understanding of the mobility of collective living systems, and motivate further inquiry into the dynamics of densely confined social living systems.

Use of biliary stent in laparoscopic common bile duct exploration.

PubMed

Lyon, Matthew; Menon, Seema; Jain, Abhiney; Kumar, Harish

2015-05-01

It is well supported in the literature that laparoscopic common bile duct exploration (LCBDE) for choledocholithiasis has equal efficacy when compared to ERCP followed by laparoscopic cholecystectomy. Decompression after supra-duodenal choledochotomy is common practice as it reduced the risk of bile leaks. We conducted a prospective non-randomized study to compare outcomes and length of stay in patients undergoing biliary stent insertion versus T-tube drainage following LCBDE via choledochotomy. The study involved 116 patients with choledocholithiasis who underwent LCBDE and decompression of the biliary system by either ante-grade biliary stent or T-tube insertion. A 7 French straight/duodenal curve biliary Diagmed™ stent (9-11 cm) was placed in 82 patients (Biliary Stent Group). T-tube insertion was used for 34 patients (T-tube group). The length of hospital stay and complications for the selected patients were recorded. All trans-cystic common bile duct explorations were excluded from the study. The mean hospital stay for patients who underwent ante-grade biliary stent or T-tube insertion after LBCDE were 1 and 3.4 days, respectively. This is a statistically significant result with a p value of less than 0.001. Of the T-tube group, two patients required laparoscopic washout due to bile leaks, one had ongoing biliary stasis and one reported ongoing pain whilst the T-tube was in situ. A complication rate of 11.2%, this was a significant finding. There were no complications or concerns reported for the Biliary Stent Group. Our results show that there is a significant reduction in length of hospital stay and morbidity for patients that have ante-grade biliary stent decompression of the CBD post laparoscopic choledochotomy when compared T-tube drainage. This implies that ante-grade biliary stent insertion is likely to reduce costs and increase overall patient satisfaction. We support the use of ante-grade biliary stent insertion during LCBDE when primary closure is not preferred.

Log-linear model based behavior selection method for artificial fish swarm algorithm.

PubMed

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

A performance evaluation of ACO and SA TSP in a supply chain network

NASA Astrophysics Data System (ADS)

Rao, T. Srinivas

2017-07-01

Supply Chain management and E commerce business solutions are one of the prominent areas of active research. In our paper we have modelled a supply chain model which aggregates all the manufacturers requirement and the products are supplied to all the manufacturer through a common vehicle routing algorithm. An appropriate tsp has been constructed for all the manufacturers which determines the shortest route thru which the aggregated material can be supplied in the shortest possible time. In this paper we have solved the shortest route through constructing a Simulated annealing algorithm and Ant colony algorithm and their performance is evaluated.

Flexible augmented reality architecture applied to environmental management

NASA Astrophysics Data System (ADS)

Correia, Nuno M. R.; Romao, Teresa; Santos, Carlos; Trabuco, Adelaide; Santos, Rossana; Romero, Luis; Danado, Jose; Dias, Eduardo; Camara, Antonio; Nobre, Edmundo

2003-05-01

Environmental management often requires in loco observation of the area under analysis. Augmented Reality (AR) technologies allow real time superimposition of synthetic objects on real images, providing augmented knowledge about the surrounding world. Users of an AR system can visualize the real surrounding world together with additional data generated in real time in a contextual way. The work reported in this paper was done in the scope of ANTS (Augmented Environments) project. ANTS is an AR project that explores the development of an augmented reality technological infrastructure for environmental management. This paper presents the architecture and the most relevant modules of ANTS. The system"s architecture follows the client-server model and is based on several independent, but functionally interdependent modules. It has a flexible design, which allows the transfer of some modules to and from the client side, according to the available processing capacities of the client device and the application"s requirements. It combines several techniques to identify the user"s position and orientation allowing the system to adapt to the particular characteristics of each environment. The determination of the data associated to a certain location involves the use of both a 3D Model of the location and the multimedia geo-referenced database.

Learner Typologies Development Using OIndex and Data Mining Based Clustering Techniques

ERIC Educational Resources Information Center

Luan, Jing

2004-01-01

This explorative data mining project used distance based clustering algorithm to study 3 indicators, called OIndex, of student behavioral data and stabilized at a 6-cluster scenario following an exhaustive explorative study of 4, 5, and 6 cluster scenarios produced by K-Means and TwoStep algorithms. Using principles in data mining, the study…

Spider diversity in coffee agroecosystems: the influence of agricultural intensification and aggressive ants.

PubMed

Marín, Linda; Perfecto, Ivette

2013-04-01

Spiders are a very diverse group of invertebrate predators found in agroecosystems and natural systems. However, spider distribution, abundance, and eventually their ecological function in ecosystems can be influenced by abiotic and biotic factors such as agricultural intensification and dominant ants. Here we explore the influence of both agricultural intensification and the dominant arboreal ant Azteca instabilis on the spider community in coffee agroecosystems in southern Mexico. To measure the influence of the arboreal ant Azteca instabilis (F. Smith) on the spider community inhabiting the coffee layer of coffee agroecosystems, spiders were collected from coffee plants that were and were not patrolled by the ant in sites differing in agricultural intensification. For 2008, generalized linear mixed models showed that spider diversity was affected positively by agricultural intensification but not by the ant. However, results suggested that some spider species were associated with A. instabilis. Therefore, in 2009 we concentrated our research on the effect of A. instabilis on spider diversity and composition. For 2009, generalized linear mixed models show that spider richness and abundance per plant were significantly higher in the presence of A. instabilis. In addition, analyses of visual counts of insects and sticky traps data show that more resources were present in plants patrolled by the ant. The positive effect of A. instabilis on spiders seems to be caused by at least two mechanisms: high abundance of insects and protection against predators.

Use of radio-tagging to map spatial organization and social interactions in insects.

PubMed

Moreau, Mathieu; Arrufat, Patrick; Latil, Gérard; Jeanson, Raphaël

2011-01-01

Understanding of the organization of animal societies often requires knowledge of the identity of group members and their spatial location. We propose an original experimental design to track automatically the position of individuals using radio frequency identification technology (RFID). Ants equipped with passive transponders were detected by a reader mounted on a mobile arm moving across the nest surface. We developed an algorithm to accurately extract the positions of individuals moving in two dimensions. Our method was validated on synthetic test cases and then used for characterization of the spatial distribution of ants within nests. This approach provides an amenable system for monitoring large populations of individuals over long periods of time.

Recourse-based facility-location problems in hybrid uncertain environment.

PubMed

Wang, Shuming; Watada, Junzo; Pedrycz, Witold

2010-08-01

The objective of this paper is to study facility-location problems in the presence of a hybrid uncertain environment involving both randomness and fuzziness. A two-stage fuzzy-random facility-location model with recourse (FR-FLMR) is developed in which both the demands and costs are assumed to be fuzzy-random variables. The bounds of the optimal objective value of the two-stage FR-FLMR are derived. As, in general, the fuzzy-random parameters of the FR-FLMR can be regarded as continuous fuzzy-random variables with an infinite number of realizations, the computation of the recourse requires solving infinite second-stage programming problems. Owing to this requirement, the recourse function cannot be determined analytically, and, hence, the model cannot benefit from the use of techniques of classical mathematical programming. In order to solve the location problems of this nature, we first develop a technique of fuzzy-random simulation to compute the recourse function. The convergence of such simulation scenarios is discussed. In the sequel, we propose a hybrid mutation-based binary ant-colony optimization (MBACO) approach to the two-stage FR-FLMR, which comprises the fuzzy-random simulation and the simplex algorithm. A numerical experiment illustrates the application of the hybrid MBACO algorithm. The comparison shows that the hybrid MBACO finds better solutions than the one using other discrete metaheuristic algorithms, such as binary particle-swarm optimization, genetic algorithm, and tabu search.

Distributional Patterns of Pseudacteon Associated with the Solenopsis saevissima Complex in South America

PubMed Central

Patrock, Richard J. W.; Porter, Sanford D.; Gilbert, Lawrence E.; Folgarait, Patricia J.

2009-01-01

Classical biological control efforts against imported fire ants have largely involved the use of Pseudacteon parasitoids. To facilitate further exploration for species and population biotypes a database of collection records for Pseudacteon species was organized, including those from the literature and other sources. These data were then used to map the geographical ranges of species associated with the imported fire ants in their native range in South America. In addition, we found geographical range metrics for all species in the genus and related these metrics to latitude and host use. Approximately equal numbers of Pseudacteon species were found in temperate and tropical regions, though the majority of taxa found only in temperate areas were found in the Northern Hemisphere. No significant differences in sizes of geographical ranges were found between Pseudacteon associated with the different host complexes of fire ants despite the much larger and systemic collection effort associated with the S. saevissima host group. The geographical range of the flies was loosely associated with both the number of hosts and the geographical range of their hosts. Pseudacteon with the most extensive ranges had either multiple hosts or hosts with broad distributions. Mean species richnesses of Pseudacteon in locality species assemblages associated with S. saevissima complex ants was 2.8 species, but intensively sampled locations were usually much higher. Possible factors are discussed related to variation in the size of geographical range, and areas in southern South America are outlined that are likely to have been under-explored for Pseudacteon associated with imported fire ants. PMID:20050779

Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode

PubMed Central

Zhu, Xiaoning

2014-01-01

Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency. In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks. An ant colony optimization is proposed to obtain near optimal solutions. Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm. The results show that the proposed method is effective in reducing the idle load time of RMGC. PMID:25538768

Impact of Chaos Functions on Modern Swarm Optimizers.

PubMed

Emary, E; Zawbaa, Hossam M

2016-01-01

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates the impact of using chaos-based control of exploration/exploitation rates against using the systematic native control. Three modern algorithms were used in the study namely grey wolf optimizer (GWO), antlion optimizer (ALO) and moth-flame optimizer (MFO) in the domain of machine learning for feature selection. Results on a set of standard machine learning data using a set of assessment indicators prove advance in optimization algorithm performance when using variational repeated periods of declined exploration rates over using systematically decreased exploration rates.

A new fire ant (Hymenoptera: Formicidae) bait base carrier for moist conditions.

PubMed

Kafle, Lekhnath; Wu, Wen-Jer; Shih, Cheng-Jen

2010-10-01

A new water-resistant fire ant bait (T-bait; cypermethrin 0.128%) consisting of dried distillers grains with solubles (DDGS) as a carrier was developed and evaluated against a standard commercial bait (Advion; indoxacarb 0.045%) under both laboratory and field conditions. When applying the normal T-bait or Advion in the laboratory, 100% of Solenopsis invicta Buren worker ants were killed within 4 days. However, when the T-bait and Advion were wetted, 70.6 and 39.7% of the ants were killed respectively. Under field conditions, dry T-bait and dry Advion had almost the same efficacy against ant colonies. However, when T-bait and Advion came in contact with water, the former's ability to kill S. invicta colonies in the field was only marginally reduced, while Advion lost virtually all of its activity. In addition, DDGS was also shown to be compatible with a number of other insecticides, such as d-allethrin, permethrin and pyrethrin. Based on its properties of remaining attractive to the fire ants when wetted, combined with its ant-killing abilities both in the laboratory and in the field, T-bait is an efficient fire ant bait, especially under moist conditions.

Vegetation structure of plantain-based agrosystems determines numerical dominance in community of ground-dwelling ants

PubMed Central

Dassou, Anicet Gbéblonoudo; Tixier, Philippe; Dépigny, Sylvain

2017-01-01

In tropics, ants can represent an important part of animal biomass and are known to be involved in ecosystem services, such as pest regulation. Understanding the mechanisms underlying the structuring of local ant communities is therefore important in agroecology. In the humid tropics of Africa, plantains are cropped in association with many other annual and perennial crops. Such agrosystems differ greatly in vegetation diversity and structure and are well-suited for studying how habitat-related factors affect the ant community. We analysed abundance data for the six numerically dominant ant taxa in 500 subplots located in 20 diversified, plantain-based fields. We found that the density of crops with foliage at intermediate and high canopy strata determined the numerical dominance of species. We found no relationship between the numerical dominance of each ant taxon with the crop diversity. Our results indicate that the manipulation of the densities of crops with leaves in the intermediate and high strata may help maintain the coexistence of ant species by providing different habitat patches. Further research in such agrosystems should be performed to assess if the effect of vegetation structure on ant abundance could result in efficient pest regulation. PMID:29152414

Vegetation structure of plantain-based agrosystems determines numerical dominance in community of ground-dwelling ants.

PubMed

Dassou, Anicet Gbéblonoudo; Tixier, Philippe; Dépigny, Sylvain; Carval, Dominique

2017-01-01

In tropics, ants can represent an important part of animal biomass and are known to be involved in ecosystem services, such as pest regulation. Understanding the mechanisms underlying the structuring of local ant communities is therefore important in agroecology. In the humid tropics of Africa, plantains are cropped in association with many other annual and perennial crops. Such agrosystems differ greatly in vegetation diversity and structure and are well-suited for studying how habitat-related factors affect the ant community. We analysed abundance data for the six numerically dominant ant taxa in 500 subplots located in 20 diversified, plantain-based fields. We found that the density of crops with foliage at intermediate and high canopy strata determined the numerical dominance of species. We found no relationship between the numerical dominance of each ant taxon with the crop diversity. Our results indicate that the manipulation of the densities of crops with leaves in the intermediate and high strata may help maintain the coexistence of ant species by providing different habitat patches. Further research in such agrosystems should be performed to assess if the effect of vegetation structure on ant abundance could result in efficient pest regulation.

Fairness in optimizing bus-crew scheduling process.

PubMed

Ma, Jihui; Song, Cuiying; Ceder, Avishai Avi; Liu, Tao; Guan, Wei

2017-01-01

This work proposes a model considering fairness in the problem of crew scheduling for bus drivers (CSP-BD) using a hybrid ant-colony optimization (HACO) algorithm to solve it. The main contributions of this work are the following: (a) a valid approach for cases with a special cost structure and constraints considering the fairness of working time and idle time; (b) an improved algorithm incorporating Gamma heuristic function and selecting rules. The relationships of each cost are examined with ten bus lines collected from the Beijing Public Transport Holdings (Group) Co., Ltd., one of the largest bus transit companies in the world. It shows that unfair cost is indirectly related to common cost, fixed cost and extra cost and also the unfair cost approaches to common and fixed cost when its coefficient is twice of common cost coefficient. Furthermore, the longest time for the tested bus line with 1108 pieces, 74 blocks is less than 30 minutes. The results indicate that the HACO-based algorithm can be a feasible and efficient optimization technique for CSP-BD, especially with large scale problems.

Heterogeneous activity causes a nonlinear increase in the group energy use of ant workers isolated from queen and brood.

PubMed

Ferral, Nolan; Holloway, Kyara; Li, Mingzhong; Yin, Zhaozheng; Hou, Chen

2018-06-01

Increasing evidence has shown that the energy use of ant colonies increases sublinearly with colony size so that large colonies consume less per capita energy than small colonies. It has been postulated that social environment (e.g., in the presence of queen and brood) is critical for the sublinear group energetics, and a few studies of ant workers isolated from queens and brood observed linear relationships between group energetics and size. In this paper, we hypothesize that the sublinear energetics arise from the heterogeneity of activity in ant groups, that is, large groups have relatively more inactive members than small groups. We further hypothesize that the energy use of ant worker groups that are allowed to move freely increases more slowly than the group size even if they are isolated from queen and brood. Previous studies only provided indirect evidence for these hypotheses due to technical difficulties. In this study, we applied the automated behavioral monitoring and respirometry simultaneously on isolated worker groups for long time periods, and analyzed the image with the state-of-the-art algorithms. Our results show that when activity was not confined, large groups had lower per capita energy use, a lower percentage of active members, and lower average walking speed than small groups; while locomotion was confined, however, the per capita energy use was a constant regardless of the group size. The quantitative analysis shows a direct link between variation in group energy use and the activity level of ant workers when isolated from queen and brood. © 2016 Institute of Zoology, Chinese Academy of Sciences.

Swarm Intelligence in Text Document Clustering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Xiaohui; Potok, Thomas E

2008-01-01

Social animals or insects in nature often exhibit a form of emergent collective behavior. The research field that attempts to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insect colonies is called Swarm Intelligence. Compared to the traditional algorithms, the swarm algorithms are usually flexible, robust, decentralized and self-organized. These characters make the swarm algorithms suitable for solving complex problems, such as document collection clustering. The major challenge of today's information society is being overwhelmed with information on any topic they are searching for. Fast and high-quality document clustering algorithms play an important role inmore » helping users to effectively navigate, summarize, and organize the overwhelmed information. In this chapter, we introduce three nature inspired swarm intelligence clustering approaches for document clustering analysis. These clustering algorithms use stochastic and heuristic principles discovered from observing bird flocks, fish schools and ant food forage.« less

DIRBoost-an algorithm for boosting deformable image registration: application to lung CT intra-subject registration.

PubMed

Muenzing, Sascha E A; van Ginneken, Bram; Viergever, Max A; Pluim, Josien P W

2014-04-01

We introduce a boosting algorithm to improve on existing methods for deformable image registration (DIR). The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well known in the field of machine learning. DIRBoost utilizes a method for automatic registration error detection to obtain estimates of local registration quality. All areas detected as erroneously registered are subjected to boosting, i.e. undergo iterative registrations by employing boosting masks on both the fixed and moving image. We validated the DIRBoost algorithm on three different DIR methods (ANTS gSyn, NiftyReg, and DROP) on three independent reference datasets of pulmonary image scan pairs. DIRBoost reduced registration errors significantly and consistently on all reference datasets for each DIR algorithm, yielding an improvement of the registration accuracy by 5-34% depending on the dataset and the registration algorithm employed. Copyright © 2014 Elsevier B.V. All rights reserved.

The role of tending ants in host plant selection and egg parasitism of two facultative myrmecophilous butterflies.

PubMed

Bächtold, Alexandra; Alves-Silva, Estevão; Kaminski, Lucas A; Del-Claro, Kleber

2014-11-01

Ovipositing adult females of myrmecophilous lycaenids are expected to select plants based on ant presence in order to maximize the survivorship of immature stages. Usually, larvae feed ants with honey-like solutions and, in turn, ants ward off parasitoids. Nonetheless, a rarely investigated approach is whether ant partners can also extend their protective behavior towards lycaenids eggs. Here, we investigated the ant-related oviposition pattern of Allosmaitia strophius and Rekoa marius; then, we compared egg parasitism according to the presence of ants. Lycaenid oviposition and egg parasitism (in percent) were experimentally compared in ant-present and ant-excluded treatments. The study plant, Heteropterys byrsonimifolia, is an extrafloral nectaried shrub which supports several ant species. We sampled 280 eggs, of which 39.65 % belonged to A. strophius and 60.35 % to R. marius. Both lycaenids eggs were significantly more abundant on branches with ants, especially those with Camponotus crassus and Camponotus blandus, two ant species known to attend to lycaenids. A. strophius and R. marius parasitism was 4.5- and 2.4-fold higher, respectively, in ant-present treatments, but the results were not statistically significant. Our study shows that ant-mediated host plant selection in lycaenids might be much more widespread than previously thought, and not restricted to obligate myrmecophilous species. Tending ants may be inefficient bodyguards of lycaenid eggs, because unlike larvae which release sugared liquids, eggs do not offer obvious rewards to ants. Ants can ward off parasitoids of larvae, as observed elsewhere, but our findings show that positive ant-lycaenid interactions are conditional and depend on immature ontogeny.

Reassembling the Information Technology Innovation Process: An Actor Network Theory Method for Managing the Initiation, Production, and Diffusion of Innovations

NASA Astrophysics Data System (ADS)

Zendejas, Gerardo; Chiasson, Mike

This paper will propose and explore a method to enhance focal actors' abilities to enroll and control the many social and technical components interacting during the initiation, production, and diffusion of innovations. The reassembling and stabilizing of such components is the challenging goal of the focal actors involved in these processes. To address this possibility, a healthcare project involving the initiation, production, and diffusion of an IT-based innovation will be influenced by the researcher, using concepts from actor network theory (ANT), within an action research methodology (ARM). The experiences using this method, and the nature of enrolment and translation during its use, will highlight if and how ANT can provide a problem-solving method to help assemble the social and technical actants involved in the diffusion of an innovation. Finally, the paper will discuss the challenges and benefits of implementing such methods to attain widespread diffusion.

Swarmathon 2017

NASA Image and Video Library

2017-04-19

A cube identified with an AprilTag, similar to a barcode, is delivered to a "home" square in the middle of a competition arena during the Swarmathon competition. At the Kennedy Space Center Visitor Complex, student teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food.

Polarized light use in the nocturnal bull ant, Myrmecia midas.

PubMed

Freas, Cody A; Narendra, Ajay; Lemesle, Corentin; Cheng, Ken

2017-08-01

Solitary foraging ants have a navigational toolkit, which includes the use of both terrestrial and celestial visual cues, allowing individuals to successfully pilot between food sources and their nest. One such celestial cue is the polarization pattern in the overhead sky. Here, we explore the use of polarized light during outbound and inbound journeys and with different home vectors in the nocturnal bull ant, Myrmecia midas . We tested foragers on both portions of the foraging trip by rotating the overhead polarization pattern by ±45°. Both outbound and inbound foragers responded to the polarized light change, but the extent to which they responded to the rotation varied. Outbound ants, both close to and further from the nest, compensated for the change in the overhead e-vector by about half of the manipulation, suggesting that outbound ants choose a compromise heading between the celestial and terrestrial compass cues. However, ants returning home compensated for the change in the e-vector by about half of the manipulation when the remaining home vector was short (1-2 m) and by more than half of the manipulation when the remaining vector was long (more than 4 m). We report these findings and discuss why weighting on polarization cues change in different contexts.

Comparison of African and North American velvet ant mimicry complexes: Another example of Africa as the 'odd man out'.

PubMed

Wilson, Joseph S; Pan, Aaron D; Limb, Erica S; Williams, Kevin A

2018-01-01

Africa has the most tropical and subtropical land of any continent, yet has relatively low species richness in several taxa. This depauperate nature of the African tropical fauna and flora has led some to call Africa the "odd man out." One exception to this pattern is velvet ants (Hymenoptera: Mutillidae), wingless wasps that are known for Müllerian mimicry. While North American velvet ants form one of the world's largest mimicry complexes, mimicry in African species has not been investigated. Here we ask do African velvet ant Müllerian mimicry rings exist, and how do they compare to the North American complex. We then explore what factors might contribute to the differences in mimetic diversity between continents. To investigate this we compared the color patterns of 304 African velvet ant taxa using nonmetric multidimensional scaling (NMDS). We then investigated distributions of each distinct mimicry ring. Finally, we compared lizard diversity and ecoregion diversity on the two continents. We found that African female velvet ants form four Müllerian rings, which is half the number of North American rings. This lower mimetic diversity could be related to the relatively lower diversity of insectivorous lizard species or to the lower number of distinct ecoregions in Africa compared to North America.

Polarized light use in the nocturnal bull ant, Myrmecia midas

PubMed Central

Lemesle, Corentin; Cheng, Ken

2017-01-01

Solitary foraging ants have a navigational toolkit, which includes the use of both terrestrial and celestial visual cues, allowing individuals to successfully pilot between food sources and their nest. One such celestial cue is the polarization pattern in the overhead sky. Here, we explore the use of polarized light during outbound and inbound journeys and with different home vectors in the nocturnal bull ant, Myrmecia midas. We tested foragers on both portions of the foraging trip by rotating the overhead polarization pattern by ±45°. Both outbound and inbound foragers responded to the polarized light change, but the extent to which they responded to the rotation varied. Outbound ants, both close to and further from the nest, compensated for the change in the overhead e-vector by about half of the manipulation, suggesting that outbound ants choose a compromise heading between the celestial and terrestrial compass cues. However, ants returning home compensated for the change in the e-vector by about half of the manipulation when the remaining home vector was short (1−2 m) and by more than half of the manipulation when the remaining vector was long (more than 4 m). We report these findings and discuss why weighting on polarization cues change in different contexts. PMID:28879002

Improving liquid bait programs for Argentine ant control: bait station density.

PubMed

Nelson, Erik H; Daane, Kent M

2007-12-01

Argentine ants, Linepithema humile (Mayr), have a positive effect on populations of mealybugs (Pseudococcus spp.) in California vineyards. Previous studies have shown reductions in both ant activity and mealybug numbers after liquid ant baits were deployed in vineyards at densities of 85-620 bait stations/ha. However, bait station densities may need to be <85 bait stations/ha before bait-based strategies for ant control are economically comparable to spray-based insecticide treatments-a condition that, if met, will encourage the commercial adoption of liquid baits for ant control. This research assessed the effectiveness of baits deployed at lower densities. Two field experiments were conducted in commercial vineyards. In experiment 1, baits were deployed at 54-225 bait stations/ha in 2005 and 2006. In experiment 2, baits were deployed at 34-205 bait stations/ha in 2006 only. In both experiments, ant activity and the density of mealybugs in grape fruit clusters at harvest time declined with increasing bait station density. In 2005 only, European fruit lecanium scale [Parthenolecanium corni (Bouché)] were also present in fruit clusters, and scale densities were negatively related to bait station density. The results indicate that the amount of ant and mealybug control achieved by an incremental increase in the number of bait stations per hectare is constant across a broad range of bait station densities. The results are discussed in the context of commercializing liquid ant baits to provide a more sustainable Argentine ant control strategy.

Les traumatismes de l’étage antérieur de la base du crane: à propos d'une série de 136 cas

PubMed Central

Bouchaouch, Abdelali; Hassani, Fahd Derkaoui; Abboud, Hilal; Mukengeshay, Jeff Ntalaja; El Fatemi, Nizare; Gana, Rachid; El Maaqili, Moulay Rchid; El Abbadi, Najia; Bellakhdar, Fouad

2015-01-01

Les traumatismes de l’étage antérieur de la base du crâne représentent 15 à 20% des traumatismes crâniens en général. Ils menacent les structures neuro-encéphaliques sus jacentes et sont très souvent responsables de brèches ostéo-méningées exposant au risque infectieux. Notre travail a concerné 136 dossiers exploitables de traumatisme de l’étage antérieur de la base du crâne colligés sur une période de 10 ans entre janvier 2003 et décembre 2012. Le diagnostic a été suspecté devant les signes cliniques évocateurs (ecchymose péri-orbitaire, rhinorrhée…) et a été confirmé dans la plupart des cas par la TDM. Le traitement idéal est la fermeture chirurgicale de la brèche en association aux moyens médicaux (vaccination, anti-épileptiques, mesures de réanimation…) Le moment idéal de la réparation est au-delà de la 72ème heure après la diminution de l'oedème cérébral en cas d'absence d'une lésion intracrânienne nécessitant une intervention en urgence. Notre équipe ne pratiquant pas la voie endoscopique, l'abord frontal est souvent indiqué. Le pronostic dépend des lésions cérébrales associées et surtout de la présence d'une brèche dont le diagnostic et la réparation doivent être les plus rapides et les plus précis possibles. Ainsi toute rhinorrhée post-traumatique nécessite une exploration systématique, le timing idéal: c'est la disparition de l'oedème cérébral pour faciliter l'exploration, ceci est en général possible à partir de la 72ème heure sauf dans les cas associés à une autre lésion intra crânienne nécessitant une exploration en urgence. PMID:26327992

Optimization of Straight Cylindrical Turning Using Artificial Bee Colony (ABC) Algorithm

NASA Astrophysics Data System (ADS)

Prasanth, Rajanampalli Seshasai Srinivasa; Hans Raj, Kandikonda

2017-04-01

Artificial bee colony (ABC) algorithm, that mimics the intelligent foraging behavior of honey bees, is increasingly gaining acceptance in the field of process optimization, as it is capable of handling nonlinearity, complexity and uncertainty. Straight cylindrical turning is a complex and nonlinear machining process which involves the selection of appropriate cutting parameters that affect the quality of the workpiece. This paper presents the estimation of optimal cutting parameters of the straight cylindrical turning process using the ABC algorithm. The ABC algorithm is first tested on four benchmark problems of numerical optimization and its performance is compared with genetic algorithm (GA) and ant colony optimization (ACO) algorithm. Results indicate that, the rate of convergence of ABC algorithm is better than GA and ACO. Then, the ABC algorithm is used to predict optimal cutting parameters such as cutting speed, feed rate, depth of cut and tool nose radius to achieve good surface finish. Results indicate that, the ABC algorithm estimated a comparable surface finish when compared with real coded genetic algorithm and differential evolution algorithm.

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

ALI (Autonomous Lunar Investigator): Revolutionary Approach to Exploring the Moon with Addressable Reconfigurable Technology

NASA Astrophysics Data System (ADS)

Clark, P. E.; Curtis, S. A.; Rilee, M. L.; Floyd, S. R.

2005-03-01

Addressable Reconfigurable Technology (ART), conceived for future ANTS (Autonomous Nanotechnology Swarm) Architectures, is now implemented as Autonomous Lunar Investigator (ALI) rovers, a mission concept allowing autonomous exploration of the lunar farside and poles within 10 years.

CrossTalk. The Journal of Defense Software Engineering. Volume 26, Number 1

DTIC Science & Technology

2013-02-01

ANTS) mission that may be used to explore the asteroid belt. Basically, the mission entails 1,000 two-pound autonomous space vehicles that will be...be used to collect data from asteroids that will be periodically transmitted back to earth. For autonomous operation, the ANTS will need to...priory information. In other words, these indicators are used to support any one of a number of situation assessments that have been predeter- mined

Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

PubMed Central

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm. PMID:25691895

Developing Software for NASA Missions in the New Millennia

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Rouff, Christopher; Hinchey, Mike

2004-01-01

NASA is working on new mission concepts for exploration of the solar system. The concepts for these missions include swarms of hundreds of cooperating intelligent spacecraft which will be able to work in teams and gather more data than current single spacecraft missions. These spacecraft will not only have to operate independently for long periods of time on their own and in teams, but will also need to have autonomic properties of self healing, self configuring, self optimizing and self protecting for them to survive in the harsh space environment. Software for these types of missions has never been developed before and represents some of the challenges of software development in the new millennia. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm missions NASA is considering. The ANTS mission will use a swarm of one thousand pico-spacecraft that weigh less than five pounds. Using an insect colony analog, ANTS will explore the asteroid belt and catalog the mass, density, morphology, and chemical composition of the asteroids. Due to the size of the spacecraft, each will only carry a single miniaturized science instrument which will require them to cooperate in searching for asteroids that are of scientific interest. This article also discusses the ANTS mission, the properties the spacecraft will need and how that will effect future software development.

The Role of Symbiont Genetic Distance and Potential Adaptability in Host Preference Towards Pseudonocardia Symbionts in Acromyrmex Leaf-Cutting Ants

PubMed Central

Poulsen, Michael; Maynard, Janielle; Roland, Damien L; Currie, Cameron R

2011-01-01

Fungus-growing ants display symbiont preference in behavioral assays, both towards the fungus they cultivate for food and Actinobacteria they maintain on their cuticle for antibiotic production against parasites. These Actinobacteria, genus Pseudonocardia Henssen (Pseudonocardiacea: Actinomycetales), help defend the ants' fungal mutualist from specialized parasites. In Acromyrmex Mayr (Hymenoptera: Formicidae) leaf-cutting ants, individual colonies maintain either a single or a few strains of Pseudonocardia, and the symbiont is primarily vertically transmitted between generations by colony-founding queens. A recent report found that Acromyrmex workers are able to differentiate between their native Pseudonocardia strain and non-native strains isolated from sympatric or allopatric Acromyrmex species, and show preference for their native strain. Here we explore worker preference when presented with two non-native strains, elucidating the role of genetic distance on preference between strains and Pseudonocardia origin. Our findings suggest that ants tend to prefer bacteria more closely related to their native bacterium and that genetic similarity is probably more important than whether symbionts are ant-associated or free-living. Preliminary findings suggest that when continued exposure to a novel Pseudonocardia strain occurs, ant symbiont preference is potentially adaptable, with colonies apparently being able to alter symbiont preference over time. These findings are discussed in relation to the role of adaptive recognition, potential ecological flexibility in symbiont preference, and more broadly, in relation to self versus non-self recognition. PMID:22225537

A SAT Based Effective Algorithm for the Directed Hamiltonian Cycle Problem

NASA Astrophysics Data System (ADS)

Jäger, Gerold; Zhang, Weixiong

The Hamiltonian cycle problem (HCP) is an important combinatorial problem with applications in many areas. While thorough theoretical and experimental analyses have been made on the HCP in undirected graphs, little is known for the HCP in directed graphs (DHCP). The contribution of this work is an effective algorithm for the DHCP. Our algorithm explores and exploits the close relationship between the DHCP and the Assignment Problem (AP) and utilizes a technique based on Boolean satisfiability (SAT). By combining effective algorithms for the AP and SAT, our algorithm significantly outperforms previous exact DHCP algorithms including an algorithm based on the award-winning Concorde TSP algorithm.

A framework for using ant colony optimization to schedule environmental flow management alternatives for rivers, wetlands, and floodplains

NASA Astrophysics Data System (ADS)

Szemis, J. M.; Maier, H. R.; Dandy, G. C.

2012-08-01

Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.

Specific, non-nutritional association between an ascomycete fungus and Allomerus plant-ants.

PubMed

Ruiz-González, Mario X; Malé, Pierre-Jean G; Leroy, Céline; Dejean, Alain; Gryta, Hervé; Jargeat, Patricia; Quilichini, Angélique; Orivel, Jérôme

2011-06-23

Ant-fungus associations are well known from attine ants, whose nutrition is based on a symbiosis with basidiomycete fungi. Otherwise, only a few non-nutritional ant-fungus associations have been recorded to date. Here we focus on one of these associations involving Allomerus plant-ants that build galleried structures on their myrmecophytic hosts in order to ambush prey. We show that this association is not opportunistic because the ants select from a monophyletic group of closely related fungal haplotypes of an ascomycete species from the order Chaetothyriales that consistently grows on and has been isolated from the galleries. Both the ants' behaviour and an analysis of the genetic population structure of the ants and the fungus argue for host specificity in this interaction. The ants' behaviour reveals a major investment in manipulating, growing and cleaning the fungus. A molecular analysis of the fungus demonstrates the widespread occurrence of one haplotype and many other haplotypes with a lower occurrence, as well as significant variation in the presence of these fungal haplotypes between areas and ant species. Altogether, these results suggest that such an interaction might represent an as-yet undescribed type of specific association between ants and fungus in which the ants cultivate fungal mycelia to strengthen their hunting galleries.

A phylogenetic perspective on the association between ants (Hymenoptera: Formicidae) and black yeasts (Ascomycota: Chaetothyriales).

PubMed

Vasse, Marie; Voglmayr, Hermann; Mayer, Veronika; Gueidan, Cécile; Nepel, Maximilian; Moreno, Leandro; de Hoog, Sybren; Selosse, Marc-André; McKey, Doyle; Blatrix, Rumsaïs

2017-03-15

The frequency and the geographical extent of symbiotic associations between ants and fungi of the order Chaetothyriales have been highlighted only recently. Using a phylogenetic approach based on seven molecular markers, we showed that ant-associated Chaetothyriales are scattered through the phylogeny of this order. There was no clustering according to geographical origin or to the taxonomy of the ant host. However, strains tended to be clustered according to the type of association with ants: strains from ant-made carton and strains from plant cavities occupied by ants ('domatia') rarely clustered together. Defining molecular operational taxonomic units (MOTUs) with an internal transcribed spacer sequence similarity cut-off of 99% revealed that a single MOTU could be composed of strains collected from various ant species and from several continents. Some ant-associated MOTUs also contained strains isolated from habitats other than ant-associated structures. Altogether, our results suggest that the degree of specialization of the interactions between ants and their fungal partners is highly variable. A better knowledge of the ecology of these interactions and a more comprehensive sampling of the fungal order are needed to elucidate the evolutionary history of mutualistic symbioses between ants and Chaetothyriales. © 2017 The Author(s).

Gaseous templates in ant nests.

PubMed

Cox, M D; Blanchard, G B

2000-05-21

We apply a diffusion model to the atmosphere of ant nests. With particular reference to carbon dioxide (CO2), we explore analytically and numerically the spatial and temporal patterns of brood- or worker-produced gases in nests. The maximum concentration within a typical one-chamber ant nest with approximately 200 ants can reach 12.5 times atmospheric concentration, reaching 95% of equilibrium concentrations within 15 min. Maximum concentration increases with increasing number of ants in the nest (or production rate of the gas), distance between the centre of the nest ants and the nest entrance, entrance length, wall thickness, and with decreasing entrance width, wall permeability and diffusion coefficient. The nest can be divided into three qualitatively distinct regions according to the shape of the gradient: a plateau of high concentration in the back half of the nest; an intermediate region of increasingly steep gradient towards the entrance; and a steep linear gradient in the entrance tunnel. These regions are robust to changes in gas concentrations, but vary with changes in nest architecture. The pattern of diffusing gases contains information about position and orientation relative to gas sources and sinks, and about colony state, including colony size, activity state and aspects of nest architecture. We discuss how this diffusion pattern may act as a "dynamic template", providing local cues which trigger behavioural acts appropriate to colony needs, which in turn may feed back to changes in the gas template. In particular, wall building occurs along lines of similar concentration for a variety of nest geometries; there is surprising convergence between the period of cycles of synchronously active ants and the time taken for CO2 levels to equilibrate; and the qualitatively distinct regions of the "dynamic template" correspond to regions occupied by different groups of ants.

Swarmathon 2017

NASA Image and Video Library

2017-04-20

In the Swarmathon competition at the Kennedy Space Center Visitor Complex, students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of cubes with AprilTags, similar to barcodes. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food.

Groups have a larger cognitive capacity than individuals.

PubMed

Sasaki, Takao; Pratt, Stephen C

2012-10-09

Increasing the number of options can paradoxically lead to worse decisions, a phenomenon known as cognitive overload [1]. This happens when an individual decision-maker attempts to digest information exceeding its processing capacity. Highly integrated groups, such as social insect colonies, make consensus decisions that combine the efforts of many members, suggesting that these groups can overcome individual limitations [2-4]. Here we report that an ant colony choosing a new nest site is less vulnerable to cognitive overload than an isolated ant making this decision on her own. We traced this improvement to differences in individual behavior. In whole colonies, each ant assesses only a small subset of available sites, and the colony combines their efforts to thoroughly explore all options. An isolated ant, on the other hand, must personally assess a larger number of sites to approach the same level of option coverage. By sharing the burden of assessment, the colony avoids overtaxing the abilities of its members. Copyright © 2012 Elsevier Ltd. All rights reserved.

In Situ Surveying of Saturn's Rings

NASA Technical Reports Server (NTRS)

Clark, P. E.; Curtis, S. A.; Rilee, M. L.; Cheung, C.

2004-01-01

The Saturn Autonomous Ring Array (SARA) mission concept is a new application for the Autonomous Nano-Technology Swarm (ANTS) architecture, a paradigm being developed for exploration of high surface area and/or multibody targets to minimize costs and maximize effectiveness of survey operations. Systems designed with ANTS architecture are built from potentially very large numbers of highly autonomous, yet socially interactive, specialists, in approximately ten specialist classes. Here, we analyze requirements for such a mission as well as specialized autonomous operations which would support this application.

Linear antenna array optimization using flower pollination algorithm.

PubMed

Saxena, Prerna; Kothari, Ashwin

2016-01-01

Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.

Urban habitat complexity affects species richness but not environmental filtering of morphologically-diverse ants

PubMed Central

Nash, Michael A.; Christie, Fiona J.; Hahs, Amy K.; Livesley, Stephen J.

2015-01-01

Habitat complexity is a major determinant of structure and diversity of ant assemblages. Following the size-grain hypothesis, smaller ant species are likely to be advantaged in more complex habitats compared to larger species. Habitat complexity can act as an environmental filter based on species size and morphological traits, therefore affecting the overall structure and diversity of ant assemblages. In natural and semi-natural ecosystems, habitat complexity is principally regulated by ecological successions or disturbance such as fire and grazing. Urban ecosystems provide an opportunity to test relationships between habitat, ant assemblage structure and ant traits using novel combinations of habitat complexity generated and sustained by human management. We sampled ant assemblages in low-complexity and high-complexity parks, and high-complexity woodland remnants, hypothesizing that (i) ant abundance and species richness would be higher in high-complexity urban habitats, (ii) ant assemblages would differ between low- and high-complexity habitats and (iii) ants living in high-complexity habitats would be smaller than those living in low-complexity habitats. Contrary to our hypothesis, ant species richness was higher in low-complexity habitats compared to high-complexity habitats. Overall, ant assemblages were significantly different among the habitat complexity types investigated, although ant size and morphology remained the same. Habitat complexity appears to affect the structure of ant assemblages in urban ecosystems as previously observed in natural and semi-natural ecosystems. However, the habitat complexity filter does not seem to be linked to ant morphological traits related to body size. PMID:26528416

Differential Recruitment of Camponotus femoratus (Fabricius) Ants in Response to Ant Garden Herbivory.

PubMed

Vicente, R E; Dáttilo, W; Izzo, T J

2014-12-01

Although several studies have shown that ants can recognize chemical cues from their host plants in ant-plant systems, it is poorly demonstrated in ant gardens (AGs). In this interaction, ant species constantly interact with various epiphyte species. Therefore, it is possible to expect a convergence of chemical signals released by plants that could be acting to ensure that ants are able to recognize and defend epiphyte species frequently associated with AGs. In this study, it was hypothesized that ants recognize and differentiate among chemical stimuli released by AG epiphytes and non-AG epiphytes. We experimentally simulated leaf herbivore damage on three epiphyte species restricted to AGs and a locally abundant understory herb, Piper hispidum, in order to quantify the number of recruited Camponotus femoratus (Fabricius) defenders. When exposed to the AG epiphytes Peperomia macrostachya and Codonanthe uleana leaves, it was observed that the recruitment of C. femoratus workers was, on average, respectively 556% and 246% higher than control. However, the number of ants recruited by the AG epiphyte Markea longiflora or by the non-AG plant did not differ from paper pieces. This indicated that ants could discern between chemicals released by different plants, suggesting that ants can select better plants. These results can be explained by evolutionary process acting on both ants' capability in discerning plants' chemical compounds (innate attraction) or by ants' learning based on the epiphyte frequency in AGs (individual experience). To disentangle an innate behavior, a product of classical coevolutionary process, from an ant's learned behavior, is a complicated but important subject to understand in the evolution of ant-plant mutualisms.

Design of Learning Model of Logic and Algorithms Based on APOS Theory

ERIC Educational Resources Information Center

Hartati, Sulis Janu

2014-01-01

This research questions were "how do the characteristics of learning model of logic & algorithm according to APOS theory" and "whether or not these learning model can improve students learning outcomes". This research was conducted by exploration, and quantitative approach. Exploration used in constructing theory about the…

The Haleakala Argentine ant project: a synthesis of past research and prospects for the future

USGS Publications Warehouse

Krushelnycky, Paul; Haines, William; Loope, Lloyd; Van Gelder, Ellen

2011-01-01

1. The Haleakala Argentine Ant Project is an ongoing effort to study the ecology of the invasive Argentine ant in the park, and if possible to develop a strategy to control this destructive species. 2. Past research has demonstrated that the Argentine ant causes very significant impacts on native arthropods where it invades, threatening a large portion of the park’s biodiversity in subalpine shrubland and alpine aeolian ecosystems. 3. Patterns of spread over the past 30+ years indicate that the invasion process is influenced to a substantial degree by abiotic factors such as elevation, rainfall and temperature, and that the ant has not reached its potential range. Predictions of total range in the park suggest that it has only invaded a small fraction of available suitable habitat, confirming that this species is one of most serious threats to the park’s natural resources. 4. Numerous experiments have been conducted since 1994 in an attempt to develop a method for eradicating the Argentine ant at Haleakala using pesticidal ant baits. Thirty baits have been screened for attractiveness to ants in the park, and ten of these were tested for effectiveness of control in field plots. While some of these baits have been very effective in reducing numbers of ants, none has been able to eliminate all nests in experimental plots. 5. Research into a secondary management goal of ant population containment was initiated in 1996. By treating only expanding margins of the park’s two ant populations with an ant pesticide, rates of outward spread were substantially reduced in some areas. While this strategy was implemented from 1997 to 2004, it was ultimately discontinued after 2004 because of the difficulty and insufficient effectiveness of the technique. 6. In order to achieve the types of results necessary for eradication, the project would probably need to explore the possibility of developing a specialized bait, rather than relying on a commercially produced bait. An alternative would be to pursue approval to use Xstinguish bait, a commercial bait manufactured in New Zealand and not registered for use in the US, which has yielded good results against Argentine ants. Either route would involve significant regulatory hurdles. Because the baits ultimately used would likely be liquid or paste in form, there would also be major logistical challenges in devising methods to successfully apply the baits across the two large ant populations at Haleakala.

Aggression and Niche-Separation in Ants: A Suggestion for a Student Project

ERIC Educational Resources Information Center

Bates, Martin R.

1973-01-01

Based upon British studies, suggests how the coexistence of different ant species can occur, and discusses competition and niche-separation in relation to a study made in Norfolk. Recommends the elucidation of the mechanisms of niche-separation in ants as an ideal student project. (JR)

Comparison of African and North American velvet ant mimicry complexes: Another example of Africa as the ‘odd man out’

PubMed Central

Limb, Erica S.; Williams, Kevin A.

2018-01-01

Africa has the most tropical and subtropical land of any continent, yet has relatively low species richness in several taxa. This depauperate nature of the African tropical fauna and flora has led some to call Africa the “odd man out.” One exception to this pattern is velvet ants (Hymenoptera: Mutillidae), wingless wasps that are known for Müllerian mimicry. While North American velvet ants form one of the world’s largest mimicry complexes, mimicry in African species has not been investigated. Here we ask do African velvet ant Müllerian mimicry rings exist, and how do they compare to the North American complex. We then explore what factors might contribute to the differences in mimetic diversity between continents. To investigate this we compared the color patterns of 304 African velvet ant taxa using nonmetric multidimensional scaling (NMDS). We then investigated distributions of each distinct mimicry ring. Finally, we compared lizard diversity and ecoregion diversity on the two continents. We found that African female velvet ants form four Müllerian rings, which is half the number of North American rings. This lower mimetic diversity could be related to the relatively lower diversity of insectivorous lizard species or to the lower number of distinct ecoregions in Africa compared to North America. PMID:29298332

Out on a limb: Thermal microenvironments in the tropical forest canopy and their relevance to ants.

PubMed

Stark, Alyssa Y; Adams, Benjamin J; Fredley, Jennifer L; Yanoviak, Stephen P

2017-10-01

Small, cursorial ectotherms like ants often are immersed in the superheated air layers that develop millimeters above exposed, insolated surfaces (i.e., the thermal boundary layer). We quantified the thermal microenvironments around tree branches in the tropical rainforest canopy, and explored the effects of substrate color on the internal body temperature and species composition of arboreal ants. Branch temperatures during the day (09:00-16:00) were hottest (often > 50°C) and most variable on the upper surface, while the lowest and least variable temperatures occurred on the underside. Temperatures on black substrates declined with increasing distance above the surface in both the field and the laboratory. By contrast, a micro-scale temperature inversion occurred above white substrates. Wind events (ca. 2ms -1 ) eliminated these patterns. Internal temperatures of bodies of Cephalotes atratus workers experimentally heated in the laboratory were 6°C warmer on white vs. black substrates, and 6°C cooler than ambient in windy conditions. The composition of ant species foraging at baits differed between black-painted and unpainted tree branches, with a tendency for smaller ants to avoid the significantly hotter black surfaces. Collectively, these outcomes show that ants traversing canopy branches experience very heterogeneous thermal microenvironments that are partly influenced in predictable ways by branch surface coloration and breezy conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performance of the species-typical alarm response in young workers of the ant Myrmica sabuleti (Hymenoptera: Formicidae) is induced by interactions with mature workers.

PubMed

Cammaerts, Marie-Claire

2014-01-01

Young workers of the ant Myrmica sabuleti (Hymenoptera: Formicidae) Meinert 1861 perceived nestmate alarm pheromone but did not display normal alarm behavior (orientation toward the source of emission, increased running speed). They changed their initial behavior when in the presence of older nestmates exhibiting normal alarm behavior. Four days later, the young ants exhibited an imperfect version of normal alarm behavior. This change of behavior did not occur in young ants, which were not exposed to older ants reacting to alarm pheromone. Queen ants perceived the alarm pheromone and, after a few seconds, moved toward its source. Thus, the ants' ability to sense the alarm pheromone and to identify it as an alarm signal is native, while the adult alarm reaction is acquired over time (= age based polyethism) by young ants. It is possible that the change in behavior observed in young ants could be initiated and/or enhanced (via experience-induced developmental plasticity, learning, and/or other mechanisms) by older ants exhibiting alarm behavior. © The Author 2014. Published by Oxford University Press on behalf of the Entomological Society of America.

Performance of the Species-Typical Alarm Response in Young Workers of the Ant Myrmica sabuleti (Hymenoptera: Formicidae) Is Induced by Interactions with Mature Workers

PubMed Central

Cammaerts, Marie-Claire

2014-01-01

Abstract Young workers of the ant Myrmica sabuleti (Hymenoptera: Formicidae) Meinert 1861 perceived nestmate alarm pheromone but did not display normal alarm behavior (orientation toward the source of emission, increased running speed). They changed their initial behavior when in the presence of older nestmates exhibiting normal alarm behavior. Four days later, the young ants exhibited an imperfect version of normal alarm behavior. This change of behavior did not occur in young ants, which were not exposed to older ants reacting to alarm pheromone. Queen ants perceived the alarm pheromone and, after a few seconds, moved toward its source. Thus, the ants’ ability to sense the alarm pheromone and to identify it as an alarm signal is native, while the adult alarm reaction is acquired over time (= age based polyethism) by young ants. It is possible that the change in behavior observed in young ants could be initiated and/or enhanced (via experience-induced developmental plasticity, learning, and/or other mechanisms) by older ants exhibiting alarm behavior. PMID:25525102

Disentangling the diversity of arboreal ant communities in tropical forest trees.

PubMed

Klimes, Petr; Fibich, Pavel; Idigel, Cliffson; Rimandai, Maling

2015-01-01

Tropical canopies are known for their high abundance and diversity of ants. However, the factors which enable coexistence of so many species in trees, and in particular, the role of foragers in determining local diversity, are not well understood. We censused nesting and foraging arboreal ant communities in two 0.32 ha plots of primary and secondary lowland rainforest in New Guinea and explored their species diversity and composition. Null models were used to test if the records of species foraging (but not nesting) in a tree were dependent on the spatial distribution of nests in surrounding trees. In total, 102 ant species from 389 trees occurred in the primary plot compared with only 50 species from 295 trees in the secondary forest plot. However, there was only a small difference in mean ant richness per tree between primary and secondary forest (3.8 and 3.3 sp. respectively) and considerably lower richness per tree was found only when nests were considered (1.5 sp. in both forests). About half of foraging individuals collected in a tree belonged to species which were not nesting in that tree. Null models showed that the ants foraging but not nesting in a tree are more likely to nest in nearby trees than would be expected at random. The effects of both forest stage and tree size traits were similar regardless of whether only foragers, only nests, or both datasets combined were considered. However, relative abundance distributions of species differed between foraging and nesting communities. The primary forest plot was dominated by native ant species, whereas invasive species were common in secondary forest. This study demonstrates the high contribution of foragers to arboreal ant diversity, indicating an important role of connectivity between trees, and also highlights the importance of primary vegetation for the conservation of native ant communities.

Disentangling the Diversity of Arboreal Ant Communities in Tropical Forest Trees

PubMed Central

Klimes, Petr; Fibich, Pavel; Idigel, Cliffson; Rimandai, Maling

2015-01-01

Tropical canopies are known for their high abundance and diversity of ants. However, the factors which enable coexistence of so many species in trees, and in particular, the role of foragers in determining local diversity, are not well understood. We censused nesting and foraging arboreal ant communities in two 0.32 ha plots of primary and secondary lowland rainforest in New Guinea and explored their species diversity and composition. Null models were used to test if the records of species foraging (but not nesting) in a tree were dependent on the spatial distribution of nests in surrounding trees. In total, 102 ant species from 389 trees occurred in the primary plot compared with only 50 species from 295 trees in the secondary forest plot. However, there was only a small difference in mean ant richness per tree between primary and secondary forest (3.8 and 3.3 sp. respectively) and considerably lower richness per tree was found only when nests were considered (1.5 sp. in both forests). About half of foraging individuals collected in a tree belonged to species which were not nesting in that tree. Null models showed that the ants foraging but not nesting in a tree are more likely to nest in nearby trees than would be expected at random. The effects of both forest stage and tree size traits were similar regardless of whether only foragers, only nests, or both datasets combined were considered. However, relative abundance distributions of species differed between foraging and nesting communities. The primary forest plot was dominated by native ant species, whereas invasive species were common in secondary forest. This study demonstrates the high contribution of foragers to arboreal ant diversity, indicating an important role of connectivity between trees, and also highlights the importance of primary vegetation for the conservation of native ant communities. PMID:25714831

An intertebrate ecosystem engineer likely covered under the umbrella of sage-grouse conservation

USGS Publications Warehouse

Carlisle, Jason D.; Stewart, David R.; Chalfoun, Anna D.

2017-01-01

Conservation practitioners often rely on areas designed to protect species of greatest conservation priority to also conserve co-occurring species (i.e., the umbrella species concept). The extent to which vertebrate species may serve as suitable umbrellas for invertebrate species, however, has rarely been explored. Sage-grouse (Centrocercus spp.) have high conservation priority throughout much of the rangelands of western North America and are considered an umbrella species through which the conservation of entire rangeland ecosystems can be accomplished. Harvester ants are ecosystem engineers and play important roles in the maintenance and function of rangeland ecosystems. We compared indices of the abundance of western harvester ants (Pogonomyrmex occidentalis) and Greater Sage-Grouse (Centrocercus urophasianus) at 72 sites in central Wyoming, USA, in 2012. The abundance of harvester ant mounds was best predicted by a regression model that included a combination of local habitat characteristics and the abundance of sage-grouse. When controlling for habitat-related factors, areas with higher abundances of sage-grouse pellets (an index of sage-grouse abundance and/or habitat use) had higher abundances of ant mounds than areas with lower abundances of sage-grouse pellets. The causal mechanism underlying this positive relationship between sage-grouse and ant mound abundance at the fine scale could be indirect (e.g., both species prefer similar environmental conditions) or direct (e.g., sage-grouse prefer areas with a high abundance of ant mounds because ants are an important prey item during certain life stages). We observed no relationship between a broad-scale index of breeding sage-grouse density and the abundance of ant mounds. We suspect that consideration of the nonbreeding habitat of sage-grouse and finer-scale measures of sagegrouse abundance are critical to the utility of sage-grouse as an umbrella species for the conservation of harvester ants and their important role in rangeland ecosystems.

A Program Complexity Metric Based on Variable Usage for Algorithmic Thinking Education of Novice Learners

ERIC Educational Resources Information Center

Fuwa, Minori; Kayama, Mizue; Kunimune, Hisayoshi; Hashimoto, Masami; Asano, David K.

2015-01-01

We have explored educational methods for algorithmic thinking for novices and implemented a block programming editor and a simple learning management system. In this paper, we propose a program/algorithm complexity metric specified for novice learners. This metric is based on the variable usage in arithmetic and relational formulas in learner's…

Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks

NASA Astrophysics Data System (ADS)

Ji, Junzhong; Song, Xiangjing; Liu, Chunnian; Zhang, Xiuzhen

2013-08-01

Community structure detection in complex networks has been intensively investigated in recent years. In this paper, we propose an adaptive approach based on ant colony clustering to discover communities in a complex network. The focus of the method is the clustering process of an ant colony in a virtual grid, where each ant represents a node in the complex network. During the ant colony search, the method uses a new fitness function to percept local environment and employs a pheromone diffusion model as a global information feedback mechanism to realize information exchange among ants. A significant advantage of our method is that the locations in the grid environment and the connections of the complex network structure are simultaneously taken into account in ants moving. Experimental results on computer-generated and real-world networks show the capability of our method to successfully detect community structures.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Lee, Charles H.; Cheung, Kar-Ming

2012-01-01

In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.

A New Metaheuristic Algorithm for Long-Term Open-Pit Production Planning / Nowy meta-heurystyczny algorytm wspomagający długoterminowe planowanie produkcji w kopalni odkrywkowej

NASA Astrophysics Data System (ADS)

Sattarvand, Javad; Niemann-Delius, Christian

2013-03-01

Paper describes a new metaheuristic algorithm which has been developed based on the Ant Colony Optimisation (ACO) and its efficiency have been discussed. To apply the ACO process on mine planning problem, a series of variables are considered for each block as the pheromone trails that represent the desirability of the block for being the deepest point of the mine in that column for the given mining period. During implementation several mine schedules are constructed in each iteration. Then the pheromone values of all blocks are reduced to a certain percentage and additionally the pheromone value of those blocks that are used in defining the constructed schedules are increased according to the quality of the generated solutions. By repeated iterations, the pheromone values of those blocks that define the shape of the optimum solution are increased whereas those of the others have been significantly evaporated.

7 CFR 301.81-5 - Issuance of a certificate or limited permit.

Code of Federal Regulations, 2010 CFR

2010-01-01

... HEALTH INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant... spread of the imported fire ant; 5 and 5 An inspector may hold, seize, quarantine, treat, apply other... free of an imported fire ant infestation, based on his or her visual examination of the article; (ii...

7 CFR 301.81-5 - Issuance of a certificate or limited permit.

Code of Federal Regulations, 2011 CFR

2011-01-01

... HEALTH INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant... spread of the imported fire ant; 5 and 5 An inspector may hold, seize, quarantine, treat, apply other... free of an imported fire ant infestation, based on his or her visual examination of the article; (ii...

7 CFR 301.81-5 - Issuance of a certificate or limited permit.

Code of Federal Regulations, 2013 CFR

2013-01-01

... HEALTH INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant... spread of the imported fire ant; 5 and 5 An inspector may hold, seize, quarantine, treat, apply other... free of an imported fire ant infestation, based on his or her visual examination of the article; (ii...

7 CFR 301.81-5 - Issuance of a certificate or limited permit.

Code of Federal Regulations, 2014 CFR

2014-01-01

... HEALTH INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant... spread of the imported fire ant; 5 and 5 An inspector may hold, seize, quarantine, treat, apply other... free of an imported fire ant infestation, based on his or her visual examination of the article; (ii...

7 CFR 301.81-5 - Issuance of a certificate or limited permit.

Code of Federal Regulations, 2012 CFR

2012-01-01

... HEALTH INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant... spread of the imported fire ant; 5 and 5 An inspector may hold, seize, quarantine, treat, apply other... free of an imported fire ant infestation, based on his or her visual examination of the article; (ii...

New fossil ants in French Cretaceous amber (Hymenoptera: Formicidae)

NASA Astrophysics Data System (ADS)

Perrichot, Vincent; Nel, André; Néraudeau, Didier; Lacau, Sébastien; Guyot, Thierry

2008-02-01

Recent studies on the ant phylogeny are mainly based on the molecular analyses of extant subfamilies and do not include the extinct, only Cretaceous subfamily Sphecomyrminae. However, the latter is of major importance for ant relationships, as it is considered the most basal subfamily. Therefore, each new discovery of a Mesozoic ant is of high interest for improving our understanding of their early history and basal relationships. In this paper, a new sphecomyrmine ant, allied to the Burmese amber genus Haidomyrmex, is described from mid-Cretaceous amber of France as Haidomyrmodes mammuthus gen. and sp. n. The diagnosis of the tribe Haidomyrmecini is emended based on the new type material, which includes a gyne (alate female) and two incomplete workers. The genus Sphecomyrmodes, hitherto known by a single species from Burmese amber, is also reported and a new species described as S. occidentalis sp. n. after two workers remarkably preserved in a single piece of Early Cenomanian French amber. The new fossils provide additional information on early ant diversity and relationships and demonstrate that the monophyly of the Sphecomyrminae, as currently defined, is still weakly supported.

Food-plant niche selection rather than the presence of ant nests explains oviposition patterns in the myrmecophilous butterfly genus Maculinea.

PubMed

Thomas, J A; Elmes, G W

2001-03-07

It has been suggested that the socially parasitic butterfly Maculinea alcon detects ant odours before ovipositing on initial larval food plants near colonies of its obligate ant host Myrmica ruginodis. It has also been suggested that overcrowding on food plants near M. ruginodis is avoided by an ability to detect high egg loads, resulting in a switch to selecting plants near less suitable ant species. If confirmed, this hypothesis (H1) would have serious implications for the application of current population models aimed at the conservation of endangered Maculinea species, which are based on the null hypothesis (H0) that females randomly select food plants whose flower buds are at a precise phenological stage, making oviposition independent of ants. If H1 were wrong, practical management based upon its assumptions could lead to the extinction of protected populations. We present data for the five European species of Maculinea which show that (i) each oviposits on a phenologically restricted flower-bud stage, which accounts for the apparent host-ant-mediated niche separation in sympatric populations of Maculinea nausithous and Maculinea teleius, (ii) there is no temporal shift in oviposition by Maculinea arion in relation to host ant distribution or egg density, and (iii) oviposition patterns in 13 populations of M. alcon's closest relative, Macaulinea rebeli, conform to H0 not H1 predictions. It is concluded that conservation measures should continue to be based on H0.

Facilitating the 3D Indoor Search and Rescue Problem: An Overview of the Problem and an Ant Colony Solution Approach

NASA Astrophysics Data System (ADS)

Tashakkori, H.; Rajabifard, A.; Kalantari, M.

2016-10-01

Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.

Following the moving and changing attachments and assemblages of 'addiction': Applying the actor network approach to autobiographies.

PubMed

Törrönen, Jukka; Tigerstedt, Christoffer

2018-04-01

The article applies actor network theory (ANT) to autobiographical data on alcohol dependence to explore what ANT can offer to the analysis of 'addiction stories'. By defining 'addiction' as a relational achievement, as the effect of elements acting together as a configuration of human and non-human actors, the article demonstrates how the moving and changing attachments of addiction can be dynamically analyzed with concepts of 'assemblage', 'mediator', 'tendency', 'translation', 'trajectory', 'immutable mobile', 'fluid' and 'bush fire'. The article shows how the reduction of alcohol dependence simply to genetic factors, neurobiological causes, personality disorders and self-medication constitutes an inadequate explanation. As 'meta theories', they illuminate addiction one-sidedly. Instead, as ANT pays attention to multiple heterogeneous mediators, it specifies in what way the causes identified in 'meta theories' may together with other actors participate in addiction assemblages. When following the development of addiction assemblages, we focus on situational sequences of action, in which human and non-human elements are linked to each other, and we trace how the relational shape of addiction changes from one sequence to another as a transforming assemblage of heterogeneous attachments that either maintain healthy subjectivities or destabilize them. The more attachments assemblages of addiction are able to make that are flexible and durable from one event to another, the stronger also the addiction-based subjectivities. Similarly, the fewer attachments that assemblages of addiction are able to keep in their various translations, the weaker the addiction-based subjectivities also become. An ANT-inspired analysis has a number of implications for the prevention and treatment of addiction: it suggests that in the prevention and treatment of addiction, the aim should hardly be to get rid of dependencies. Rather, the ambition should be the identification of attachments and relations that enable unhealthy practices and the development of harm as part of specific actor networks. Copyright © 2018 Elsevier B.V. All rights reserved.

Range image registration based on hash map and moth-flame optimization

NASA Astrophysics Data System (ADS)

Zou, Li; Ge, Baozhen; Chen, Lei

2018-03-01

Over the past decade, evolutionary algorithms (EAs) have been introduced to solve range image registration problems because of their robustness and high precision. However, EA-based range image registration algorithms are time-consuming. To reduce the computational time, an EA-based range image registration algorithm using hash map and moth-flame optimization is proposed. In this registration algorithm, a hash map is used to avoid over-exploitation in registration process. Additionally, we present a search equation that is better at exploration and a restart mechanism to avoid being trapped in local minima. We compare the proposed registration algorithm with the registration algorithms using moth-flame optimization and several state-of-the-art EA-based registration algorithms. The experimental results show that the proposed algorithm has a lower computational cost than other algorithms and achieves similar registration precision.

Optimal angle of polycrystalline silicon solar panels placed in a building using the ant colony optimization algorithm

NASA Astrophysics Data System (ADS)

Saouane, I.; Chaker, A.; Zaidi, B.; Shekhar, C.

2017-03-01

This paper describes the mathematical model used to determine the amount of solar radiation received on an inclined solar photovoltaic panel. The optimum slope angles for each month, season, and year have also been calculated for a solar photovoltaic panel. The optimization of the procedure to maximize the solar energy collected by the solar panel by varying the tilt angle is also presented. As a first step, the global solar radiation on the horizontal surface of a thermal photovoltaic panel during clear sky is estimated. Thereafter, the Muneer model, which provides the most accurate estimation of the total solar radiation at a given geographical point has been used to determine the optimum collector slope. Also, the Ant Colony Optimization (ACO) algorithm was applied to obtain the optimum tilt angle settings for PV collector to improve the PV collector efficiency. The results show good agreement between calculated and predicted results. Additionally, this paper presents studies carried out on the polycrystalline silicon solar panels for electrical energy generation in the city of Ghardaia. The electrical energy generation has been studied as a function of amount of irradiation received and the angle of optimum orientation of the solar panels.

A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks.

PubMed

Gu, Xiangping; Zhou, Xiaofeng; Sun, Yanjing

2018-02-28

Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings' spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node's residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets' sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods.

Advances of the reverse lactate threshold test: Non-invasive proposal based on heart rate and effect of previous cycling experience

PubMed Central

2018-01-01

Our first aim was to compare the anaerobic threshold (AnT) determined by the incremental protocol with the reverse lactate threshold test (RLT), investigating the previous cycling experience effect. Secondarily, an alternative RLT application based on heart rate was proposed. Two groups (12 per group-according to cycling experience) were evaluated on cycle ergometer. The incremental protocol started at 25 W with increments of 25 W at each 3 minutes, and the AnT was calculated by bissegmentation, onset of blood lactate concentration and maximal deviation methods. The RLT was applied in two phases: a) lactate priming segment; and b) reverse segment; the AnT (AnTRLT) was calculated based on a second order polynomial function. The AnT from the RLT was calculated based on the heart rate (AnTRLT-HR) by the second order polynomial function. In regard of the Study 1, most of statistical procedures converged for similarity between the AnT determined from the bissegmentation method and AnTRLT. For 83% of non-experienced and 75% of experienced subjects the bias was 4% and 2%, respectively. In Study 2, no difference was found between the AnTRLT and AnTRLT-HR. For 83% of non-experienced and 91% of experienced subjects, the bias between AnTRLT and AnTRLT-HR was similar (i.e. 6%). In summary, the AnT determined by the incremental protocol and RLT are consistent. The AnT can be determined during the RLT via heart rate, improving its applicability. However, future studies are required to improve the agreement between variables. PMID:29534108

Plant-derived differences in the composition of aphid honeydew and their effects on colonies of aphid-tending ants

PubMed Central

Pringle, Elizabeth G; Novo, Alexandria; Ableson, Ian; Barbehenn, Raymond V; Vannette, Rachel L

2014-01-01

In plant–ant–hemipteran interactions, ants visit plants to consume the honeydew produced by phloem-feeding hemipterans. If genetically based differences in plant phloem chemistry change the chemical composition of hemipteran honeydew, then the plant's genetic constitution could have indirect effects on ants via the hemipterans. If such effects change ant behavior, they could feed back to affect the plant itself. We compared the chemical composition of honeydews produced by Aphis nerii aphid clones on two milkweed congeners, Asclepias curassavica and Asclepias incarnata, and we measured the responses of experimental Linepithema humile ant colonies to these honeydews. The compositions of secondary metabolites, sugars, and amino acids differed significantly in the honeydews from the two plant species. Ant colonies feeding on honeydew derived from A. incarnata recruited in higher numbers to artificial diet, maintained higher queen and worker dry weight, and sustained marginally more workers than ants feeding on honeydew derived from A. curassavica. Ants feeding on honeydew from A. incarnata were also more exploratory in behavioral assays than ants feeding from A. curassavica. Despite performing better when feeding on the A. incarnata honeydew, ant workers marginally preferred honeydew from A. curassavica to honeydew from A. incarnata when given a choice. Our results demonstrate that plant congeners can exert strong indirect effects on ant colonies by means of plant-species-specific differences in aphid honeydew chemistry. Moreover, these effects changed ant behavior and thus could feed back to affect plant performance in the field. PMID:25505534

Tetramorium tsushimae Ants Use Methyl Branched Hydrocarbons of Aphids for Partner Recognition.

PubMed

Sakata, Itaru; Hayashi, Masayuki; Nakamuta, Kiyoshi

2017-10-01

In mutualisms, partner discrimination is often the most important challenge for interacting organisms. The interaction between ants and aphids is a model system for studying mutualisms; ants are provided with honeydew by aphids and, in turn, the ants offer beneficial services to the aphids. To establish and maintain this system, ants must discriminate mutualistic aphid species correctly. Although recent studies have shown that ants recognize aphids as mutualistic partners based on their cuticular hydrocarbons (CHCs), it was unclear which CHCs are involved in recognition. Here, we tested whether the n-alkane or methylalkane fraction, or both, of aphid CHCs were utilized as partner recognition cues by measuring ant aggressiveness toward these fractions. When workers of Tetramorium tsushimae ants were presented with dummies coated with n-alkanes of their mutualistic aphid Aphis craccivora, ants displayed higher levels of aggression than to dummies treated with total CHCs or methyl alkanes of A. craccivora; responses to dummies treated with n-alkanes of A. craccivora were similar to those to control dummies or dummies treated with the CHCs of the non-mutualistic aphid Acyrthosiphon pisum. By contrast, ants exhibited lower aggression to dummies treated with either total CHCs or the methylalkane fraction of the mutualistic aphid than to control dummies or dummies treated with CHCs of the non-mutualistic aphid. These results suggest that T. tsushimae ants use methylalkanes of the mutualistic aphid's CHCs to recognize partners, and that these ants do not recognize aphids as partners on the basis of n-alkanes.

Non-native Ants Are Smaller than Related Native Ants.

PubMed

McGlynn, Terrence P

1999-12-01

I compare the sizes of non-native and native ants to evaluate how worker size may be related to the ability of a species to invade new habitats. I compare the size of 78 non-native ant species belonging to 26 genera with the size of native congeneric species; native ants are larger than non-native ants in 22 of 26 genera. Ants were sorted by genera into fighting and nonfighting groups, based on observations of interspecific interactions with other ant species. In all of the genera with monomorphic worker castes that fight during competition, the non-native species were smaller than the native species. The genera that engage in combat had a higher frequency of significantly smaller size in non-native ants. I selected Wasmannia auropunctata for further studies, to compare native and non-native populations. Specimens of W. auropunctata from non-native populations were smaller than conspecific counterparts from its native habitat. I consider hypotheses to explain why non-native ants are smaller in size than native ants, including the role of colony size in interspecific fights, changes in life history, the release from intraspecific fighting, and climate. The discovery that fighting non-natives are smaller than their closest native relatives may provide insight into the mechanisms for success of non-native species, as well as the role of worker size and colony size during interspecific competition.

Use of fluorescent ANTS to examine the BBB-permeability of polysaccharide

PubMed Central

Christopher, Kevin; Makani, Vishruti; Judy, Wesley; Lee, Erica; Chiaia, Nicolas; Kim, Dong Shik; Park, Joshua

2015-01-01

Recently, some polysaccharides showed therapeutic potentials for the treatment of neurodegenerative diseases while the most important property, their permeability to the blood brain barrier (BBB) that sheathes the brain and spinal cord, is not yet determined. The determination has been delayed by the difficulty in tracking a target polysaccharide among endogenous polysaccharides in animal. We developed an easy way to examine the BBB-permeability and, possibly, tissue distribution of a target polysaccharide in animal. We tagged a polysaccharide with fluorescent 8-aminonaphthalene-1,3,6-trisulfonic acid disodium salt (ANTS) for tracking. We also developed a simple method to separate ANTS-tagged polysaccharide from unconjugated free ANTS using 75% ethanol. After ANTS-polysaccharide was intra-nasally administered into animals, we could quantify the amounts of ANTS-polysaccharide in the brain and the serum by fluorocytometry. We could also separate free ANTS-polysaccharide from serum proteins using trichloroacetic acid (TCA) and 75% ethanol. Our method will help to track a polysaccharide in animal easily. • ANTS-labeling is less tedious than but as powerful as radiolabeling for tracking a target polysaccharide in animal. • Our simple method can separate structurally intact ANTS-polysaccharide from animal serum and tissues. • This method is good for the fluorometry-based measurement of ANTS-conjugated macromolecules in tissues. PMID:25914873

Privatization by Other Means: Social Power, Tankers and Techno-Assemblages of Water Supply in Amman, Jordan.

NASA Astrophysics Data System (ADS)

Mustafa, D.

2016-12-01

Combined piped and tanker based water supply systems have become a ubiquitous feature of urban waterscapes in the global South. Jordanian water sector, and Amman in particular has been a recipient of considerable international financial and technical assistance over the past decades. The international assistance has coupled with the Jordanian state's own pro-market ideological stance, and its political compulsions to spawn a techno-social assemblage of water supply that represents a hybrid state and commercial water supply system. I present the results of a field study in Amman, Jordan on water tankers and water users to understand the techno-political underpinnings of the hybrid system and its impact on differential access to water. I explore how Actor Network Theory (ANT) based analysis of tankers, suction pumps and piped water system and their materiality may explain differential access to water. But that exploration is inflected by a larger political ecological concern with questions of power and discourses about citizenship and claim making on the state. I find that ANT based focus on water technologies, while ontologically fertile, and epistemologically innovative, is nevertheless politically barren. Much richer political insights are to be gained from structural and post-structurally based investigations of the discursive and material drivers of the techno-social assemblages of water supply. The technologies don't just neutrally impact water access, but seem to almost intentionally favour the powerful over the powerless. Surely the political agency must not reside in inanimate technologies but in the social actors and structures that fashion those technologies, and configure them such to reinforce geographies of power. I call for a renewed focus on social power and how its impact on lived geographies is mediated by technology.

Saving the injured: Rescue behavior in the termite-hunting ant Megaponera analis.

PubMed

Frank, Erik Thomas; Schmitt, Thomas; Hovestadt, Thomas; Mitesser, Oliver; Stiegler, Jonas; Linsenmair, Karl Eduard

2017-04-01

Predators of highly defensive prey likely develop cost-reducing adaptations. The ant Megaponera analis is a specialized termite predator, solely raiding termites of the subfamily Macrotermitinae (in this study, mostly colonies of Pseudocanthotermes sp.) at their foraging sites. The evolutionary arms race between termites and ants led to various defensive mechanisms in termites (for example, a caste specialized in fighting predators). Because M. analis incurs high injury/mortality risks when preying on termites, some risk-mitigating adaptations seem likely to have evolved. We show that a unique rescue behavior in M. analis , consisting of injured nestmates being carried back to the nest, reduces combat mortality. After a fight, injured ants are carried back by their nestmates; these ants have usually lost an extremity or have termites clinging to them and are able to recover within the nest. Injured ants that are forced experimentally to return without help, die in 32% of the cases. Behavioral experiments show that two compounds, dimethyl disulfide and dimethyl trisulfide, present in the mandibular gland reservoirs, trigger the rescue behavior. A model accounting for this rescue behavior identifies the drivers favoring its evolution and estimates that rescuing enables maintenance of a 28.7% larger colony size. Our results are the first to explore experimentally the adaptive value of this form of rescue behavior focused on injured nestmates in social insects and help us to identify evolutionary drivers responsible for this type of behavior to evolve in animals.

Saving the injured: Rescue behavior in the termite-hunting ant Megaponera analis

PubMed Central

Frank, Erik Thomas; Schmitt, Thomas; Hovestadt, Thomas; Mitesser, Oliver; Stiegler, Jonas; Linsenmair, Karl Eduard

2017-01-01

Predators of highly defensive prey likely develop cost-reducing adaptations. The ant Megaponera analis is a specialized termite predator, solely raiding termites of the subfamily Macrotermitinae (in this study, mostly colonies of Pseudocanthotermes sp.) at their foraging sites. The evolutionary arms race between termites and ants led to various defensive mechanisms in termites (for example, a caste specialized in fighting predators). Because M. analis incurs high injury/mortality risks when preying on termites, some risk-mitigating adaptations seem likely to have evolved. We show that a unique rescue behavior in M. analis, consisting of injured nestmates being carried back to the nest, reduces combat mortality. After a fight, injured ants are carried back by their nestmates; these ants have usually lost an extremity or have termites clinging to them and are able to recover within the nest. Injured ants that are forced experimentally to return without help, die in 32% of the cases. Behavioral experiments show that two compounds, dimethyl disulfide and dimethyl trisulfide, present in the mandibular gland reservoirs, trigger the rescue behavior. A model accounting for this rescue behavior identifies the drivers favoring its evolution and estimates that rescuing enables maintenance of a 28.7% larger colony size. Our results are the first to explore experimentally the adaptive value of this form of rescue behavior focused on injured nestmates in social insects and help us to identify evolutionary drivers responsible for this type of behavior to evolve in animals. PMID:28439543

Translating the Prescribed into the Enacted Curriculum in College and School

ERIC Educational Resources Information Center

Edwards, Richard

2011-01-01

Drawing upon concepts from actor-network theory (ANT), this article explores how the principle of symmetry can provide alternative readings of the translations of the prescribed into the enacted curriculum, without reducing understanding to explanation. The paper explores the contrasting ways in which the prescribed curriculum is translated into…

Biased and greedy random walks on two-dimensional lattices with quenched randomness: The greedy ant within a disordered environment

NASA Astrophysics Data System (ADS)

Mitran, T. L.; Melchert, O.; Hartmann, A. K.

2013-12-01

The main characteristics of biased greedy random walks (BGRWs) on two-dimensional lattices with real-valued quenched disorder on the lattice edges are studied. Here the disorder allows for negative edge weights. In previous studies, considering the negative-weight percolation (NWP) problem, this was shown to change the universality class of the existing, static percolation transition. In the presented study, four different types of BGRWs and an algorithm based on the ant colony optimization heuristic were considered. Regarding the BGRWs, the precise configurations of the lattice walks constructed during the numerical simulations were influenced by two parameters: a disorder parameter ρ that controls the amount of negative edge weights on the lattice and a bias strength B that governs the drift of the walkers along a certain lattice direction. The random walks are “greedy” in the sense that the local optimal choice of the walker is to preferentially traverse edges with a negative weight (associated with a net gain of “energy” for the walker). Here, the pivotal observable is the probability that, after termination, a lattice walk exhibits a total negative weight, which is here considered as percolating. The behavior of this observable as function of ρ for different bias strengths B is put under scrutiny. Upon tuning ρ, the probability to find such a feasible lattice walk increases from zero to 1. This is the key feature of the percolation transition in the NWP model. Here, we address the question how well the transition point ρc, resulting from numerically exact and “static” simulations in terms of the NWP model, can be resolved using simple dynamic algorithms that have only local information available, one of the basic questions in the physics of glassy systems.

Effect of Interactions between Harvester Ants on Forager Decisions

PubMed Central

Davidson, Jacob D.; Arauco-Aliaga, Roxana P.; Crow, Sam; Gordon, Deborah M.; Goldman, Mark S.

2017-01-01

Harvester ant colonies adjust their foraging activity to day-to-day changes in food availability and hour-to-hour changes in environmental conditions. This collective behavior is regulated through interactions, in the form of brief antennal contacts, between outgoing foragers and returning foragers with food. Here we consider how an ant, waiting in the entrance chamber just inside the nest entrance, uses its accumulated experience of interactions to decide whether to leave the nest to forage. Using videos of field observations, we tracked the interactions and foraging decisions of ants in the entrance chamber. Outgoing foragers tended to interact with returning foragers at higher rates than ants that returned to the deeper nest and did not forage. To provide a mechanistic framework for interpreting these results, we develop a decision model in which ants make decisions based upon a noisy accumulation of individual contacts with returning foragers. The model can reproduce core trends and realistic distributions for individual ant interaction statistics, and suggests possible mechanisms by which foraging activity may be regulated at an individual ant level. PMID:28758093

Fire ants self-assemble into waterproof rafts to survive floods

PubMed Central

Mlot, Nathan J.; Tovey, Craig A.; Hu, David L.

2011-01-01

Why does a single fire ant Solenopsis invicta struggle in water, whereas a group can float effortlessly for days? We use time-lapse photography to investigate how fire ants S. invicta link their bodies together to build waterproof rafts. Although water repellency in nature has been previously viewed as a static material property of plant leaves and insect cuticles, we here demonstrate a self-assembled hydrophobic surface. We find that ants can considerably enhance their water repellency by linking their bodies together, a process analogous to the weaving of a waterproof fabric. We present a model for the rate of raft construction based on observations of ant trajectories atop the raft. Central to the construction process is the trapping of ants at the raft edge by their neighbors, suggesting that some “cooperative” behaviors may rely upon coercion. PMID:21518911

Trail pheromone disruption of Argentine ant trail formation and foraging.

PubMed

Suckling, David Maxwell; Peck, Robert W; Stringer, Lloyd D; Snook, Kirsten; Banko, Paul C

2010-01-01

Trail pheromone disruption of invasive ants is a novel tactic that builds on the development of pheromone-based pest management in other insects. Argentine ant trail pheromone, (Z)-9-hexadecenal, was formulated as a micro-encapsulated sprayable particle and applied against Argentine ant populations in 400 m2 field plots in Hawai'i Volcanoes National Park. A widely dispersed point source strategy for trail pheromone disruption was used. Traffic rates of ants in bioassays of treated filter paper, protected from rainfall and sunlight, indicated the presence of behaviorally significant quantities of pheromone being released from the formulation for up to 59 days. The proportion of plots, under trade wind conditions (2–3 m s−1), with visible trails was reduced for up to 14 days following treatment, and the number of foraging ants at randomly placed tuna-bait cards was similarly reduced. The success of these trail pheromone disruption trials in a natural ecosystem highlights the potential of this method for control of invasive ant species in this and other environments.

Prevalence of the genus Cladosporium on the integument of leaf-cutting ants characterized by 454 pyrosequencing.

PubMed

Duarte, A P M; Ferro, M; Rodrigues, A; Bacci, M; Nagamoto, N S; Forti, L C; Pagnocca, F C

2016-09-01

The relationship of attine ants with their mutualistic fungus and other microorganisms has been studied during the last two centuries. However, previous studies about the diversity of fungi in the ants' microenvironment are based mostly on culture-dependent approaches, lacking a broad characterization of the fungal ant-associated community. Here, we analysed the fungal diversity found on the integument of Atta capiguara and Atta laevigata alate ants using 454 pyrosequencing. We obtained 35,453 ITS reads grouped into 99 molecular operational taxonomic units (MOTUs). Data analysis revealed that A. capiguara drones had the highest diversity of MOTUs. Besides the occurrence of several uncultured fungi, the mycobiota analysis revealed that the most abundant taxa were the Cladosporium-complex, Cryptococcus laurentii and Epicoccum sp. Taxa in the genus Cladosporium were predominant in all samples, comprising 67.9 % of all reads. The remarkable presence of the genus Cladosporium on the integument of leaf-cutting ants alates from distinct ant species suggests that this fungus is favored in this microenvironment.

Tritrophic effects of birds and ants on a canopy food web, tree growth, and phytochemistry

Treesearch

Kailen A. Mooney

2007-01-01

Insectivorous birds and ants co-occur in most terrestrial communities, and theory predicts that emergent properties (i.e., nonadditive effects) can determine their combined influence on arthropods and plants. In a three-year factorial experiment, I investigated whether the effects of birds on pine and its arthropods differed based on the presence of ants that were...

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Myrmecochores can target high-quality disperser ants: variation in elaiosome traits and ant preferences for myrmecochorous Euphorbiaceae in Brazilian Caatinga.

PubMed

Leal, Laura Carolina; Lima Neto, Mário Correia; de Oliveira, Antônio Fernando Morais; Andersen, Alan N; Leal, Inara R

2014-02-01

Recent evidence suggests that the traditional view of myrmecochory as a highly diffuse interaction between diaspores and a wide range of ant species attracted to their elaiosomes may not be correct. The effectiveness of dispersal varies markedly among ant species, and combined with differential attractiveness of diaspores due to elaiosome size and composition, this raises the potential for myrmecochorous plants to target ant species that offer the highest quality dispersal services. We ask the question: Do particular physical and chemical traits of elaiosomes result in disproportionate removal of Euphorbiaceae diaspores by high-quality disperser ants in Caatinga vegetation of north-eastern Brazil? We offered seeds of five euphorb species that varied in morphological and chemical traits of elaiosomes to seed-dispersing ants. High-quality seed-disperser ants (species of Dinoponera, Ectatomma and Camponotus) were identified as those that rapidly collected and transported diaspores to their nests, often over substantial distances, whereas low-quality disperser ants (primarily species of Pheidole and Solenopsis) typically fed on elaiosomes in situ, and only ever transported diaspores very short distances. Low-quality disperser ants were equally attracted to the elaiosomes of all study species. However, high-quality dispersers showed a strong preference for diaspores with the highest elaiosome mass (and especially proportional mass). As far as we are aware, this is the first study to identify a mechanism of diaspore selection by high-quality ant dispersers based on elaiosome traits under field conditions. Our findings suggest that myrmecochorous plants can preferentially target high-quality seed-disperser ants through the evolution of particular elaiosome traits.

The effects of ant nests on soil fertility and plant performance: a meta-analysis.

PubMed

Farji-Brener, Alejandro G; Werenkraut, Victoria

2017-07-01

Ants are recognized as one of the major sources of soil disturbance world-wide. However, this view is largely based on isolated studies and qualitative reviews. Here, for the first time, we quantitatively determined whether ant nests affect soil fertility and plant performance, and identified the possible sources of variation of these effects. Using Bayesian mixed-models meta-analysis, we tested the hypotheses that ant effects on soil fertility and plant performance depend on the substrate sampled, ant feeding type, latitude, habitat and the plant response variable measured. Ant nests showed higher nutrient and cation content than adjacent non-nest soil samples, but similar pH. Nutrient content was higher in ant refuse materials than in nest soils. The fertilizer effect of ant nests was also higher in dry habitats than in grasslands or savannas. Cation content was higher in nests of plant-feeding ants than in nests of omnivorous species, and lower in nests from agro-ecosystems than in nests from any other habitat. Plants showed higher green/root biomass and fitness on ant nests soils than in adjacent, non-nest sites; but plant density and diversity were unaffected by the presence of ant nests. Root growth was particularly higher in refuse materials than in ant nest soils, in leaf-cutting ant nests and in deserts habitats. Our results confirm the major role of ant nests in influencing soil fertility and vegetation patterns and provide information about the factors that mediate these effects. First, ant nests improve soil fertility mainly through the accumulation of refuse materials. Thus, different refuse dump locations (external or in underground nest chambers) could benefit different vegetation life-forms. Second, ant nests could increase plant diversity at larger spatial scales only if the identity of favoured plants changes along environmental gradients (i.e. enhancing β-diversity). Third, ant species that feed on plants play a relevant role fertilizing soils, which may balance their known influence as primary consumers. Fourth, the effects of ant nests as fertility islands are larger in arid lands, possibly because fertility is intrinsically lower in these habitats. Overall, this study provide novel and quantitative evidence confirming that ant nests are key soil modifiers, emphasizing their role as ecological engineers. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Insecticide Transfer Efficiency and Lethal Load in Argentine Ants

DOE PAGES

Hooper-Bui, L. M.; Kwok, E S.C.; Buchholz, B. A.; ...

2015-07-03

Trophallaxis between individual worker ants and the toxicant load in dead and live Argentine ants (Linepithema humile) in colonies exposed to fipronil and hydramethylnon experimental baits were examined using accelerator mass spectrometry (AMS). About 50% of the content of the crop containing trace levels of 14C-sucrose, 14C-hydramethylnon, and 14C-fipronil was shared between single donor and recipient ants. Dead workers and queens contained significantly more hydramethylnon (122.7 and 22.4 amol/μg ant, respectively) than did live workers and queens (96.3 and 10.4 amol/μg ant, respectively). Dead workers had significantly more fipronil (420.3 amol/μg ant) than did live workers (208.5 amol/μg ant), butmore » dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). Moreover, the distribution of fipronil differed within the bodies of dead and live queens; the highest amounts of fipronil were recovered in the thorax of dead queens whereas live queens had the highest levels in the head. Resurgence of polygynous ant colonies treated with hydramethylnon baits may be explained by queen survival resulting from sublethal doses due to a slowing of trophallaxis throughout the colony. The bait strategies and dose levels for controlling insect pests need to be based on the specific toxicant properties and trophic strategies for targeting the entire colony.« less

Insecticide Transfer Efficiency and Lethal Load in Argentine Ants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hooper-Bui, L. M.; Kwok, E S.C.; Buchholz, B. A.

Trophallaxis between individual worker ants and the toxicant load in dead and live Argentine ants (Linepithema humile) in colonies exposed to fipronil and hydramethylnon experimental baits were examined using accelerator mass spectrometry (AMS). About 50% of the content of the crop containing trace levels of 14C-sucrose, 14C-hydramethylnon, and 14C-fipronil was shared between single donor and recipient ants. Dead workers and queens contained significantly more hydramethylnon (122.7 and 22.4 amol/μg ant, respectively) than did live workers and queens (96.3 and 10.4 amol/μg ant, respectively). Dead workers had significantly more fipronil (420.3 amol/μg ant) than did live workers (208.5 amol/μg ant), butmore » dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). Moreover, the distribution of fipronil differed within the bodies of dead and live queens; the highest amounts of fipronil were recovered in the thorax of dead queens whereas live queens had the highest levels in the head. Resurgence of polygynous ant colonies treated with hydramethylnon baits may be explained by queen survival resulting from sublethal doses due to a slowing of trophallaxis throughout the colony. The bait strategies and dose levels for controlling insect pests need to be based on the specific toxicant properties and trophic strategies for targeting the entire colony.« less

How to escape from the host nest: imperfect chemical mimicry in eucharitid parasitoids and exploitation of the ants' hygienic behavior.

PubMed

Pérez-Lachaud, Gabriela; Bartolo-Reyes, Juan Carlos; Quiroa-Montalván, Claudia M; Cruz-López, Leopoldo; Lenoir, Alain; Lachaud, Jean-Paul

2015-04-01

Communication in ants is based to a great extent on chemical compounds. Recognition of intruders is primarily based on cuticular hydrocarbon (CHC) profile matching but is prone to being cheated. Eucharitid wasps are specific parasitoids of the brood of ants; the immature stages are either well integrated within the colony or are protected within the host cocoons, whereas adult wasps at emergence must leave their host nest to reproduce and need to circumvent the ant recognition system to escape unscathed. The behavioral interactions between eucharitid wasps and workers of their host, the Neotropical ant Ectatomma tuberculatum, are characterized. In experimental bioassays, newly emerged parasitoids were not violently aggressed. They remained still and were grabbed by ants upon contact and transported outside the nest; host workers were even observed struggling to reject them. Parasitoids were removed from the nest within five minutes, and most were unharmed, although two wasps (out of 30) were killed during the interaction with the ants. We analyzed the CHCs of the ant and its two parasitoids, Dilocantha lachaudii and Isomerala coronata, and found that although wasps shared all of their compounds with the ants, each wasp species had typical blends and hydrocarbon abundance was also species specific. Furthermore, the wasps had relatively few CHCs compared to E. tuberculatum (22-44% of the host components), and these were present in low amounts. Wasps, only partially mimicking the host CHC profile, were immediately recognized as alien and actively removed from the nest by the ants. Hexane-washed wasps were also transported to the refuse piles, but only after being thoroughly inspected and after most of the workers had initially ignored them. Being recognized as intruder may be to the parasitoids' advantage, allowing them to quickly leave the natal nest, and therefore enhancing the fitness of these very short lived parasitoids. We suggest that eucharitids take advantage of the hygienic behavior of ants to quickly escape from their host nests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Next Generation System and Software Architectures: Challenges from Future NASA Exploration Missions

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Rouff, Christopher A.; Hinchey, Michael G.; Rash, James L.; Truszkowski, Walt

2006-01-01

The four key objective properties of a system that are required of it in order for it to qualify as "autonomic" are now well-accepted-self-configuring, self-healing, self-protecting, and self-optimizing- together with the attribute properties-viz. self-aware, environment-aware, self-monitoring and self- adjusting. This paper describes the need for next generation system software architectures, where components are agents, rather than objects masquerading as agents, and where support is provided for self-* properties (both existing self-chop and emerging self-* properties). These are discussed as exhibited in NASA missions, and in particular with reference to a NASA concept mission, ANTS, which is illustrative of future NASA exploration missions based on the technology of intelligent swarms.

Foraging activity and dietary spectrum of the Argentine ant (Hymenoptera: Formicidae) in invaded natural areas of the northeast Iberian Peninsula.

PubMed

Abril, S; Oliveras, J; Gómez, C

2007-10-01

We analyzed the foraging activity and the dietary spectrum of the Argentine ant (Linepithema humile Mayr) and select native ants on cork oaks from Mediterranean open cork oak (Quercus suber) secondary forests. The study areas included invaded and noninvaded zones in close proximity. The Argentine ant's daily foraging activity was correlated to the abiotic factors studied, whereas the seasonal foraging activity was related not only to the variations in the average air temperature, but also to the trophic needs of the colony. Argentine ant workers focused their attention on protein foods during the queens' oviposition periods and during the larvae development phase, and on carbohydrate foods, such as honeydew, when males and workers were hatching. There were no significant differences over the entire year in the quantity of liquid food collected by the Argentine ant workers in comparison with the native ants studied. The solid diet of the Argentine ant on cork oaks is composed of insects, most of which are aphids. Our results have clear applications for control methods based on toxic baits in the invaded natural ecosystems of the Iberian Peninsula.

Effect of an invasive ant and its chemical control on a threatened endemic Seychelles millipede.

PubMed

Lawrence, James M; Samways, Michael J; Henwood, Jock; Kelly, Janine

2011-06-01

The impact of invasive species on island faunas can be of major local consequence, while their control is an important part of island ecosystem restoration. Among these invasive species are ants, of which some have a disruptive impact on indigenous arthropod populations. Here, we study the impact of the invasive African big-headed ant, Pheidole megacephala, on a small Seychelles island, Cousine, and assess the impact of this ant, and its chemical control, using the commercially available hydramethylnon-based bait, Siege, on the endemic keystone Seychelles giant millipede species, Sechelleptus seychellarum. We found no significant correlations in landscape-scale spatial overlap and abundance between the ant and the millipede. Furthermore, the ant did not attack healthy millipedes, but fed only on dying and dead individuals. The chemical defences of the millipede protected it from ant predation. Ingestion of the bait at standard concentration had no obvious impact on the millipede. The most significant threat to the Seychelles giant millipede in terms of P. megacephala invasion is from possible catastrophic shifts in ecosystem function through ant hemipteran mutualisms which can lead to tree mortality, resulting in alteration of the millipede's habitat.

Ant Colony Optimization for Mapping, Scheduling and Placing in Reconfigurable Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferrandi, Fabrizio; Lanzi, Pier Luca; Pilato, Christian

Modern heterogeneous embedded platforms, com- posed of several digital signal, application specific and general purpose processors, also include reconfigurable devices support- ing partial dynamic reconfiguration. These devices can change the behavior of some of their parts during execution, allowing hardware acceleration of more sections of the applications. Never- theless, partial dynamic reconfiguration imposes severe overheads in terms of latency. For such systems, a critical part of the design phase is deciding on which processing elements (mapping) and when (scheduling) executing a task, but also how to place them on the reconfigurable device to guarantee the most efficient reuse of themore » programmable logic. In this paper we propose an algorithm based on Ant Colony Optimization (ACO) that simultaneously executes the scheduling, the mapping and the linear placing of tasks, hiding reconfiguration overheads through prefetching. Our heuristic gradually constructs solutions and then searches around the best ones, cutting out non-promising areas of the design space. We show how to consider the partial dynamic reconfiguration constraints in the scheduling, placing and mapping problems and compare our formulation to other heuristics that address the same problems. We demonstrate that our proposal is more general and robust, and finds better solutions (16.5% in average) with respect to competing solutions.« less

Using physiology to predict the responses of ants to climatic warming.

PubMed

Diamond, Sarah E; Penick, Clint A; Pelini, Shannon L; Ellison, Aaron M; Gotelli, Nicholas J; Sanders, Nathan J; Dunn, Robert R

2013-12-01

Physiological intolerance of high temperatures places limits on organismal responses to the temperature increases associated with global climatic change. Because ants are geographically widespread, ecologically diverse, and thermophilic, they are an ideal system for exploring the extent to which physiological tolerance can predict responses to environmental change. Here, we expand on simple models that use thermal tolerance to predict the responses of ants to climatic warming. We investigated the degree to which changes in the abundance of ants under warming reflect reductions in the thermal niche space for their foraging. In an eastern deciduous forest system in the United States with approximately 40 ant species, we found that for some species, the loss of thermal niche space for foraging was related to decreases in abundance with increasing experimental climatic warming. However, many ant species exhibited no loss of thermal niche space. For one well-studied species, Temnothorax curvispinosus, we examined both survival of workers and growth of colonies (a correlate of reproductive output) as functions of temperature in the laboratory, and found that the range of thermal tolerances for colony growth was much narrower than for survival of workers. We evaluated these functions in the context of experimental climatic warming and found that the difference in the responses of these two attributes to temperature generates differences in the means and especially the variances of expected fitness under warming. The expected mean growth of colonies was optimized at intermediate levels of warming (2-4°C above ambient); yet, the expected variance monotonically increased with warming. In contrast, the expected mean and variance of the survival of workers decreased when warming exceeded 4°C above ambient. Together, these results for T. curvispinosus emphasize the importance of measuring reproduction (colony growth) in the context of climatic change: indeed, our examination of the loss of thermal niche space with the larger species pool could be missing much of the warming impact due to these analyses being based on survival rather than reproduction. We suggest that while physiological tolerance of temperature can be a useful predictive tool for modeling responses to climatic change, future efforts should be devoted to understanding the causes and consequences of variability in models of tolerance calibrated with different metrics of performance and fitness.

Differential Cloud Particles Evolution Algorithm Based on Data-Driven Mechanism for Applications of ANN

PubMed Central

2017-01-01

Computational scientists have designed many useful algorithms by exploring a biological process or imitating natural evolution. These algorithms can be used to solve engineering optimization problems. Inspired by the change of matter state, we proposed a novel optimization algorithm called differential cloud particles evolution algorithm based on data-driven mechanism (CPDD). In the proposed algorithm, the optimization process is divided into two stages, namely, fluid stage and solid stage. The algorithm carries out the strategy of integrating global exploration with local exploitation in fluid stage. Furthermore, local exploitation is carried out mainly in solid stage. The quality of the solution and the efficiency of the search are influenced greatly by the control parameters. Therefore, the data-driven mechanism is designed for obtaining better control parameters to ensure good performance on numerical benchmark problems. In order to verify the effectiveness of CPDD, numerical experiments are carried out on all the CEC2014 contest benchmark functions. Finally, two application problems of artificial neural network are examined. The experimental results show that CPDD is competitive with respect to other eight state-of-the-art intelligent optimization algorithms. PMID:28761438

A Pilot Study Exploring the Use of Breath Analysis to Differentiate Healthy Cattle from Cattle Experimentally Infected with Mycobacterium bovis

PubMed Central

Ellis, Christine K.; Stahl, Randal S.; Nol, Pauline; Waters, W. Ray; Palmer, Mitchell V.; Rhyan, Jack C.; VerCauteren, Kurt C.; McCollum, Matthew; Salman, M. D.

2014-01-01

Bovine tuberculosis, caused by Mycobacterium bovis, is a zoonotic disease of international public health importance. Ante-mortem surveillance is essential for control; however, current surveillance tests are hampered by limitations affecting ease of use or quality of results. There is an emerging interest in human and veterinary medicine in diagnosing disease via identification of volatile organic compounds produced by pathogens and host-pathogen interactions. The objective of this pilot study was to explore application of existing human breath collection and analysis methodologies to cattle as a means to identify M. bovis infection through detection of unique volatile organic compounds or changes in the volatile organic compound profiles present in breath. Breath samples from 23 male Holstein calves (7 non-infected and 16 M. bovis-infected) were collected onto commercially available sorbent cartridges using a mask system at 90 days post-inoculation with M. bovis. Samples were analyzed using gas chromatography-mass spectrometry, and chromatographic data were analyzed using standard analytical chemical and metabolomic analyses, principle components analysis, and a linear discriminant algorithm. The findings provide proof of concept that breath-derived volatile organic compound analysis can be used to differentiate between healthy and M. bovis-infected cattle. PMID:24586655

Adaptive Radiation in Socially Advanced Stem-Group Ants from the Cretaceous.

PubMed

Barden, Phillip; Grimaldi, David A

2016-02-22

Across terrestrial ecosystems, modern ants are ubiquitous. As many as 94 out of every 100 individual arthropods in rainforests are ants, and they constitute up to 15% of animal biomass in the Amazon. Moreover, ants are pervasive agents of natural selection as over 10,000 arthropod species are specialized inquilines or myrmecomorphs living among ants or defending themselves through mimicry. Such impact is traditionally explained by sociality: ants are the first major group of ground-dwelling predatory insects to become eusocial, increasing efficiency of tasks and establishing competitive superiority over solitary species. A wealth of specimens from rich deposits of 99 million-year-old Burmese amber resolves ambiguity regarding sociality and diversity in the earliest ants. The stem-group genus Gerontoformica maintained distinct reproductive castes including morphotypes unknown in solitary aculeate (stinging) wasps, providing insight into early behavior. We present rare aggregations of workers, indicating group recruitment as well as an instance of interspecific combat; such aggression is a social feature of modern ants. Two species and an unusual new genus are described, further expanding the remarkable diversity of early ants. Stem-group ants are recovered as a paraphyletic assemblage at the base of modern lineages varying greatly in size, form, and mouthpart structure, interpreted here as an adaptive radiation. Though Cretaceous stem-group ants were eusocial and adaptively diverse, we hypothesize that their extinction resulted from the rise of competitively superior crown-group taxa that today form massive colonies, consistent with Wilson and Hölldobler's concept of "dynastic succession." Copyright © 2016 Elsevier Ltd. All rights reserved.

Discovery-dominance trade-off among widespread invasive ant species.

PubMed

Bertelsmeier, Cleo; Avril, Amaury; Blight, Olivier; Jourdan, Hervé; Courchamp, Franck

2015-07-01

Ants are among the most problematic invasive species. They displace numerous native species, alter ecosystem processes, and can have negative impacts on agriculture and human health. In part, their success might stem from a departure from the discovery-dominance trade-off that can promote co-existence in native ant communities, that is, invasive ants are thought to be at the same time behaviorally dominant and faster discoverers of resources, compared to native species. However, it has not yet been tested whether similar asymmetries in behavioral dominance, exploration, and recruitment abilities also exist among invasive species. Here, we establish a dominance hierarchy among four of the most problematic invasive ants (Linepithema humile, Lasius neglectus, Wasmannia auropunctata, Pheidole megacephala) that may be able to arrive and establish in the same areas in the future. To assess behavioral dominance, we used confrontation experiments, testing the aggressiveness in individual and group interactions between all species pairs. In addition, to compare discovery efficiency, we tested the species' capacity to locate a food resource in a maze, and the capacity to recruit nestmates to exploit a food resource. The four species differed greatly in their capacity to discover resources and to recruit nestmates and to dominate the other species. Our results are consistent with a discovery-dominance trade-off. The species that showed the highest level of interspecific aggressiveness and dominance during dyadic interactions.

Synchrony between fruit maturation and effective dispersers' foraging activity increases seed protection against seed predators

PubMed Central

Boulay, Raphaël; Carro, Francisco; Soriguer, Ramón C; Cerdá, Xim

2007-01-01

The evolution of pollination and seed dispersal mutualisms is conditioned by the spatial and temporal co-occurrence of animals and plants. In the present study we explore the timing of seed release of a myrmecochorous plant (Helleborus foetidus) and ant activity in two populations in southern Spain during 2 consecutive years. The results indicate that fruit dehiscence and seed shedding occur mostly in the morning and correspond to the period of maximum foraging activity of the most effective ant dispersers. By contrast, ant species that do not transport seeds and/or that do not abound near the plants are active either before or after H. foetidus diaspores are released. Experimental analysis of diet preference for three kinds of food shows that effective ant dispersers are mostly scavengers that readily feed on insect corpses and sugars. Artificial seed depots suggest that seeds deposited on the ground out of the natural daily time window of diaspore releasing are not removed by ants and suffer strong predation by nocturnal rodents Apodemus sylvaticus. Nevertheless, important inter-annual variations in rodent populations cast doubts on their real importance as selection agents. We argue that traits allowing synchrony between seed presentation and effective partners may constitute a crucial pre-adaptation for the evolution of plant–animal mutualisms involving numerous animal partners. PMID:17698486

AntBot: Anti-pollution peer-to-peer botnets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Guanhua; Eidenbenz, Stephan; Ha, Duc T

2009-01-01

Botnets, which are responsible for many email sparnming and DDoS (Distributed Denial of Service) attacks in the current Internet, have emerged as one of most severe cyber-threats in recent years. To evade detection and improve resistance against countermeasures, botnets have evolved from the first generation that relies on IRC chat channels to deliver commands to the current generation that uses highly resilient P2P (Peer-to-Peer) protocols to spread their C&C (Command and Control) information. It is, however, revealed that P2P botnets, although relieved from the single point of failure that IRC botnets suffer, can be easily disrupted using pollution-based mitigation schemesmore » [15]. In this paper, we play the devil's advocate and propose a new type of hypothetical botnets called AntBot, which aim to propagate their C&C information to individual bots even though there exists an adversary that persistently pollutes keys used by seized bots to search the command information. The key idea of AntBot is a tree-like structure that bots use to deliver the command so that captured bots reveal only limited information. To evaluate effectiveness of AntBot against pollution-based mitigation in a virtual environment, we develop a distributed P2P botnet simulator. Using extensive experiments, we demonstrate that AntBot operates resiliently against pollution-based mitigation. We further present a few potential defense schemes that could effectively disrupt AntBot operations.« less

Stigmergic construction and topochemical information shape ant nest architecture

PubMed Central

Khuong, Anaïs; Gautrais, Jacques; Perna, Andrea; Sbaï, Chaker; Combe, Maud; Kuntz, Pascale; Jost, Christian; Theraulaz, Guy

2016-01-01

The nests of social insects are not only impressive because of their sheer complexity but also because they are built from individuals whose work is not centrally coordinated. A key question is how groups of insects coordinate their building actions. Here, we use a combination of experimental and modeling approaches to investigate nest construction in the ant Lasius niger. We quantify the construction dynamics and the 3D structures built by ants. Then, we characterize individual behaviors and the interactions of ants with the structures they build. We show that two main interactions are involved in the coordination of building actions: (i) a stigmergic-based interaction that controls the amplification of depositions at some locations and is attributable to a pheromone added by ants to the building material; and (ii) a template-based interaction in which ants use their body size as a cue to control the height at which they start to build a roof from existing pillars. We then develop a 3D stochastic model based on these individual behaviors to analyze the effect of pheromone presence and strength on construction dynamics. We show that the model can quantitatively reproduce key features of construction dynamics, including a large-scale pattern of regularly spaced pillars, the formation and merging of caps over the pillars, and the remodeling of built structures. Finally, our model suggests that the lifetime of the pheromone is a highly influential parameter that controls the growth and form of nest architecture. PMID:26787857

Stigmergic construction and topochemical information shape ant nest architecture.

PubMed

Khuong, Anaïs; Gautrais, Jacques; Perna, Andrea; Sbaï, Chaker; Combe, Maud; Kuntz, Pascale; Jost, Christian; Theraulaz, Guy

2016-02-02

The nests of social insects are not only impressive because of their sheer complexity but also because they are built from individuals whose work is not centrally coordinated. A key question is how groups of insects coordinate their building actions. Here, we use a combination of experimental and modeling approaches to investigate nest construction in the ant Lasius niger. We quantify the construction dynamics and the 3D structures built by ants. Then, we characterize individual behaviors and the interactions of ants with the structures they build. We show that two main interactions are involved in the coordination of building actions: (i) a stigmergic-based interaction that controls the amplification of depositions at some locations and is attributable to a pheromone added by ants to the building material; and (ii) a template-based interaction in which ants use their body size as a cue to control the height at which they start to build a roof from existing pillars. We then develop a 3D stochastic model based on these individual behaviors to analyze the effect of pheromone presence and strength on construction dynamics. We show that the model can quantitatively reproduce key features of construction dynamics, including a large-scale pattern of regularly spaced pillars, the formation and merging of caps over the pillars, and the remodeling of built structures. Finally, our model suggests that the lifetime of the pheromone is a highly influential parameter that controls the growth and form of nest architecture.

Visual cues for the retrieval of landmark memories by navigating wood ants.

PubMed

Harris, Robert A; Graham, Paul; Collett, Thomas S

2007-01-23

Even on short routes, ants can be guided by multiple visual memories. We investigate here the cues controlling memory retrieval as wood ants approach a one- or two-edged landmark to collect sucrose at a point along its base. In such tasks, ants store the desired retinal position of landmark edges at several points along their route. They guide subsequent trips by retrieving the appropriate memory and moving to bring the edges in the scene toward the stored positions. The apparent width of the landmark turns out to be a powerful cue for retrieving the desired retinal position of a landmark edge. Two other potential cues, the landmark's apparent height and the distance that the ant walks, have little effect on memory retrieval. A simple model encapsulates these conclusions and reproduces the ants' routes in several conditions. According to this model, the ant stores a look-up table. Each entry contains the apparent width of the landmark and the desired retinal position of vertical edges. The currently perceived width provides an index for retrieving the associated stored edge positions. The model accounts for the population behavior of ants and the idiosyncratic training routes of individual ants. Our results imply binding between the edge of a shape and its width and, further, imply that assessing the width of a shape does not depend on the presence of any particular local feature, such as a landmark edge. This property makes the ant's retrieval and guidance system relatively robust to edge occlusions.

Bacteria may contribute to distant species recognition in ant-aphid mutualistic relationships.

PubMed

Fischer, Christophe Y; Detrain, Claire; Thonart, Philippe; Haubruge, Eric; Francis, Frédéric; Verheggen, François J; Lognay, Georges C

2017-04-01

Mutualistic interactions between ant and aphid species have been the subject of considerable historical and contemporary investigations, the primary benefits being cleaning and protection for the aphids and carbohydrate-rich honeydew for the ants. Questions remained, however, as to the volatile semiochemical factor influencing this relationship. A recent study highlighted the role of bacterial honeydew volatile compounds in ant attraction. Here, ant's ability to distantly discriminate 2 aphid species was investigated based on bacterial honeydew semiochemicals emissions using a two-way olfactometer. Both the mutualistic aphid Aphis fabae L. and the nonmyrmecophilous aphid Acyrthosiphon pisum Harris were found to be attractive for the ant Lasius niger L. The level of attraction was similar in both assays (control vs. one of the aphid species). However, when given a choice between these 2 aphid species, ants showed a significant preference for Aphis fabae. Honeydew volatiles, mostly from bacterial origins, are known to be a key element in ant attraction. Using the same olfactometry protocol, the relative attractiveness of volatiles emitted by honeydews collected from each aphid species and by bacteria isolated from each honeydew was investigated. Again, ants significantly preferred volatiles released by Aphis fabae honeydew and bacteria. This information suggests that microbial honeydew volatiles enable ants to distantly discriminate aphid species. These results strengthen the interest of studying the occurrence and potential impact of microorganisms in insect symbioses. © 2015 Institute of Zoology, Chinese Academy of Sciences.

Water stress strengthens mutualism among ants, trees, and scale insects.

PubMed

Pringle, Elizabeth G; Akçay, Erol; Raab, Ted K; Dirzo, Rodolfo; Gordon, Deborah M

2013-11-01

Abiotic environmental variables strongly affect the outcomes of species interactions. For example, mutualistic interactions between species are often stronger when resources are limited. The effect might be indirect: water stress on plants can lead to carbon stress, which could alter carbon-mediated plant mutualisms. In mutualistic ant-plant symbioses, plants host ant colonies that defend them against herbivores. Here we show that the partners' investments in a widespread ant-plant symbiosis increase with water stress across 26 sites along a Mesoamerican precipitation gradient. At lower precipitation levels, Cordia alliodora trees invest more carbon in Azteca ants via phloem-feeding scale insects that provide the ants with sugars, and the ants provide better defense of the carbon-producing leaves. Under water stress, the trees have smaller carbon pools. A model of the carbon trade-offs for the mutualistic partners shows that the observed strategies can arise from the carbon costs of rare but extreme events of herbivory in the rainy season. Thus, water limitation, together with the risk of herbivory, increases the strength of a carbon-based mutualism.

Negative feedback in ants: crowding results in less trail pheromone deposition

PubMed Central

Czaczkes, Tomer J.; Grüter, Christoph; Ratnieks, Francis L. W.

2013-01-01

Crowding in human transport networks reduces efficiency. Efficiency can be increased by appropriate control mechanisms, which are often imposed externally. Ant colonies also have distribution networks to feeding sites outside the nest and can experience crowding. However, ants do not have external controllers or leaders. Here, we report a self-organized negative feedback mechanism, based on local information, which downregulates the production of recruitment signals in crowded parts of a network by Lasius niger ants. We controlled crowding by manipulating trail width and the number of ants on a trail, and observed a 5.6-fold reduction in the number of ants depositing trail pheromone from least to most crowded conditions. We also simulated crowding by placing glass beads covered in nest-mate cuticular hydrocarbons on the trail. After 10 bead encounters over 20 cm, forager ants were 45 per cent less likely to deposit pheromone. The mechanism of negative feedback reported here is unusual in that it acts by downregulating the production of a positive feedback signal, rather than by direct inhibition or the production of an inhibitory signal. PMID:23365196

Trail Pheromone Disruption of Argentine Ant Trail Formation and Foraging

USGS Publications Warehouse

Suckling, D.M.; Peck, R.W.; Stringer, L.D.; Snook, K.; Banko, P.C.

2010-01-01

Trail pheromone disruption of invasive ants is a novel tactic that builds on the development of pheromone-based pest management in other insects. Argentine ant trail pheromone, (Z)-9-hexadecenal, was formulated as a micro-encapsulated sprayable particle and applied against Argentine ant populations in 400 m2 field plots in Hawai'i Volcanoes National Park. A widely dispersed point source strategy for trail pheromone disruption was used. Traffic rates of ants in bioassays of treated filter paper, protected from rainfall and sunlight, indicated the presence of behaviorally significant quantities of pheromone being released from the formulation for up to 59 days. The proportion of plots, under trade wind conditions (2-3 m s-1), with visible trails was reduced for up to 14 days following treatment, and the number of foraging ants at randomly placed tuna-bait cards was similarly reduced. The success of these trail pheromone disruption trials in a natural ecosystem highlights the potential of this method for control of invasive ant species in this and other environments. ?? Springer Science+Business Media, LLC 2010.

Towards enhancement of performance of K-means clustering using nature-inspired optimization algorithms.

PubMed

Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

PubMed Central

Deb, Suash; Yang, Xin-She

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730

Improving Search Algorithms by Using Intelligent Coordinates

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan; Bandari, Esfandiar

2004-01-01

We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent eta is self-interested; it sets its variable to maximize its own function g (sub eta). Three factors govern such a distributed algorithm's performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit alI three factors by modifying a search algorithm's exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based player engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.

The Effects of Restoration Age and Prescribed Burns on Grassland Ant Community Structure.

PubMed

Menke, Sean B; Gaulke, Emilee; Hamel, Allison; Vachter, Nicole

2015-10-01

North American grassland environments are endangered as a result of degradation and conversion for agriculture and housing. Efforts to manage and restore grasslands have traditionally focused on monitoring plant communities to determine restoration success, but the incorporation of animal communities may provide important benchmarks of ecosystem function and restoration. Ants play many roles in maintaining ecosystem health in temperate grasslands, but relatively little is known about how ant communities respond to restoration. We studied the role that restoration age and prescribed burns have on ant communities in two types of Illinois grasslands, prairies and savannas, and identify indicator species of restoration success. Grassland environments included remnants and restorations that varied in age from newly restored sites, to sites that have been under restoration for >15 yr. We demonstrate that prairie and savanna ant communities are distinct, but respond to restoration in a similar manner. Three distinct prairie ant assemblages were identified based on the age of restoration of a site-sites <3 yr old, sites that have been under restoration >5 yr, and remnant prairies. Four distinct savanna ant assemblages were identified based on the age of restoration of a site-sites <3 yr old, sites 5-15 yr old, sites >15 yr old, and remnant savanna environments. After accounting for restoration age, time since last burn in both prairie and savannas does not explain community composition or species richness. Several ant species in both prairies and savannas have predictable changes in incidence that indicate their suitability for use as indicator species. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Dynamics of Plant Cell-Wall Polysaccharide Decomposition in Leaf-Cutting Ant Fungus Gardens

PubMed Central

Harholt, Jesper; Willats, William G. T.; Boomsma, Jacobus J.

2011-01-01

The degradation of live plant biomass in fungus gardens of leaf-cutting ants is poorly characterised but fundamental for understanding the mutual advantages and efficiency of this obligate nutritional symbiosis. Controversies about the extent to which the garden-symbiont Leucocoprinus gongylophorus degrades cellulose have hampered our understanding of the selection forces that induced large scale herbivory and of the ensuing ecological footprint of these ants. Here we use a recently established technique, based on polysaccharide microarrays probed with antibodies and carbohydrate binding modules, to map the occurrence of cell wall polymers in consecutive sections of the fungus garden of the leaf-cutting ant Acromyrmex echinatior. We show that pectin, xyloglucan and some xylan epitopes are degraded, whereas more highly substituted xylan and cellulose epitopes remain as residuals in the waste material that the ants remove from their fungus garden. These results demonstrate that biomass entering leaf-cutting ant fungus gardens is only partially utilized and explain why disproportionally large amounts of plant material are needed to sustain colony growth. They also explain why substantial communities of microbial and invertebrate symbionts have evolved associations with the dump material from leaf-cutting ant nests, to exploit decomposition niches that the ant garden-fungus does not utilize. Our approach thus provides detailed insight into the nutritional benefits and shortcomings associated with fungus-farming in ants. PMID:21423735

Constraint programming based biomarker optimization.

PubMed

Zhou, Manli; Luo, Youxi; Sun, Guoquan; Mai, Guoqin; Zhou, Fengfeng

2015-01-01

Efficient and intuitive characterization of biological big data is becoming a major challenge for modern bio-OMIC based scientists. Interactive visualization and exploration of big data is proven to be one of the successful solutions. Most of the existing feature selection algorithms do not allow the interactive inputs from users in the optimizing process of feature selection. This study investigates this question as fixing a few user-input features in the finally selected feature subset and formulates these user-input features as constraints for a programming model. The proposed algorithm, fsCoP (feature selection based on constrained programming), performs well similar to or much better than the existing feature selection algorithms, even with the constraints from both literature and the existing algorithms. An fsCoP biomarker may be intriguing for further wet lab validation, since it satisfies both the classification optimization function and the biomedical knowledge. fsCoP may also be used for the interactive exploration of bio-OMIC big data by interactively adding user-defined constraints for modeling.

Desiccation resistance in tropical insects: causes and mechanisms underlying variability in a Panama ant community.

PubMed

Bujan, Jelena; Yanoviak, Stephen P; Kaspari, Michael

2016-09-01

Desiccation resistance, the ability of an organism to reduce water loss, is an essential trait in arid habitats. Drought frequency in tropical regions is predicted to increase with climate change, and small ectotherms are often under a strong desiccation risk. We tested hypotheses regarding the underexplored desiccation potential of tropical insects. We measured desiccation resistance in 82 ant species from a Panama rainforest by recording the time ants can survive desiccation stress. Species' desiccation resistance ranged from 0.7 h to 97.9 h. We tested the desiccation adaptation hypothesis, which predicts higher desiccation resistance in habitats with higher vapor pressure deficit (VPD) - the drying power of the air. In a Panama rainforest, canopy microclimates averaged a VPD of 0.43 kPa, compared to a VPD of 0.05 kPa in the understory. Canopy ants averaged desiccation resistances 2.8 times higher than the understory ants. We tested a number of mechanisms to account for desiccation resistance. Smaller insects should desiccate faster given their higher surface area to volume ratio. Desiccation resistance increased with ant mass, and canopy ants averaged 16% heavier than the understory ants. A second way to increase desiccation resistance is to carry more water. Water content was on average 2.5% higher in canopy ants, but total water content was not a good predictor of ant desiccation resistance or critical thermal maximum (CT max), a measure of an ant's thermal tolerance. In canopy ants, desiccation resistance and CT max were inversely related, suggesting a tradeoff, while the two were positively correlated in understory ants. This is the first community level test of desiccation adaptation hypothesis in tropical insects. Tropical forests do contain desiccation-resistant species, and while we cannot predict those simply based on their body size, high levels of desiccation resistance are always associated with the tropical canopy.

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

PubMed

Li, Bai; Gong, Li-gang; Yang, Wen-lun

2014-01-01

Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

NASA Astrophysics Data System (ADS)

Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

2016-09-01

This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

Cost- and reliability-oriented aggregation point association in long-term evolution and passive optical network hybrid access infrastructure for smart grid neighborhood area network

NASA Astrophysics Data System (ADS)

Cheng, Xiao; Feng, Lei; Zhou, Fanqin; Wei, Lei; Yu, Peng; Li, Wenjing

2018-02-01

With the rapid development of the smart grid, the data aggregation point (AP) in the neighborhood area network (NAN) is becoming increasingly important for forwarding the information between the home area network and wide area network. Due to limited budget, it is unable to use one-single access technology to meet the ongoing requirements on AP coverage. This paper first introduces the wired and wireless hybrid access network with the integration of long-term evolution (LTE) and passive optical network (PON) system for NAN, which allows a good trade-off among cost, flexibility, and reliability. Then, based on the already existing wireless LTE network, an AP association optimization model is proposed to make the PON serve as many APs as possible, considering both the economic efficiency and network reliability. Moreover, since the features of the constraints and variables of this NP-hard problem, a hybrid intelligent optimization algorithm is proposed, which is achieved by the mixture of the genetic, ant colony and dynamic greedy algorithm. By comparing with other published methods, simulation results verify the performance of the proposed method in improving the AP coverage and the performance of the proposed algorithm in terms of convergence.

An effective inversion algorithm for retrieving bimodal aerosol particle size distribution from spectral extinction data

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Yao, Yuchen; Ruan, Liming

2014-12-01

The Ant Colony Optimization algorithm based on the probability density function (PDF-ACO) is applied to estimate the bimodal aerosol particle size distribution (PSD). The direct problem is solved by the modified Anomalous Diffraction Approximation (ADA, as an approximation for optically large and soft spheres, i.e., χ⪢1 and |m-1|⪡1) and the Beer-Lambert law. First, a popular bimodal aerosol PSD and three other bimodal PSDs are retrieved in the dependent model by the multi-wavelength extinction technique. All the results reveal that the PDF-ACO algorithm can be used as an effective technique to investigate the bimodal PSD. Then, the Johnson's SB (J-SB) function and the modified beta (M-β) function are employed as the general distribution function to retrieve the bimodal PSDs under the independent model. Finally, the J-SB and M-β functions are applied to recover actual measurement aerosol PSDs over Beijing and Shanghai obtained from the aerosol robotic network (AERONET). The numerical simulation and experimental results demonstrate that these two general functions, especially the J-SB function, can be used as a versatile distribution function to retrieve the bimodal aerosol PSD when no priori information about the PSD is available.

Arms races and the evolution of big fierce societies.

PubMed

Boswell, G P; Franks, N R; Britton, N F

2001-08-22

The causes of biological gigantism have received much attention, but only for individual organisms. What selection pressures might favour the evolution of gigantic societies? Here we consider the largest single-queen insect societies, those of the Old World army ant Dorylus, single colonies of which can have 20 million workers. We propose that colony gigantism in Dorylus arises as a result of an arms race and test this prediction by developing a size-structured mathematical model. We use this model for exploring and potentially explaining differences in colony size, colony aggression and colony propagation strategies in populations of New World army ants Eciton and Old World army ants Dorylus. The model shows that, by determining evolutionarily stable strategies (ESSs), differences in the trophic levels at which these army ants live feed forwards into differences in their densities and collision rates and, hence, into different strategies of growth, aggression and propagation. The model predicts large colony size and the occurrence of battles and a colony-propagation strategy involving highly asymmetrical divisions in Dorylus and that Eciton colonies should be smaller, non-combative and exhibit equitable binary fission. These ESSs are in excellent agreement with field observations and demonstrate that gargantuan societies can arise through arms races.

A Review of the Tawny Crazy Ant, Nylanderia fulva, an Emergent Ant Invader in the Southern United States: Is Biological Control a Feasible Management Option?

PubMed

Wang, Zinan; Moshman, Lori; Kraus, Emily C; Wilson, Blake E; Acharya, Namoona; Diaz, Rodrigo

2016-12-15

The tawny crazy ant, Nylanderia fulva (Mayr) (Hymenoptera: Formicidae), has invaded states of the U.S. including Texas, Louisiana, Mississippi, Alabama, Florida, and Georgia. Native to South America, N. fulva is considered a pest in the U.S. capable of annoying homeowners and farmers, as well as displacing native ant species. As it continues to expand its range, there is a growing need to develop novel management techniques to control the pest and prevent further spread. Current management efforts rely heavily on chemical control, but these methods have not been successful. A review of the biology, taxonomy, ecology, and distribution of N. fulva , including discussion of ecological and economic consequences of this invasive species, is presented. Options for future management are suggested focusing on biological control, including parasitoid flies in the genus Pseudacteon , the microsporidian parasite Myrmecomorba nylanderiae , and a novel polynucleotide virus as potential biological control agents. We suggest further investigation of natural enemies present in the adventive range, as well as foreign exploration undertaken in the native range including Paraguay, Brazil, and Argentina. We conclude that N. fulva may be a suitable candidate for biological control.

A Review of the Tawny Crazy Ant, Nylanderia fulva, an Emergent Ant Invader in the Southern United States: Is Biological Control a Feasible Management Option?

PubMed Central

Wang, Zinan; Moshman, Lori; Kraus, Emily C.; Wilson, Blake E.; Acharya, Namoona; Diaz, Rodrigo

2016-01-01

The tawny crazy ant, Nylanderia fulva (Mayr) (Hymenoptera: Formicidae), has invaded states of the U.S. including Texas, Louisiana, Mississippi, Alabama, Florida, and Georgia. Native to South America, N. fulva is considered a pest in the U.S. capable of annoying homeowners and farmers, as well as displacing native ant species. As it continues to expand its range, there is a growing need to develop novel management techniques to control the pest and prevent further spread. Current management efforts rely heavily on chemical control, but these methods have not been successful. A review of the biology, taxonomy, ecology, and distribution of N. fulva, including discussion of ecological and economic consequences of this invasive species, is presented. Options for future management are suggested focusing on biological control, including parasitoid flies in the genus Pseudacteon, the microsporidian parasite Myrmecomorba nylanderiae, and a novel polynucleotide virus as potential biological control agents. We suggest further investigation of natural enemies present in the adventive range, as well as foreign exploration undertaken in the native range including Paraguay, Brazil, and Argentina. We conclude that N. fulva may be a suitable candidate for biological control. PMID:27983690

Collective movements of pedestrians: How we can learn from simple experiments with non-human (ant) crowds

PubMed Central

Sarvi, Majid

2017-01-01

Introduction Understanding collective behavior of moving organisms and how interactions between individuals govern their collective motion has triggered a growing number of studies. Similarities have been observed between the scale-free behavioral aspects of various systems (i.e. groups of fish, ants, and mammals). Investigation of such connections between the collective motion of non-human organisms and that of humans however, has been relatively scarce. The problem demands for particular attention in the context of emergency escape motion for which innovative experimentation with panicking ants has been recently employed as a relatively inexpensive and non-invasive approach. However, little empirical evidence has been provided as to the relevance and reliability of this approach as a model of human behaviour. Methods This study explores pioneer experiments of emergency escape to tackle this question and to connect two forms of experimental observations that investigate the collective movement at macroscopic level. A large number of experiments with human and panicking ants are conducted representing the escape behavior of these systems in crowded spaces. The experiments share similar architectural structures in which two streams of crowd flow merge with one another. Measures such as discharge flow rates and the probability distribution of passage headways are extracted and compared between the two systems. Findings Our findings displayed an unexpected degree of similarity between the collective patterns emerged from both observation types, particularly based on aggregate measures. Experiments with ants and humans commonly indicated how significantly the efficiency of motion and the rate of discharge depend on the architectural design of the movement environment. Practical applications Our findings contribute to the accumulation of evidence needed to identify the boarders of applicability of experimentation with crowds of non-human entities as models of human collective motion as well as the level of measurements (i.e. macroscopic or microscopic) and the type of contexts at which reliable inferences can be drawn. This particularly has implications in the context of experimenting evacuation behaviour for which recruiting human subjects may face ethical restrictions. The findings, at minimum, offer promise as to the potential benefit of piloting such experiments with non-human crowds, thereby forming better-informed hypotheses. PMID:28854221

Collective movements of pedestrians: How we can learn from simple experiments with non-human (ant) crowds.

PubMed

Shahhoseini, Zahra; Sarvi, Majid

2017-01-01

Understanding collective behavior of moving organisms and how interactions between individuals govern their collective motion has triggered a growing number of studies. Similarities have been observed between the scale-free behavioral aspects of various systems (i.e. groups of fish, ants, and mammals). Investigation of such connections between the collective motion of non-human organisms and that of humans however, has been relatively scarce. The problem demands for particular attention in the context of emergency escape motion for which innovative experimentation with panicking ants has been recently employed as a relatively inexpensive and non-invasive approach. However, little empirical evidence has been provided as to the relevance and reliability of this approach as a model of human behaviour. This study explores pioneer experiments of emergency escape to tackle this question and to connect two forms of experimental observations that investigate the collective movement at macroscopic level. A large number of experiments with human and panicking ants are conducted representing the escape behavior of these systems in crowded spaces. The experiments share similar architectural structures in which two streams of crowd flow merge with one another. Measures such as discharge flow rates and the probability distribution of passage headways are extracted and compared between the two systems. Our findings displayed an unexpected degree of similarity between the collective patterns emerged from both observation types, particularly based on aggregate measures. Experiments with ants and humans commonly indicated how significantly the efficiency of motion and the rate of discharge depend on the architectural design of the movement environment. Our findings contribute to the accumulation of evidence needed to identify the boarders of applicability of experimentation with crowds of non-human entities as models of human collective motion as well as the level of measurements (i.e. macroscopic or microscopic) and the type of contexts at which reliable inferences can be drawn. This particularly has implications in the context of experimenting evacuation behaviour for which recruiting human subjects may face ethical restrictions. The findings, at minimum, offer promise as to the potential benefit of piloting such experiments with non-human crowds, thereby forming better-informed hypotheses.

Solving the vehicle routing problem by a hybrid meta-heuristic algorithm

NASA Astrophysics Data System (ADS)

Yousefikhoshbakht, Majid; Khorram, Esmaile

2012-08-01

The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called sweep algorithm (SW) + ant colony system (ACS) for the classical VRP. At the first stage, the VRP is solved by the SW, and at the second stage, the ACS and 3-opt local search are used for improving the solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.

Alkaloid venom weaponry of three Megalomyrmex thief ants and the behavioral response of Cyphomyrmex costatus host ants.

PubMed

Adams, Rachelle M M; Jones, Tappey H; Longino, John T; Weatherford, Robert G; Mueller, Ulrich G

2015-04-01

Social parasites exploit other societies by invading and stealing resources. Some enter protected nests using offensive chemical weaponry made from alkaloid-based venom. We characterized the venoms of three Megalomyrmex thief ant species (M. mondabora, M. mondaboroides, and M. silvestrii) that parasitize the fungus-growing ants, and developed an ethogram to describe host ant reactions to raiding M. mondaboroides and M. silvestrii parasites. We compared piperidine, pyrrolidine, and pyrolizidine venom alkaloid structures with synthetic samples from previous studies, and describe the novel stereochemistry of trans 2-hexyl-5-[8-oxononyl]-pyrrolidine (3) from M. mondabora. We showed that workers of Cyphomyrmex costatus, the host of M. mondaboroides and M. silvestrii, react to a sting by Megalomyrmex parasites mainly with submissive behavior, playing dead or retreating. Host submission also followed brief antennal contact. The behavior of C. costatus ants observed in this study was similar to that of Cyphomyrmex cornutus, host of M. mondabora, suggesting that the alkaloidal venoms with pyrrolidines from M. mondabora, piperidines from M. mondaboroides, and pyrolizidines from M. silvestrii may function similarly as appeasement and repellent allomones against host ants, despite their different chemical structure. With the use of these chemical weapons, the Megalomyrmex thief ants are met with little host resistance and easily exploit host colony resources.

Impact of red imported fire ant infestation on northern bobwhite quail abundance trends in southeastern United States

USGS Publications Warehouse

Allen, Craig R.; Willey, R.D.; Myers, P.E.; Horton, P.M.; Buffa, J.

2000-01-01

Northern bobwhite quail (Colinus virginianus L.) populations are declining throughout their range. One factor contributing to the decline in the southeastern United States may be the red imported fire ant (Solenopsis invicta Buren). Recent research in Texas has documented that red imported fire ants can have a significant impact on northern bobwhite quail. That research was conducted in areas where fire ants are predominately polygynous (multiple queen). Polygynous infestations have much higher mound densities than the monogynous (single queen) form. In most of the southeastern United States, fire ants are predominately monogynous. We determined if there was a relationship between the invasion of monogynous red imported fire ants and abundance trends in northern bobwhite quail in the southeastern United States. For Florida, Georgia, and South Carolina we compared average northern bobwhite quail abundance based on Christmas Bird Count data for each county before and after fire ant invasion, and conducted regression analyses on bobwhite quail abundance and year preinvasion, and abundance and year postinvasion. Regionally, northern bobwhite quail were more abundant before (0.067 ??0.018 bobwhite quail per observer hour) than after fire ants invaded (0.019 ?? 0.006; Z = -3.746, df = 18, P 30-yr variation in invasion dates.

Foraging ants trade off further for faster: use of natural bridges and trunk trail permanency in carpenter ants

NASA Astrophysics Data System (ADS)

Loreto, Raquel G.; Hart, Adam G.; Pereira, Thairine M.; Freitas, Mayara L. R.; Hughes, David P.; Elliot, Simon L.

2013-10-01

Trail-making ants lay pheromones on the substrate to define paths between foraging areas and the nest. Combined with the chemistry of these pheromone trails and the physics of evaporation, trail-laying and trail-following behaviours provide ant colonies with the quickest routes to food. In relatively uniform environments, such as that provided in many laboratory studies of trail-making ants, the quickest route is also often the shortest route. Here, we show that carpenter ants ( Camponotus rufipes), in natural conditions, are able to make use of apparent obstacles in their environment to assist in finding the fastest routes to food. These ants make extensive use of fallen branches, twigs and lianas as bridges to build their trails. These bridges make trails significantly longer than their straight line equivalents across the forest floor, but we estimate that ants spend less than half the time to reach the same point, due to increased carriage speed across the bridges. We also found that these trails, mainly composed of bridges, are maintained for months, so they can be characterized as trunk trails. We suggest that pheromone-based foraging trail networks in field conditions are likely to be structured by a range of potentially complex factors but that even then, speed remains the most important consideration.

Mathematical modeling on obligate mutualism: Interactions between leaf-cutter ants and their fungus garden.

PubMed

Kang, Yun; Clark, Rebecca; Makiyama, Michael; Fewell, Jennifer

2011-11-21

We propose a simple mathematical model by applying Michaelis-Menton equations of enzyme kinetics to study the mutualistic interaction between the leaf cutter ant and its fungus garden at the early stage of colony expansion. We derive sufficient conditions on the extinction and coexistence of these two species. In addition, we give a region of initial condition that leads to the extinction of two species when the model has an interior attractor. Our global analysis indicates that the division of labor by worker ants and initial conditions are two important factors that determine whether leaf cutter ants' colonies and their fungus garden can survive and grow or not. We validate the model by comparing model simulations and data on fungal and ant colony growth rates under laboratory conditions. We perform sensitive analysis of the model based on the experimental data to gain more biological insights on ecological interactions between leaf-cutter ants and their fungus garden. Finally, we give conclusions and discuss potential future work. Published by Elsevier Ltd.

Extrafloral-nectar-based partner manipulation in plant–ant relationships

PubMed Central

Grasso, D. A.; Pandolfi, C.; Bazihizina, N.; Nocentini, D.; Nepi, M.; Mancuso, S.

2015-01-01

Plant–ant interactions are generally considered as mutualisms, with both parties gaining benefits from the association. It has recently emerged that some of these mutualistic associations have, however, evolved towards other forms of relationships and, in particular, that plants may manipulate their partner ants to make reciprocation more beneficial, thereby stabilizing the mutualism. Focusing on plants bearing extrafloral nectaries, we review recent studies and address three key questions: (i) how can plants attract potential partners and maintain their services; (ii) are there compounds in extrafloral nectar that could mediate partner manipulation; and (iii) are ants susceptible to such compounds? After reviewing the current knowledge on plant–ant associations, we propose a possible scenario where plant-derived chemicals, such as secondary metabolites, known to have an impact on animal brain, could have evolved in plants to attract and manipulate ant behaviour. This new viewpoint would place plant–animal interaction in a different ecological context, opening new ecological and neurobiological perspectives of drug seeking and use. PMID:25589521

Cross-layer design for intrusion detection and data security in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2007-09-01

A wireless ad hoc sensor network is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. The nodes are severely resource-constrained, with limited processing, memory and power capacities and must operate cooperatively to fulfill a common mission in typically unattended modes. In a wireless sensor network (WSN), each sensor at a node can observe locally some underlying physical phenomenon and sends a quantized version of the observation to sink (destination) nodes via wireless links. Since the wireless medium can be easily eavesdropped, links can be compromised by intrusion attacks from nodes that may mount denial-of-service attacks or insert spurious information into routing packets, leading to routing loops, long timeouts, impersonation, and node exhaustion. A cross-layer design based on protocol-layer interactions is proposed for detection and identification of various intrusion attacks on WSN operation. A feature set is formed from selected cross-layer parameters of the WSN protocol to detect and identify security threats due to intrusion attacks. A separate protocol is not constructed from the cross-layer design; instead, security attributes and quantified trust levels at and among nodes established during data exchanges complement customary WSN metrics of energy usage, reliability, route availability, and end-to-end quality-of-service (QoS) provisioning. Statistical pattern recognition algorithms are applied that use observed feature-set patterns observed during network operations, viewed as security audit logs. These algorithms provide the "best" network global performance in the presence of various intrusion attacks. A set of mobile (software) agents distributed at the nodes implement the algorithms, by moving among the layers involved in the network response at each active node and trust neighborhood, collecting parametric information and executing assigned decision tasks. The communications overhead due to security mechanisms and the latency in network response are thus minimized by reducing the need to move large amounts of audit data through resource-limited nodes and by locating detection/identification programs closer to audit data. If network partitioning occurs due to uncoordinated node exhaustion, data compromise or other effects of the attacks, the mobile agents can continue to operate, thereby increasing fault tolerance in the network response to intrusions. Since the mobile agents behave like an ant colony in securing the WSN, published ant colony optimization (ACO) routines and other evolutionary algorithms are adapted to protect network security, using data at and through nodes to create audit records to detect and respond to denial-of-service attacks. Performance evaluations of algorithms are performed by simulation of a few intrusion attacks, such as black hole, flooding, Sybil and others, to validate the ability of the cross-layer algorithms to enable WSNs to survive the attacks. Results are compared for the different algorithms.

Weaver ant role in cashew orchards in Vietnam.

PubMed

Peng, Renkang; Lan, La Pham; Christian, Keith

2014-08-01

Cashew (Anacardium occidentale L.) is a very important source of income for more than 200,000 farmer households in Vietnam. The present cashew productivity in Vietnam is low and unstable, and pest damage is partly responsible for this. Cashew farmers rely on pesticides to minimize the damage, resulting in adverse impacts on farm environment and farmers' health. Weaver ants (Oecophylla spp) are effective biocontrol agents of a range of cashew insect pests in several cashew-growing countries, and these ants are widely distributed in Vietnam. The aim of this study is to evaluate the potential of weaver ants in cashew orchards in Vietnam. Field surveys and field experiment were conducted in five cashew orchards from July 2006 to January 2008 in Binh Phuoc, Dong Nai, and Ba Ria Vung Tau provinces, Vietnam. Based on the field surveys, the most important pests that damage flushing foliar and floral shoots and young cashew fruits and nuts were mosquito bugs, brown shoot borers, blue shoot borers, and fruit-nut borers. The damage caused by each of these pests was significantly lower on trees with weaver ants compared with trees without the ants, showing that the ants were able to keep these pest damages under the control threshold. Regular monitoring of the field experiment showed that weaver ants were similar to insecticides for controlling mosquito bugs, blue shoot borers, fruit-nut borers, leaf rollers, and leaf miners. Aphids did not become major pests in plot with weaver ants. To manage insect pest assemblage in cashew orchards, an integrated pest management using weaver ants as a major component is discussed.

Nest architecture, fungus gardens, queen, males and larvae of the fungus-growing ant Mycetagroicus inflatus Brandão & Mayhé-Nunes.

PubMed

Jesovnik, A; Sosa-Calvo, J; Lopes, C T; Vasconcelos, H L; Schultz, T R

2013-01-01

All known fungus-growing ants (tribe Attini) are obligately symbiotic with their cultivated fungi. The fungal cultivars of "lower" attine ants are facultative symbionts, capable of living apart from ants, whereas the fungal cultivars of "higher" attine ants, including leaf-cutting genera Atta and Acromyrmex , are highly specialized, obligate symbionts. Since higher attine ants and fungi are derived from lower attine ants and fungi, understanding the evolutionary transition from lower to higher attine agriculture requires understanding the historical sequence of change in both ants and fungi. The biology of the poorly known ant genus Mycetagroicus is of special interest in this regard because it occupies a phylogenetic position intermediate between lower and higher ant agriculture. Here, based on the excavations of four nests in Pará, Brazil, we report the first biological data for the recently described species Mycetagroicus inflatus , including the first descriptions of Mycetagroicus males and larvae. Like M. cerradensis , the only other species in the genus for which nesting biology is known, the garden chambers of M. inflatus are unusually deep and the garden is most likely relocated vertically in rainy and dry seasons. Due to the proximity of nests to the Araguaia River, it is likely that even the uppermost chambers and nest entrances of M. inflatus are submerged during the rainy season. Most remarkably, all three examined colonies of M. inflatus cultivate the same fungal species as their congener, M. cerradensis , over 1,000 km away, raising the possibility of long-term symbiont fidelity spanning speciation events within the genus.

ANTS-anchored Zn-Al-CO3-LDH particles as fluorescent probe for sensing of folic acid

NASA Astrophysics Data System (ADS)

Liu, Pengfei; Liu, Dan; Liu, Yanhuan; Li, Lei

2016-09-01

A novel fluorescent nanosensor for detecting folic acid (FA) in aqueous media has been developed based on 8-aminonaphthalene-1,3,6-trisulfonate (ANTS) anchored to the surface of Zn-Al-CO3-layered double hydroxides (LDH) particles. The nanosensor showed high fluorescence intensity and good photostability due to a strong coordination interaction between surface Zn2+ ions of Zn-Al-CO3-LDH and N atoms of ANTS, which were verified by result of X-ray photoelectron spectroscopy (XPS). ANTS-anchored on the surface of Zn-Al-CO3-LDH restricted the intra-molecular rotation leading to ANTS-anchored J-type aggregation emission enhancement. ANTS-anchored Zn-Al-CO3-LDH particles exhibited highly sensitive and selective response to FA over other common metal ions and saccharides present in biological fluids. The proposed mechanism was that oxygen atoms of -SO3 groups in ANTS-anchored on the surface of Zn-Al-CO3-LDH were easily collided by FA molecules to form potential hydrogen bonds between ANTS-anchored and FA molecules, which could effectively quench the ANTS-anchored fluorescence. Under the simulated physiological conditions (pH of 7.4), the fluorescence quenching was fitted to Stern-Volmer equation with a linear response in the concentration range of 1 μM to 200 μM with a limit of detection of 0.1 μM. The results indicate that ANTS-anchored Zn-Al-CO3-LDH particles can afford a very sensitive system for the sensing FA in aqueous solution.

Parallelizing flow-accumulation calculations on graphics processing units—From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

NASA Astrophysics Data System (ADS)

Qin, Cheng-Zhi; Zhan, Lijun

2012-06-01

As one of the important tasks in digital terrain analysis, the calculation of flow accumulations from gridded digital elevation models (DEMs) usually involves two steps in a real application: (1) using an iterative DEM preprocessing algorithm to remove the depressions and flat areas commonly contained in real DEMs, and (2) using a recursive flow-direction algorithm to calculate the flow accumulation for every cell in the DEM. Because both algorithms are computationally intensive, quick calculation of the flow accumulations from a DEM (especially for a large area) presents a practical challenge to personal computer (PC) users. In recent years, rapid increases in hardware capacity of the graphics processing units (GPUs) provided in modern PCs have made it possible to meet this challenge in a PC environment. Parallel computing on GPUs using a compute-unified-device-architecture (CUDA) programming model has been explored to speed up the execution of the single-flow-direction algorithm (SFD). However, the parallel implementation on a GPU of the multiple-flow-direction (MFD) algorithm, which generally performs better than the SFD algorithm, has not been reported. Moreover, GPU-based parallelization of the DEM preprocessing step in the flow-accumulation calculations has not been addressed. This paper proposes a parallel approach to calculate flow accumulations (including both iterative DEM preprocessing and a recursive MFD algorithm) on a CUDA-compatible GPU. For the parallelization of an MFD algorithm (MFD-md), two different parallelization strategies using a GPU are explored. The first parallelization strategy, which has been used in the existing parallel SFD algorithm on GPU, has the problem of computing redundancy. Therefore, we designed a parallelization strategy based on graph theory. The application results show that the proposed parallel approach to calculate flow accumulations on a GPU performs much faster than either sequential algorithms or other parallel GPU-based algorithms based on existing parallelization strategies.

Gis-Based Route Finding Using ANT Colony Optimization and Urban Traffic Data from Different Sources

NASA Astrophysics Data System (ADS)

Davoodi, M.; Mesgari, M. S.

2015-12-01

Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

Prediction of Sybil attack on WSN using Bayesian network and swarm intelligence

NASA Astrophysics Data System (ADS)

Muraleedharan, Rajani; Ye, Xiang; Osadciw, Lisa Ann

2008-04-01

Security in wireless sensor networks is typically sacrificed or kept minimal due to limited resources such as memory and battery power. Hence, the sensor nodes are prone to Denial-of-service attacks and detecting the threats is crucial in any application. In this paper, the Sybil attack is analyzed and a novel prediction method, combining Bayesian algorithm and Swarm Intelligence (SI) is proposed. Bayesian Networks (BN) is used in representing and reasoning problems, by modeling the elements of uncertainty. The decision from the BN is applied to SI forming an Hybrid Intelligence Scheme (HIS) to re-route the information and disconnecting the malicious nodes in future routes. A performance comparison based on the prediction using HIS vs. Ant System (AS) helps in prioritizing applications where decisions are time-critical.

An Information Theoretic Framework and Self-organizing Agent- based Sensor Network Architecture for Power Plant Condition Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loparo, Kenneth; Kolacinski, Richard; Threeanaew, Wanchat

A central goal of the work was to enable both the extraction of all relevant information from sensor data, and the application of information gained from appropriate processing and fusion at the system level to operational control and decision-making at various levels of the control hierarchy through: 1. Exploiting the deep connection between information theory and the thermodynamic formalism, 2. Deployment using distributed intelligent agents with testing and validation in a hardware-in-the loop simulation environment. Enterprise architectures are the organizing logic for key business processes and IT infrastructure and, while the generality of current definitions provides sufficient flexibility, the currentmore » architecture frameworks do not inherently provide the appropriate structure. Of particular concern is that existing architecture frameworks often do not make a distinction between ``data'' and ``information.'' This work defines an enterprise architecture for health and condition monitoring of power plant equipment and further provides the appropriate foundation for addressing shortcomings in current architecture definition frameworks through the discovery of the information connectivity between the elements of a power generation plant. That is, to identify the correlative structure between available observations streams using informational measures. The principle focus here is on the implementation and testing of an emergent, agent-based, algorithm based on the foraging behavior of ants for eliciting this structure and on measures for characterizing differences between communication topologies. The elicitation algorithms are applied to data streams produced by a detailed numerical simulation of Alstom’s 1000 MW ultra-super-critical boiler and steam plant. The elicitation algorithm and topology characterization can be based on different informational metrics for detecting connectivity, e.g. mutual information and linear correlation.« less

Collective choice in ants: the role of protein and carbohydrates ratios.

PubMed

Arganda, S; Nicolis, S C; Perochain, A; Péchabadens, C; Latil, G; Dussutour, A

2014-10-01

In a foraging context, social insects make collective decisions from individuals responding to local information. When faced with foods varying in quality, ants are known to be able to select the best food source using pheromone trails. Until now, studies investigating collective decisions have focused on single nutrients, mostly carbohydrates. In the environment, the foods available are a complex mixture and are composed of various nutrients, available in different forms. In this paper, we explore the effect of protein to carbohydrate ratio on ants' ability to detect and choose between foods with different protein characteristics (free amino acids or whole proteins). In a two-choice set up, Argentine ants Linepithema humile were presented with two artificial foods containing either whole protein or amino acids in two different dietary conditions: high protein food or high carbohydrate food. At the collective level, when ants were faced with high carbohydrate foods, they did not show a preference between free amino acids or whole proteins, while a preference for free amino acids emerged when choosing between high protein foods. At the individual level, the probability of feeding was higher for high carbohydrates food and for foods containing free amino acids. Two mathematical models were developed to evaluate the importance of feeding probability in collective food selection. A first model in which a forager deposits pheromone only after feeding, and a second model in which a forager always deposits pheromone, but with greater intensity after feeding. Both models were able to predict free amino acid selection, however the second one was better able to reproduce the experimental results suggesting that modulating trail strength according to feeding probability is likely the mechanism explaining amino acid preference at a collective level in Argentine ants. Copyright © 2014 Elsevier Ltd. All rights reserved.

A novel hybrid meta-heuristic technique applied to the well-known benchmark optimization problems

NASA Astrophysics Data System (ADS)

Abtahi, Amir-Reza; Bijari, Afsane

2017-03-01

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition, the proposed hybrid algorithm uses SA to make a balance between exploration and exploitation phases. The proposed hybrid algorithm is compared with several meta-heuristic methods, including genetic algorithm (GA), HS, and ICA on several well-known benchmark instances. The comprehensive experiments and statistical analysis on standard benchmark functions certify the superiority of the proposed method over the other algorithms. The efficacy of the proposed hybrid algorithm is promising and can be used in several real-life engineering and management problems.

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

PubMed

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

Efficient sequential and parallel algorithms for finding edit distance based motifs.

PubMed

Pal, Soumitra; Xiao, Peng; Rajasekaran, Sanguthevar

2016-08-18

Motif search is an important step in extracting meaningful patterns from biological data. The general problem of motif search is intractable and there is a pressing need to develop efficient, exact and approximation algorithms to solve this problem. In this paper, we present several novel, exact, sequential and parallel algorithms for solving the (l,d) Edit-distance-based Motif Search (EMS) problem: given two integers l,d and n biological strings, find all strings of length l that appear in each input string with atmost d errors of types substitution, insertion and deletion. One popular technique to solve the problem is to explore for each input string the set of all possible l-mers that belong to the d-neighborhood of any substring of the input string and output those which are common for all input strings. We introduce a novel and provably efficient neighborhood exploration technique. We show that it is enough to consider the candidates in neighborhood which are at a distance exactly d. We compactly represent these candidate motifs using wildcard characters and efficiently explore them with very few repetitions. Our sequential algorithm uses a trie based data structure to efficiently store and sort the candidate motifs. Our parallel algorithm in a multi-core shared memory setting uses arrays for storing and a novel modification of radix-sort for sorting the candidate motifs. The algorithms for EMS are customarily evaluated on several challenging instances such as (8,1), (12,2), (16,3), (20,4), and so on. The best previously known algorithm, EMS1, is sequential and in estimated 3 days solves up to instance (16,3). Our sequential algorithms are more than 20 times faster on (16,3). On other hard instances such as (9,2), (11,3), (13,4), our algorithms are much faster. Our parallel algorithm has more than 600 % scaling performance while using 16 threads. Our algorithms have pushed up the state-of-the-art of EMS solvers and we believe that the techniques introduced in this paper are also applicable to other motif search problems such as Planted Motif Search (PMS) and Simple Motif Search (SMS).

Ocelli contribute to the encoding of celestial compass information in the Australian desert ant Melophorus bagoti.

PubMed

Schwarz, Sebastian; Albert, Laurence; Wystrach, Antoine; Cheng, Ken

2011-03-15

Many animal species, including some social hymenoptera, use the visual system for navigation. Although the insect compound eyes have been well studied, less is known about the second visual system in some insects, the ocelli. Here we demonstrate navigational functions of the ocelli in the visually guided Australian desert ant Melophorus bagoti. These ants are known to rely on both visual landmark learning and path integration. We conducted experiments to reveal the role of ocelli in the perception and use of celestial compass information and landmark guidance. Ants with directional information from their path integration system were tested with covered compound eyes and open ocelli on an unfamiliar test field where only celestial compass cues were available for homing. These full-vector ants, using only their ocelli for visual information, oriented significantly towards the fictive nest on the test field, indicating the use of celestial compass information that is presumably based on polarised skylight, the sun's position or the colour gradient of the sky. Ants without any directional information from their path-integration system (zero-vector) were tested, also with covered compound eyes and open ocelli, on a familiar training field where they have to use the surrounding panorama to home. These ants failed to orient significantly in the homeward direction. Together, our results demonstrated that M. bagoti could perceive and process celestial compass information for directional orientation with their ocelli. In contrast, the ocelli do not seem to contribute to terrestrial landmark-based navigation in M. bagoti.

Dramatic Differences in Gut Bacterial Densities Correlate with Diet and Habitat in Rainforest Ants.

PubMed

Sanders, Jon G; Lukasik, Piotr; Frederickson, Megan E; Russell, Jacob A; Koga, Ryuichi; Knight, Rob; Pierce, Naomi E

2017-10-01

Abundance is a key parameter in microbial ecology, and important to estimates of potential metabolite flux, impacts of dispersal, and sensitivity of samples to technical biases such as laboratory contamination. However, modern amplicon-based sequencing techniques by themselves typically provide no information about the absolute abundance of microbes. Here, we use fluorescence microscopy and quantitative polymerase chain reaction as independent estimates of microbial abundance to test the hypothesis that microbial symbionts have enabled ants to dominate tropical rainforest canopies by facilitating herbivorous diets, and compare these methods to microbial diversity profiles from 16S rRNA amplicon sequencing. Through a systematic survey of ants from a lowland tropical forest, we show that the density of gut microbiota varies across several orders of magnitude among ant lineages, with median individuals from many genera only marginally above detection limits. Supporting the hypothesis that microbial symbiosis is important to dominance in the canopy, we find that the abundance of gut bacteria is positively correlated with stable isotope proxies of herbivory among canopy-dwelling ants, but not among ground-dwelling ants. Notably, these broad findings are much more evident in the quantitative data than in the 16S rRNA sequencing data. Our results provide quantitative context to the potential role of bacteria in facilitating the ants' dominance of the tropical rainforest canopy, and have broad implications for the interpretation of sequence-based surveys of microbial diversity. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

A Single-Center, Randomized, Double-Blind, Placebo-Controlled Clinical Trial of the Effectiveness of ANT1 Soybean Extract Cream on Skin Recovery After Nd: YAG Laser Treatment.

PubMed

Hsieh, Meng-Chien; Wu, Yi-Chia; Huang, Shu-Hung; Kuo, Yur-Ren; Lee, Su-Shin

2018-02-01

Nd:YAG laser has been used extensively for its versatility in treating many common aesthetic problems, but numerous adverse effects are often complained by recipients of Nd:YAG laser. This study introduces the ANT1 soybean extract cream, which was formulated to alleviate adverse effects after laser therapy. This study explores whether ANT1 enhances the repair mechanism of the postlaser skin, decreases laser-induced complication, and shortens recovery time. The study also aims to pinpoint the ANT1 concentration that is most effective in improving the skin condition after Nd-YAG laser therapy. This study was a single-center, randomized, double-blind, placebo-controlled trial. Patients eligible for the study were Asian women, aged 25 to 40 years, who were free of dermatological diseases and allergic reaction. There were a total of 45 subjects. Each subject received a session of Nd-YAG laser therapy every 2 weeks, totaling 3 sessions. Facial skin assessment was achieved via VISIA complexion analysis. VISIA complexion analysis quantitatively assessed the skin condition and tracked the recovery progress of each subject at baseline, immediately after all 3 laser sessions, and a week after the final laser treatment. Skin condition was evaluated by VISIA complexion analysis. Skin condition was recorded in aspects of pigmented spots, wrinkles, texture, pores, and red area. After Nd-YAG laser therapy, postlaser inflammation was observed in all subjects. Throughout the laser sessions and the outpatient follow-up clinic, the adverse effects of laser therapy, such as redness, spots, wrinkles, pores, and textures, decreased with the use of ANT1 cream. There has been a marked effect in wrinkle reduction in the patients who received a higher concentration of ANT1 cream (P ≤ 0.05). Statistically significant improvement in spots and pores is also seen (P ≤ 0.05). Through this study, the results suggest that the application of ANT1 soybean extract cream ameliorates the complications and enhances the cosmetic effects of Nd-YAG laser therapy. A higher concentration of the ANT1 cream significantly reduces wrinkles and redness after laser. All in all, this study proves that the ANT1 soy extract cream may be a useful addition to postlaser care for an overall enhancement in skin condition and recovery.

Antimicrobial, antioxidant and sensory features of eugenol, carvacrol and trans-anethole in active packaging for organic ready-to-eat iceberg lettuce.

PubMed

Wieczyńska, Justyna; Cavoski, Ivana

2018-09-01

In this study, bio-based emitting sachets containing eugenol (EUG), carvacrol (CAR) and trans-anethole (ANT) were inserted into cellulose (CE) and polypropylene (PP) pillow packages of organic ready-to-eat (RTE) iceberg lettuce to investigate their functional features. EUG, CAR and ANT sachets in CE; and CAR in PP packages showed antimicrobial activities against coliforms (Δlog CFU g -1 of -1.38, -0.91, -0.93 and -0.93, respectively). EUG and ANT sachets in both packages reduced discoloration (ΔE of 9.5, 1.8, 9.4 and 5.6, respectively). ANT in both, and EUG only in PP packages induced biosynthesis of caffeoyl derivatives (C a T A , D i C a T A , D i C a Q A ), total phenolics and antioxidant activity (FRAP). Also, ANT and EUG in both packages improved overall freshness and odor. Principal component analysis separated ANT and EUG from CAR in both packages. The Pearson correlation confirmed that overall quality improvements were more pronounced by ANT inside the packages in comparison to EUG and CAR. Copyright © 2018 Elsevier Ltd. All rights reserved.

Determining the most effective concentration of cypermethrin and the appropriate carrier particle size for fire ant (Hymenoptera: Formicidae) bait.

PubMed

Kafle, Lekhnath; Shih, Cheng-Jen

2012-03-01

The purpose of this study was to determine the most effective particle size of DDGS (distiller's dried grains with solubles) as fire ant bait carrier, as well as the most effective concentration of cypermethrin as a toxicant against the red imported fire ant (RIFA) Solenopsis invicta Buren under laboratory conditions. The DDGS particle size did not affect the fire ant's preference for the bait, but it did affect the mass of DDGS being carried back to the nest. The size of the DDGS particles and the mass of DDGS being carried back to the nest were positively correlated. The most efficient particle size of DDGS was 0.8-2 mm. The concentration of cypermethrin has a specific range for killing fire ants in an efficient manner. Neither a very low nor a very high concentration of cypermethrin was able to kill fire ants efficiently. The most effective concentration of cypermethrin was 0.13% in DDGS when mixed with 15% shrimp shell powders and 11% soybean oil. Based on its ability to kill fire ants when mixed with cypermethrin, as well as the advantage of having a larger area coverage when sprayed in the field, DDGS as the carrier and cypermethrin as the toxicant can be considered to be an efficient way to prepare fire ant bait for controlling fire ants in infested areas. Copyright © 2012 Society of Chemical Industry.

Suppressing tawny crazy ant (Nylanderia fulva) by RNAi technology.

PubMed

Meng, Jia; Lei, Jiaxin; Davitt, Andrew; Holt, Jocelyn R; Huang, Jian; Gold, Roger; Vargo, Edward L; Tarone, Aaron M; Zhu-Salzman, Keyan

2018-05-22

The tawny crazy ant (Nylanderia fulva) is a new invasive pest in the United States. At present, its management mainly relies on the use of synthetic insecticides, which are generally ineffective at producing lasting control of the pest, necessitating alternative environmentally friendly measures. In this study, we evaluated the feasibility of gene silencing to control this ant species. Six housekeeping genes encoding actin (NfActin), coatomer subunit β (NfCOPβ), arginine kinase (NfArgK), and V-type proton ATPase subunits A (NfvATPaseA), B (NfvATPaseB) and E (NfvATPaseE) were cloned. Phylogenetic analysis revealed high sequence similarity to homologs from other ant species, particularly the Florida carpenter ant (Camponotus floridanus). To silence these genes, vector L4440 was used to generate 6 specific RNAi constructs for bacterial expression. Heat-inactivated, dsRNA-expressing Escherichia coli were incorporated into artificial diet. Worker ants exhibited reduced endogenous gene expression after feeding on such diet for 9 days. However, only ingestion of dsRNAs of NfCOPβ (a gene involved in protein trafficking) and NfArgK (a cellular energy reserve regulatory gene in invertebrates) caused modest but significantly higher ant mortality than the control. These results suggest that bacterially expressed dsRNA can be orally delivered to ant cells as a mean to target its vulnerabilities. Improved efficacy is necessary for the RNAi-based approach to be useful in tawny crazy ant management. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Predictive Cache Modeling and Analysis

DTIC Science & Technology

2011-11-01

metaheuristic /bin-packing algorithm to optimize task placement based on task communication characterization. Our previous work on task allocation showed...Cache Miss Minimization Technology To efficiently explore combinations and discover nearly-optimal task-assignment algorithms , we extended to our...it was possible to use our algorithmic techniques to decrease network bandwidth consumption by ~25%. In this effort, we adapted these existing

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems

PubMed Central

Tuo, Shouheng; Yong, Longquan; Deng, Fang’an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application. PMID:28403224

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

PubMed

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

Unsupervised algorithms for intrusion detection and identification in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2009-05-01

In previous work by the author, parameters across network protocol layers were selected as features in supervised algorithms that detect and identify certain intrusion attacks on wireless ad hoc sensor networks (WSNs) carrying multisensor data. The algorithms improved the residual performance of the intrusion prevention measures provided by any dynamic key-management schemes and trust models implemented among network nodes. The approach of this paper does not train algorithms on the signature of known attack traffic, but, instead, the approach is based on unsupervised anomaly detection techniques that learn the signature of normal network traffic. Unsupervised learning does not require the data to be labeled or to be purely of one type, i.e., normal or attack traffic. The approach can be augmented to add any security attributes and quantified trust levels, established during data exchanges among nodes, to the set of cross-layer features from the WSN protocols. A two-stage framework is introduced for the security algorithms to overcome the problems of input size and resource constraints. The first stage is an unsupervised clustering algorithm which reduces the payload of network data packets to a tractable size. The second stage is a traditional anomaly detection algorithm based on a variation of support vector machines (SVMs), whose efficiency is improved by the availability of data in the packet payload. In the first stage, selected algorithms are adapted to WSN platforms to meet system requirements for simple parallel distributed computation, distributed storage and data robustness. A set of mobile software agents, acting like an ant colony in securing the WSN, are distributed at the nodes to implement the algorithms. The agents move among the layers involved in the network response to the intrusions at each active node and trustworthy neighborhood, collecting parametric values and executing assigned decision tasks. This minimizes the need to move large amounts of audit-log data through resource-limited nodes and locates routines closer to that data. Performance of the unsupervised algorithms is evaluated against the network intrusions of black hole, flooding, Sybil and other denial-of-service attacks in simulations of published scenarios. Results for scenarios with intentionally malfunctioning sensors show the robustness of the two-stage approach to intrusion anomalies.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

Exploring the Peer Interaction Effects on Learning Achievement in a Social Learning Platform Based on Social Network Analysis

ERIC Educational Resources Information Center

Lin, Yu-Tzu; Chen, Ming-Puu; Chang, Chia-Hu; Chang, Pu-Chen

2017-01-01

The benefits of social learning have been recognized by existing research. To explore knowledge distribution in social learning and its effects on learning achievement, we developed a social learning platform and explored students' behaviors of peer interactions by the proposed algorithms based on social network analysis. An empirical study was…

ANTS — a simulation package for secondary scintillation Anger-camera type detector in thermal neutron imaging

NASA Astrophysics Data System (ADS)

Morozov, A.; Defendi, I.; Engels, R.; Fraga, F. A. F.; Fraga, M. M. F. R.; Guerard, B.; Jurkovic, M.; Kemmerling, G.; Manzin, G.; Margato, L. M. S.; Niko, H.; Pereira, L.; Petrillo, C.; Peyaud, A.; Piscitelli, F.; Raspino, D.; Rhodes, N. J.; Sacchetti, F.; Schooneveld, E. M.; Van Esch, P.; Zeitelhack, K.

2012-08-01

A custom and fully interactive simulation package ANTS (Anger-camera type Neutron detector: Toolkit for Simulations) has been developed to optimize the design and operation conditions of secondary scintillation Anger-camera type gaseous detectors for thermal neutron imaging. The simulation code accounts for all physical processes related to the neutron capture, energy deposition pattern, drift of electrons of the primary ionization and secondary scintillation. The photons are traced considering the wavelength-resolved refraction and transmission of the output window. Photo-detection accounts for the wavelength-resolved quantum efficiency, angular response, area sensitivity, gain and single-photoelectron spectra of the photomultipliers (PMTs). The package allows for several geometrical shapes of the PMT photocathode (round, hexagonal and square) and offers a flexible PMT array configuration: up to 100 PMTs in a custom arrangement with the square or hexagonal packing. Several read-out patterns of the PMT array are implemented. Reconstruction of the neutron capture position (projection on the plane of the light emission) is performed using the center of gravity, maximum likelihood or weighted least squares algorithm. Simulation results reproduce well the preliminary results obtained with a small-scale detector prototype. ANTS executables can be downloaded from http://coimbra.lip.pt/~andrei/.

Using Swarming Agents for Scalable Security in Large Network Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crouse, Michael; White, Jacob L.; Fulp, Errin W.

2011-09-23

The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtualmore » colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.« less

Ant brood function as life preservers during floods.

PubMed

Purcell, Jessica; Avril, Amaury; Jaffuel, Geoffrey; Bates, Sarah; Chapuisat, Michel

2014-01-01

Social organisms can surmount many ecological challenges by working collectively. An impressive example of such collective behavior occurs when ants physically link together into floating 'rafts' to escape from flooded habitat. However, raft formation may represent a social dilemma, with some positions posing greater individual risks than others. Here, we investigate the position and function of different colony members, and the costs and benefits of this functional geometry in rafts of the floodplain-dwelling ant Formica selysi. By causing groups of ants to raft in the laboratory, we observe that workers are distributed throughout the raft, queens are always in the center, and 100% of brood items are placed on the base. Through a series of experiments, we show that workers and brood are extremely resistant to submersion. Both workers and brood exhibit high survival rates after they have rafted, suggesting that occupying the base of the raft is not as costly as expected. The placement of all brood on the base of one cohesive raft confers several benefits: it preserves colony integrity, takes advantage of brood buoyancy, and increases the proportion of workers that immediately recover after rafting.

Geographic and taxonomic distribution of a positive interaction: ant-tended homopterans indirectly benefit figs across southern Africa.

PubMed

Cushman, J Hall; Compton, Stephen G; Zachariades, Costas; Ware, Anthony B; Nefdt, Rory J C; Rashbrook, Vanessa K

1998-09-01

Although species pairs and assemblages often occur across geographic regions, ecologists know very little about the outcome of their interactions on such large spatial scales. Here, we assess the geographic distribution and taxonomic diversity of a positive interaction involving ant-tended homopterans and fig trees in the genus Ficus. Previous experimental studies at a few locations in South Africa indicated that Ficus sur indirectly benefited from the presence of a homopteran (Hilda patruelis) because it attracted ants (primarily Pheidole megacephala) that reduced the effects of both pre-dispersal ovule gallers and parasitoids of pollinating wasps. Based on this work, we evaluated three conditions that must be met in order to support the hypothesis that this indirect interaction involves many fig species and occurs throughout much of southern Africa and Madagascar. Data on 429 trees distributed among five countries indicated that 20 of 38 Ficus species, and 46% of all trees sampled, had ants on their figs. Members of the Sycomorus subgenus were significantly more likely to attract ants than those in the Urostigma subgenus, and ant-colonization levels on these species were significantly greater than for Urostigma species. On average, each ant-occupied F.sur tree had 37% of its fig crop colonized by ants, whereas the value was 24% for other Ficus species. H. patruelis was the most common source for attracting ants, although figs were also attacked by a range of other ant-tended homopterans. P. megacephala was significantly more common on figs than other ant species, being present on 58% of sampled trees. Ant densities commonly exceeded 4.5 per fig, which a field experiment indicated was sufficient to provide protection from ovule gallers and parasitoids of pollinators. Forty-nine percent of all colonized F. sur trees sampled had ant densities equal to or greater than 4.5 per fig, whereas this value was 23% for other Ficus species. We conclude that there is considerable evidence to suggest that this indirect interaction occurs across four southern African countries and Madagascar, and involves many Ficus species.

A Revision of Male Ants of the Malagasy Amblyoponinae (Hymenoptera: Formicidae) with Resurrections of the Genera Stigmatomma and Xymmer

PubMed Central

Yoshimura, Masashi; Fisher, Brian L.

2012-01-01

In a male-based revision of ants of the subfamily Amblyoponinae from the Southwest Indian Ocean islands (SWIO: Comoros, Madagascar, Mauritius, Mayotte, Reunion, and Seychelles), we explore and reconsider male morphological characters that distinguish genera within the group. Our investigation redefines Amblyopone Erichson sensu Brown (1960), here referred to as Amblyopone sensu lato, into three genera: Xymmer Santschi stat. rev., Amblyopone sensu stricto, Stigmatomma Roger stat. rev. All species names under Amblyopone s. l. reassign into Xymmer and Amblyopone s. s., which are small, well-defined genera, and Stigmatomma, a large group with a generic delimitation that still needs further refinement. Based on a study of male mandible characters and our scenario for mandibular evolution of the worker caste within Amblyopone s. l, we conclude that Amblyopone s. s. nests outside of XMAS (Xymmer+Mystrium+Adetomyrma+Stigmatomma) clade. The following names are transferred from Amblyopone s. l. to Xymmer as comb. rev.: muticus. The following names are transferred from Amblyopone s. l. to Stigmatomma as comb. rev.: amblyops, armigerum, bellii, bierigi, bruni, celata, chilense, denticulatum, elongatum, emeryi, feae, impressifrons, luzonicum, minuta, normandi, oregonense, pallipes, quadratum, reclinatum, rothneyi, santschii, saundersi, silvestrii, zwaluwenburgi; as comb. nov.: agostii, annae, besucheti, boltoni, caliginosum, cleae, crenatum, degeneratum, egregium, electrinum, eminia, exiguum, falcatum, ferrugineum, fulvidum, gaetulicum, gingivalis, glauerti, gnoma, gracile, groehni, heraldoi, lucidum, lurilabes, monrosi, mystriops, noonadan, octodentatum, ophthalmicum, orizabanum, papuanum, pertinax, pluto, punctulatum, rubiginoum, sakaii, smithi, trigonignathum, trilobum, wilsoni, zaojun, and testaceum. A male-based key to the genera of Malagasy amblyoponine ants, their diagnoses, and a discussion of the evolution of the morphological character of males in the subfamily are given, and the distinguishing characters of each are illustrated. In addition, our results predict that Paraprionopelta belongs in the XMAS clade and that Concoctio should have males with two mandibular teeth. PMID:22496722

An uneasy alliance: a nesting association between aggressive ants and equally fierce social wasps.

PubMed

Servigne, Pablo; Orivel, Jérôme; Azémar, Frédéric; Carpenter, James; Dejean, Alain; Corbara, Bruno

2018-04-16

Although the Neotropical territorially dominant arboreal ant Azteca chartifex Forel is very aggressive towards any intruder, its populous colonies tolerate the close presence of the fierce polistine wasp Polybia rejecta (F.). In French Guiana, 83.33% of the 48 P. rejecta nests recorded were found side by side with those of A. chartifex. This nesting association results in mutual protection from predators (i.e., the wasps protected from army ants; the ants protected from birds). We conducted field studies, laboratory-based behavioral experiments and chemical analyses to elucidate the mechanisms allowing the persistence of this association. Due to differences in the cuticular profiles of the two species, we eliminated thepossibility of chemical mimicry. Also, analyses of the carton nests did not reveal traces of marking on the envelopes. Because ant forager flows were not perturbed by extracts from the wasps' Dufour's and venom glands, we rejected any hypothetical action of repulsive chemicals. Nevertheless, we noted that the wasps 'scraped' the surface of the upper part of their nest envelope using their mandibles, likely removing the ants' scent trails, and an experiment showed that ant foragers were perturbed by the removal of their scent trails. This leads us to use the term 'erasure hypothesis'. Thus, this nesting association persists thanks to a relative tolerance by the ants towards wasp presence and the behavior of the wasps that allows them to 'contain' their associated ants through the elimination of their scent trails, direct attacks, 'wing-buzzing' behavior and ejecting the ants. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Ant groups optimally amplify the effect of transiently informed individuals

NASA Astrophysics Data System (ADS)

Gelblum, Aviram; Pinkoviezky, Itai; Fonio, Ehud; Ghosh, Abhijit; Gov, Nir; Feinerman, Ofer

2015-07-01

To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.

Mathematical model for path selection by ants between nest and food source.

PubMed

Bodnar, Marek; Okińczyc, Natalia; Vela-Pérez, M

2017-03-01

Several models have been proposed to describe the behavior of ants when moving from nest to food sources. Most of these studies where based on numerical simulations with no mathematical justification. In this paper, we propose a mechanism for the formation of paths of minimal length between two points by a collection of individuals undergoing reinforced random walks taking into account not only the lengths of the paths but also the angles (connected to the preference of ants to move along straight lines). Our model involves reinforcement (pheromone accumulation), persistence (tendency to preferably follow straight directions in absence of any external effect) and takes into account the bifurcation angles of each edge (represented by a probability of willingness of choosing the path with the smallest angle). We describe analytically the results for 2 ants and different path lengths and numerical simulations for several ants. Copyright © 2016 Elsevier Inc. All rights reserved.

Ant groups optimally amplify the effect of transiently informed individuals

PubMed Central

Gelblum, Aviram; Pinkoviezky, Itai; Fonio, Ehud; Ghosh, Abhijit; Gov, Nir; Feinerman, Ofer

2015-01-01

To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge. PMID:26218613

Adaptive block online learning target tracking based on super pixel segmentation

NASA Astrophysics Data System (ADS)

Cheng, Yue; Li, Jianzeng

2018-04-01

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments

PubMed Central

Filho, Raimir Holanda; Rabêlo, Ricardo de Andrade L.; de Carvalho, Carlos Giovanni N.; Mendes, Douglas Lopes de S.; Costa, Valney da Gama

2018-01-01

Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user’s queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user’s queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios. PMID:29495406

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments.

PubMed

Lemos, Marcus Vinícius de S; Filho, Raimir Holanda; Rabêlo, Ricardo de Andrade L; de Carvalho, Carlos Giovanni N; Mendes, Douglas Lopes de S; Costa, Valney da Gama

2018-02-26

Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user's queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user's queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios.

Intraspecific Variation among Social Insect Colonies: Persistent Regional and Colony-Level Differences in Fire Ant Foraging Behavior

PubMed Central

Bockoven, Alison A.; Wilder, Shawn M.; Eubanks, Micky D.

2015-01-01

Individuals vary within a species in many ecologically important ways, but the causes and consequences of such variation are often poorly understood. Foraging behavior is among the most profitable and risky activities in which organisms engage and is expected to be under strong selection. Among social insects there is evidence that within-colony variation in traits such as foraging behavior can increase colony fitness, but variation between colonies and the potential consequences of such variation are poorly documented. In this study, we tested natural populations of the red imported fire ant, Solenopsis invicta, for the existence of colony and regional variation in foraging behavior and tested the persistence of this variation over time and across foraging habitats. We also reared single-lineage colonies in standardized environments to explore the contribution of colony lineage. Fire ants from natural populations exhibited significant and persistent colony and regional-level variation in foraging behaviors such as extra-nest activity, exploration, and discovery of and recruitment to resources. Moreover, colony-level variation in extra-nest activity was significantly correlated with colony growth, suggesting that this variation has fitness consequences. Lineage of the colony had a significant effect on extra-nest activity and exploratory activity and explained approximately half of the variation observed in foraging behaviors, suggesting a heritable component to colony-level variation in behavior. PMID:26197456

Path integration mediated systematic search: a Bayesian model.

PubMed

Vickerstaff, Robert J; Merkle, Tobias

2012-08-21

The systematic search behaviour is a backup system that increases the chances of desert ants finding their nest entrance after foraging when the path integrator has failed to guide them home accurately enough. Here we present a mathematical model of the systematic search that is based on extensive behavioural studies in North African desert ants Cataglyphis fortis. First, a simple search heuristic utilising Bayesian inference and a probability density function is developed. This model, which optimises the short-term nest detection probability, is then compared to three simpler search heuristics and to recorded search patterns of Cataglyphis ants. To compare the different searches a method to quantify search efficiency is established as well as an estimate of the error rate in the ants' path integrator. We demonstrate that the Bayesian search heuristic is able to automatically adapt to increasing levels of positional uncertainty to produce broader search patterns, just as desert ants do, and that it outperforms the three other search heuristics tested. The searches produced by it are also arguably the most similar in appearance to the ant's searches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Defensive traits exhibit an evolutionary trade-off and drive diversification in ants.

PubMed

Blanchard, Benjamin D; Moreau, Corrie S

2017-02-01

Evolutionary biologists have long predicted that evolutionary trade-offs among traits should constrain morphological divergence and species diversification. However, this prediction has yet to be tested in a broad evolutionary context in many diverse clades, including ants. Here, we reconstruct an expanded ant phylogeny representing 82% of ant genera, compile a new family-wide trait database, and conduct various trait-based analyses to show that defensive traits in ants do exhibit an evolutionary trade-off. In particular, the use of a functional sting negatively correlates with a suite of other defensive traits including spines, large eye size, and large colony size. Furthermore, we find that several of the defensive traits that trade off with a sting are also positively correlated with each other and drive increased diversification, further suggesting that these traits form a defensive suite. Our results support the hypothesis that trade-offs in defensive traits significantly constrain trait evolution and influence species diversification in ants. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Pro-social behaviour of ants depends on their ecological niche-Rescue actions in species from tropical and temperate regions.

PubMed

Miler, Krzysztof; Yahya, Bakhtiar Effendi; Czarnoleski, Marcin

2017-11-01

Some ants display rescue behaviour, which is performed by nearby nestmates and directed at individuals in danger. Here, using several ant species, we demonstrate that rescue behaviour expression matches predicted occurrences based on certain aspects of species' ecological niches. Rescue occurred in sand-dwelling ants exposed both to co-occurring antlion larvae, representing the threat of being captured by a predator, and to nest cave-ins, representing the threat of being trapped in a collapsed nest chamber. Rescue also occurred in forest groundcover ants exposed to certain entrapment situations. However, rescue never occurred in species associated with open plains, which nest in hardened soils and forage largely on herbaceous plants, or in ants living in close mutualistic relationships with their host plants. In addition, because we tested each species in two types of tests, antlion larva capture tests and artificial entrapment tests, we highlight the importance of accounting for test context in studying rescue behaviour expression. Copyright © 2017 Elsevier B.V. All rights reserved.

High Resolution Imaging Using Phase Retrieval. Volume 2

DTIC Science & Technology

1991-10-01

aberrations of the telescope. It will also correct aberrations due to atmospheric turbulence for a ground- based telescope, and can be used with several other...retrieval algorithm, based on the Ayers/Dainty blind deconvolution algorithm, was also developed. A new methodology for exploring the uniqueness of phase...Simulation Experiments ..................... 42 3.3.1 Initial Simulations with Noisy Modulus Data ..... 45 3.3.2 Simulations of a Space- Based Amplitude

Myrmica rubra ants are more communicative when young: Do they need experience?

PubMed

Atsarkina, Natalia V; Panteleeva, Sofia N; Reznikova, Zhanna I

2017-05-01

The role of experience in the development of communication in animals is a matter of special interest to many ethologists and psychologists. Ants are known to possess sophisticated and flexible communication systems based mainly on their antennal movements (Reznikova & Ryabko, 2011). However, it is still enigmatic whether young ants need stimulation performances by adults to develop their communication capacities. Experiments with pairwise interactions of Myrmica rubra ants revealed significant differences in individual behavior and the mode of communication in callow (newly emerged) and adult workers. Adult ants are much more mobile than callow ones, and they switch their behavior depending on what partner they interact with, whereas callows behave independently. Adults communicate with callows and queens much longer than with other adults. Both callows and queens seem to be rather attractive to adults, although in different ways. Adults pay close attention to callow ants and initiate prolonged antennal contacts with them, touching their bodies and not leaving them alone. Young (callow) ants appear to be more communicative than adults, and they are equally ready to communicate with each other and with adults. Antennal movements are slow and clumsy in young ants, and they often switch from communication to other activities. It is likely that patterns of antennal movements in callows change gradually. Peculiarities of the mode of communication enable us to speculate that young ants need prolonged contacts with adult nestmates to gain the experience of communication. Some parallels with the development of communication skills in vertebrate species are considered. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Overcoming PCR Inhibition During DNA-Based Gut Content Analysis of Ants.

PubMed

Penn, Hannah J; Chapman, Eric G; Harwood, James D

2016-10-01

Generalist predators play an important role in many terrestrial systems, especially within agricultural settings, and ants (Hymenoptera: Formicidae) often constitute important linkages of these food webs, as they are abundant and influential in these ecosystems. Molecular gut content analysis provides a means of delineating food web linkages of ants based on the presence of prey DNA within their guts. Although this method can provide insight, its use on ants has been limited, potentially due to inhibition when amplifying gut content DNA. We designed a series of experiments to determine those ant organs responsible for inhibition and identified variation in inhibition among three species (Tetramorium caespitum (L.), Solenopsis invicta Buren, and Camponotus floridanus (Buckley)). No body segment, other than the gaster, caused significant inhibition. Following dissection, we determined that within the gaster, the digestive tract and crop cause significant levels of inhibition. We found significant differences in the frequency of inhibition between the three species tested, with inhibition most evident in T. caespitum The most effective method to prevent inhibition before DNA extraction was to exude crop contents and crop structures onto UV-sterilized tissue. However, if extracted samples exhibit inhibition, addition of bovine serum albumin to PCR reagents will overcome this problem. These methods will circumvent gut content inhibition within selected species of ants, thereby allowing more detailed and reliable studies of ant food webs. As little is known about the prevalence of this inhibition in other species, it is recommended that the protocols in this study are used until otherwise shown to be unnecessary. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

PubMed

Hong, Xia

2006-07-01

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

Cloud Model Bat Algorithm

PubMed Central

Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi

2014-01-01

Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425

A Modified Artificial Bee Colony Algorithm for p-Center Problems

PubMed Central

Yurtkuran, Alkın

2014-01-01

The objective of the p-center problem is to locate p-centers on a network such that the maximum of the distances from each node to its nearest center is minimized. The artificial bee colony algorithm is a swarm-based meta-heuristic algorithm that mimics the foraging behavior of honey bee colonies. This study proposes a modified ABC algorithm that benefits from a variety of search strategies to balance exploration and exploitation. Moreover, random key-based coding schemes are used to solve the p-center problem effectively. The proposed algorithm is compared to state-of-the-art techniques using different benchmark problems, and computational results reveal that the proposed approach is very efficient. PMID:24616648

Using Motion Planning to Determine the Existence of an Accessible Route in a CAD Environment

ERIC Educational Resources Information Center

Pan, Xiaoshan; Han, Charles S.; Law, Kincho H.

2010-01-01

We describe an algorithm based on motion-planning techniques to determine the existence of an accessible route through a facility for a wheeled mobility device. The algorithm is based on LaValle's work on rapidly exploring random trees and is enhanced to take into consideration the particularities of the accessible route domain. Specifically, the…

Drivers’ Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving

PubMed Central

Du, Mingbo; Mei, Tao; Liang, Huawei; Chen, Jiajia; Huang, Rulin; Zhao, Pan

2016-01-01

This paper describes a real-time motion planner based on the drivers’ visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers’ visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers’ visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms. PMID:26784203

Drivers' Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving.

PubMed

Du, Mingbo; Mei, Tao; Liang, Huawei; Chen, Jiajia; Huang, Rulin; Zhao, Pan

2016-01-15

This paper describes a real-time motion planner based on the drivers' visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers' visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers' visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms.

Complex foraging ecology of the red harvester ant and its effect on the soil seed bank

NASA Astrophysics Data System (ADS)

Luna, Pedro; García-Chávez, Juan Héctor; Dáttilo, Wesley

2018-01-01

Granivory is an important interaction in the arid and semi-arid zones of the world, since seeds form an abundant and nutritious resource in these areas. While species of the genus Pogonomyrmex have been studied in detail as seed predators, their impact on seed abundance in the soil has not yet been explored in sufficient depth. We studied the impact of the harvesting activities of the ant Pogonomyrmex barbatus on seed abundance in the soil of the Zapotitlán valley, Mexico. We found that P. barbatus activity significantly impacts the abundance of seeds in the soil, which is lower in the sites where P. barbatus forages than it is in sites with no recorded foraging. We also found that P. barbatus distributes intact seeds of three tree species, two of which are nurse plants, and could consequently be promoting the establishment of these species. Using tools derived from graph theory, we observed that the ant-seed interactions exhibit a nested pattern; where more depredated seed species seem to be the more spatially abundant in the environment. This study illustrates the complex foraging ecology of the harvester ant P. barbatus and elucidates its effect on the soil seed bank in a semi-arid environment.

Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm.

PubMed

Schroeders, Ulrich; Wilhelm, Oliver; Olaru, Gabriel

2016-01-01

The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems. Therefore, we compare the quality and efficiency of three item selection strategies to derive short scales from an existing long version: a Stepwise COnfirmatory Factor Analytical approach (SCOFA) that maximizes factor loadings and two metaheuristics, specifically an Ant Colony Optimization (ACO) with a tailored user-defined optimization function and a Genetic Algorithm (GA) with an unspecific cost-reduction function. SCOFA compiled short versions were highly reliable, but had poor validity. In contrast, both metaheuristics outperformed SCOFA and produced efficient and psychometrically sound short versions (unidimensional, reliable, sensitive, and valid). We discuss under which circumstances ACO and GA produce equivalent results and provide recommendations for conditions in which it is advisable to use a metaheuristic with an unspecific out-of-the-box optimization function.

The modification of hybrid method of ant colony optimization, particle swarm optimization and 3-OPT algorithm in traveling salesman problem

NASA Astrophysics Data System (ADS)

Hertono, G. F.; Ubadah; Handari, B. D.

2018-03-01

The traveling salesman problem (TSP) is a famous problem in finding the shortest tour to visit every vertex exactly once, except the first vertex, given a set of vertices. This paper discusses three modification methods to solve TSP by combining Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and 3-Opt Algorithm. The ACO is used to find the solution of TSP, in which the PSO is implemented to find the best value of parameters α and β that are used in ACO.In order to reduce the total of tour length from the feasible solution obtained by ACO, then the 3-Opt will be used. In the first modification, the 3-Opt is used to reduce the total tour length from the feasible solutions obtained at each iteration, meanwhile, as the second modification, 3-Opt is used to reduce the total tour length from the entire solution obtained at every iteration. In the third modification, 3-Opt is used to reduce the total tour length from different solutions obtained at each iteration. Results are tested using 6 benchmark problems taken from TSPLIB by calculating the relative error to the best known solution as well as the running time. Among those modifications, only the second and third modification give satisfactory results except the second one needs more execution time compare to the third modifications.

Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm

PubMed Central

Schroeders, Ulrich; Wilhelm, Oliver; Olaru, Gabriel

2016-01-01

The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems. Therefore, we compare the quality and efficiency of three item selection strategies to derive short scales from an existing long version: a Stepwise COnfirmatory Factor Analytical approach (SCOFA) that maximizes factor loadings and two metaheuristics, specifically an Ant Colony Optimization (ACO) with a tailored user-defined optimization function and a Genetic Algorithm (GA) with an unspecific cost-reduction function. SCOFA compiled short versions were highly reliable, but had poor validity. In contrast, both metaheuristics outperformed SCOFA and produced efficient and psychometrically sound short versions (unidimensional, reliable, sensitive, and valid). We discuss under which circumstances ACO and GA produce equivalent results and provide recommendations for conditions in which it is advisable to use a metaheuristic with an unspecific out-of-the-box optimization function. PMID:27893845

Evaluation of Liquid and Bait Insecticides against the Dark Rover Ant (Brachymyrmex patagonicus)

PubMed Central

Miguelena, Javier G.; Baker, Paul B.

2014-01-01

Dark rover ants (Brachymyrmex patagonicus, Mayr) are an exotic ant species native to South America that has recently spread through the southern US. We evaluated the residual activity of three liquid insecticides (indoxacarb, fipronil and lambda-cyhalothrin) as potential barrier treatments against these ants. The factors we considered include the use of a porous or non-porous surface, a short or long exposure time and the changes in insecticide activity after treatment during a 90 day period. We also tested the effect of baits containing three different active ingredients (imidacloprid, sodium tetraborate and indoxacarb) on colony fragments of this species for a 15 day period. Both lambda-cyhalothrin® and indoxacarb® resulted in high levels of ant mortality up to 90 days after application. The results of exposure to fipronil® resembled those from the control treatment. Application of insecticides on a porous surface and the shorter exposure time generally resulted in greater ant survival. Of the baits tested, only the imidacloprid based one decreased ant survival significantly during the evaluation period. Within three days, the imidacloprid bait produced over 50% mortality which increased to over 95% by the end of the experiment. Results from the other two bait treatments were not significantly different from the control. PMID:26462943

Viruses of invasive Argentine ants from the European Main supercolony: characterization, interactions and evolution.

PubMed

Viljakainen, Lumi; Holmberg, Ida; Abril, Sílvia; Jurvansuu, Jaana

2018-06-25

The Argentine ant (Linepithema humile) is a highly invasive pest, yet very little is known about its viruses. We analysed individual RNA-sequencing data from 48 Argentine ant queens to identify and characterisze their viruses. We discovered eight complete RNA virus genomes - all from different virus families - and one putative partial entomopoxvirus genome. Seven of the nine virus sequences were found from ant samples spanning 7 years, suggesting that these viruses may cause long-term infections within the super-colony. Although all nine viruses successfully infect Argentine ants, they have very different characteristics, such as genome organization, prevalence, loads, activation frequencies and rates of evolution. The eight RNA viruses constituted in total 23 different virus combinations which, based on statistical analysis, were non-random, suggesting that virus compatibility is a factor in infections. We also searched for virus sequences from New Zealand and Californian Argentine ant RNA-sequencing data and discovered that many of the viruses are found on different continents, yet some viruses are prevalent only in certain colonies. The viral loads described here most probably present a normal asymptomatic level of infection; nevertheless, detailed knowledge of Argentine ant viruses may enable the design of viral biocontrol methods against this pest.

The Effects of Mindfulness-Based Intervention on Children's Attention Regulation.

PubMed

Felver, Joshua C; Tipsord, Jessica M; Morris, Maxwell J; Racer, Kristina Hiatt; Dishion, Thomas J

2017-08-01

This article describes results from a randomized clinical trial of a mindfulness-based intervention for parents and children, Mindful Family Stress Reduction, on a behavioral measure of attention in youths, the Attention Network Task (ANT). Forty-one parent-child dyads were randomly assigned to either the mindfulness-based intervention condition or a wait-list control. School-age youths completed the ANT before and after the intervention. Results demonstrate significant, medium-size ( f 2 = -.16) intervention effects to the conflict monitoring subsystem of the ANT such that those in the intervention condition decreased in conflict monitoring more than those in the wait-list control. Youths in the intervention condition also showed improvements in their orienting subsystem scores, compared with controls. Mindfulness-based interventions for youths have potential utility to improve attentional self-regulation, and future research should consider incorporating measures of attention into interventions that use mindfulness training.

Exact and Heuristic Algorithms for Runway Scheduling

NASA Technical Reports Server (NTRS)

Malik, Waqar A.; Jung, Yoon C.

2016-01-01

This paper explores the Single Runway Scheduling (SRS) problem with arrivals, departures, and crossing aircraft on the airport surface. Constraints for wake vortex separations, departure area navigation separations and departure time window restrictions are explicitly considered. The main objective of this research is to develop exact and heuristic based algorithms that can be used in real-time decision support tools for Air Traffic Control Tower (ATCT) controllers. The paper provides a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the SRS problem, but may prove unusable for application in real-time environment due to large computation times for moderate sized problems. We next propose a second algorithm that uses heuristics to restrict the search space for the DP based algorithm. A third algorithm based on a combination of insertion and local search (ILS) heuristics is then presented. Simulation conducted for the east side of Dallas/Fort Worth International Airport allows comparison of the three proposed algorithms and indicates that the ILS algorithm performs favorably in its ability to find efficient solutions and its computation times.

The implementation of contour-based object orientation estimation algorithm in FPGA-based on-board vision system

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel; Ershov, Maksim; Strotov, Valery

2016-10-01

This paper describes the implementation of the orientation estimation algorithm in FPGA-based vision system. An approach to estimate an orientation of objects lacking axial symmetry is proposed. Suggested algorithm is intended to estimate orientation of a specific known 3D object based on object 3D model. The proposed orientation estimation algorithm consists of two stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

Successful conservation of a threatened Maculinea butterfly.

PubMed

Thomas, J A; Simcox, D J; Clarke, R T

2009-07-03

Globally threatened butterflies have prompted research-based approaches to insect conservation. Here, we describe the reversal of the decline of Maculinea arion (Large Blue), a charismatic specialist whose larvae parasitize Myrmica ant societies. M. arion larvae were more specialized than had previously been recognized, being adapted to a single host-ant species that inhabits a narrow niche in grassland. Inconspicuous changes in grazing and vegetation structure caused host ants to be replaced by similar but unsuitable congeners, explaining the extinction of European Maculinea populations. Once this problem was identified, UK ecosystems were perturbed appropriately, validating models predicting the recovery and subsequent dynamics of the butterfly and ants at 78 sites. The successful identification and reversal of the problem provides a paradigm for other insect conservation projects.

Improved packing of protein side chains with parallel ant colonies.

PubMed

Quan, Lijun; Lü, Qiang; Li, Haiou; Xia, Xiaoyan; Wu, Hongjie

2014-01-01

The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

A new improved artificial bee colony algorithm for ship hull form optimization

NASA Astrophysics Data System (ADS)

Huang, Fuxin; Wang, Lijue; Yang, Chi

2016-04-01

The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.

Multi-frame knowledge based text enhancement for mobile phone captured videos

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-02-01

In this study, we explore automated text recognition and enhancement using mobile phone captured videos of store receipts. We propose a method which includes Optical Character Resolution (OCR) enhanced by our proposed Row Based Multiple Frame Integration (RB-MFI), and Knowledge Based Correction (KBC) algorithms. In this method, first, the trained OCR engine is used for recognition; then, the RB-MFI algorithm is applied to the output of the OCR. The RB-MFI algorithm determines and combines the most accurate rows of the text outputs extracted by using OCR from multiple frames of the video. After RB-MFI, KBC algorithm is applied to these rows to correct erroneous characters. Results of the experiments show that the proposed video-based approach which includes the RB-MFI and the KBC algorithm increases the word character recognition rate to 95%, and the character recognition rate to 98%.

Prognostic Model for Resected Squamous Cell Lung Cancer: External Multicenter Validation and Propensity Score Analysis exploring the Impact of Adjuvant and Neoadjuvant Treatment.

PubMed

Pilotto, Sara; Sperduti, Isabella; Leuzzi, Giovanni; Chiappetta, Marco; Mucilli, Felice; Ratto, Giovanni Battista; Lococo, Filippo; Filosso, Pier Lugigi; Spaggiari, Lorenzo; Novello, Silvia; Milella, Michele; Santo, Antonio; Scarpa, Aldo; Infante, Maurizio; Tortora, Giampaolo; Facciolo, Francesco; Bria, Emilio

2018-04-01

We developed one of the first clinicopathological prognostic nomograms for resected squamous cell lung cancer (SQLC). Herein, we validate the model in a larger multicenter cohort and we explore the impact of adjuvant and neoadjuvant treatment (ANT). Patients with resected SQLC from January 2002 to December 2012 in six institutions were eligible. Each patient was assigned a prognostic score based on the clinicopathological factors included in the model (age, T descriptor according to seventh edition of the TNM classification, lymph node status, and grading). Kaplan-Meier analysis for disease-free survival, cancer-specific survival (CSS), and overall survival was performed according to a three-class risk model. Harrell's C-statistics were adopted for model validation. The effect of ANT was adjusted with propensity score. Data on 1375 patients were gathered (median age, 68 years; male sex, 86.8%; T descriptor 1 or 2 versus 3 or 4, 71.7% versus 24.9%; nodes negative versus positive, 53.4% versus 46.6%; and grading of 1 or 2 versus 3, 35.0% versus 41.1%). Data for survival analysis were available for 1097 patients. With a median follow-up of 55 months, patients at low risk had a significantly longer disease-free survival than did patients at intermediate risk (hazard ratio [HR] = 1.67, 95% confidence interval [CI]: 1.40-2.01) and patients at high risk (HR = 2.46, 95% CI: 1.90-3.19); they also had a significantly longer CSS (HR = 2.46, 95% CI: 1.80-3.36 versus HR = 4.30, 95% CI: 2.92-6.33) and overall survival (HR = 1.79, 95% CI: 1.48-2.17 versus HR = 2.33, 95% CI: 1.76-3.07). A trend in favor of ANT was observed for intermediate-risk/high-risk patients, particularly for CSS (p = 0.06 [5-year CSS 72.7% versus 60.8%]). A model based on a combination of easily available clinicopathological factors effectively stratifies patients with resected SQLC into three risk classes. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

The polarization compass dominates over idiothetic cues in path integration of desert ants.

PubMed

Lebhardt, Fleur; Koch, Julja; Ronacher, Bernhard

2012-02-01

Desert ants, Cataglyphis, use the sky's pattern of polarized light as a compass reference for navigation. However, they do not fully exploit the complexity of this pattern, rather - as proposed previously - they assess their walking direction by means of an approximate solution based on a simplified internal template. Approximate rules are error-prone. We therefore asked whether the ants use additional cues to improve the accuracy of directional decisions, and focused on 'idiothetic' cues, i.e. cues based on information from proprioceptors. We trained ants in a channel system that was covered with a polarization filter, providing only a single e-vector direction as a directional 'celestial' cue. Then we observed their homebound runs on a test field, allowing full view of the sky. In crucial experiments, the ants were exposed to a cue conflict, in which sky compass and idiothetic information disagreed, by training them in a straight channel that provided a change in e-vector direction. The results indicated that the polarization information completely dominates over idiothetic cues. Two path segments with different e-vector orientations are combined linearly to a summed home vector. Our data provide additional evidence that Cataglyphis uses a simplified internal template to derive directional information from the sky's polarization pattern.

Analysis of Functional Coupling: Mitochondrial Creatine Kinase and Adenine Nucleotide Translocase

PubMed Central

Vendelin, Marko; Lemba, Maris; Saks, Valdur A.

2004-01-01

The mechanism of functional coupling between mitochondrial creatine kinase (MiCK) and adenine nucleotide translocase (ANT) in isolated heart mitochondria is analyzed. Two alternative mechanisms are studied: 1), dynamic compartmentation of ATP and ADP, which assumes the differences in concentrations of the substrates between intermembrane space and surrounding solution due to some diffusion restriction and 2), direct transfer of the substrates between MiCK and ANT. The mathematical models based on these possible mechanisms were composed and simulation results were compared with the available experimental data. The first model, based on a dynamic compartmentation mechanism, was not sufficient to reproduce the measured values of apparent dissociation constants of MiCK reaction coupled to oxidative phosphorylation. The second model, which assumes the direct transfer of substrates between MiCK and ANT, is shown to be in good agreement with experiments—i.e., the second model reproduced the measured constants and the estimated ADP flux, entering mitochondria after the MiCK reaction. This model is thermodynamically consistent, utilizing the free energy profiles of reactions. The analysis revealed the minimal changes in the free energy profile of the MiCK-ANT interaction required to reproduce the experimental data. A possible free energy profile of the coupled MiCK-ANT system is presented. PMID:15240503

Multirobot Lunar Excavation and ISRU Using Artificial-Neural-Tissue Controllers

NASA Astrophysics Data System (ADS)

Thangavelautham, Jekanthan; Smith, Alexander; Abu El Samid, Nader; Ho, Alexander; Boucher, Dale; Richard, Jim; D'Eleuterio, Gabriele M. T.

2008-01-01

Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to `breed' controllers for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates `machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thangavelautham, Jekanthan; Smith, Alexander; Abu El Samid, Nader

Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to 'breed' controllersmore » for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates 'machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes.« less

Ex ante Implementatietoetsing van Beleid, Een Methodiek Gebaseerd op Synergie Tussen Risicomanagement en Verandermanagement (Ex Ante Test for Policy Implementation - A Method Based Upon Synergy Between Risk Management an Change Management)

DTIC Science & Technology

2006-12-01

ante implementatietoetsing van beleid Een methodiek gebaseerd op synergie tussen risicomnanagemnent en verandermanagemnent Datuni december 2006 Auteur (s...te analyseren. Het de resultaten van de interviews gebruikct bij de theorie van risicomanagement en project Verandermanagernent bij de de ontwikkehing...Opdrachtnummer Hoewel expliciet is gekeken naar voorbeelden van risico’s bij Datum december 2006 Auteur (s) PROGRAMMA PR03ECT drs. R.C.T. de Haas drs

The Legitimation of Novel Technologies: The Case of Nanotechnology

NASA Astrophysics Data System (ADS)

Thyroff, Anastasia E.

Nanotechnology is the control, manipulation, and application of matter on an atomic and molecular level. The technology is complex and confusing to consumers, and its long-term safety and effect on the human body, as well as the environment, are unknown. However, for the past decade, nanotechnology has been used to develop consumer products and food with novel and attractive attributes. Since nanotechnology is still not well known, it is not legitimized; that is, it has not been deemed safe and accepted by society. However, the market for nanotechnology is in the legitimation process. It will take an entire network of key stakeholders playing a specific roles for nanotechnology to legitimize. Specifically, each key stakeholder will align with a certain cultural discourse to frame nanotechnology in a particular way that complements their values. In Essay 1, I follow previous market system dynamic's literature and combine Actor Network Theory (ANT), Foucault's Discourse on Power and Goffman's Frame analysis to theoretically explore what the actor network for nanotechnology looks like. Four dominate frames are identified: 1) Advancement (i.e., government), 2) Management (i.e., industry), 3) Development (i.e., academia/scientists), and 4) Informant (i.e., NGO). Essay 2 empirically explores each actor's perspective on the nanotechnology network through a total of 24 interviews. A hermeneutic approach is used to analyze the 208 page text and themes describing each actor's role from a self and other's perspective are discussed. Additionally, three overarching themes (i.e., contradiction, constance, and cutoff) emerge; these themes describe the degree of similarity in how actors view their role in the nanotechnology network compared to how other actor's view that actor's role. In Essay 3, I bring critical theory into market system's research to better contextualize market formation theories. Specifically, I discuss how critical theory can be used to supplement ANT. I suggest that ANT can be combined with critical theory to better understand the process of translation through exploring conflicts and contradictions among key stakeholders. To show this process, I explore the juxtaposition of economic benefits vs. cultural concerns that has emerged in the nanotechnology marketplace. It is determined that this exploration process can determine why mobilization has not occurred.

Disease in the Society: Infectious Cadavers Result in Collapse of Ant Sub-Colonies.

PubMed

Loreto, Raquel G; Hughes, David P

2016-01-01

Despite the growing number of experimental studies on mechanisms of social immunity in ant societies, little is known about how social behavior relates to disease progression within the nests of ants. In fact, when empirically studying disease in ant societies, it is common to remove dead ants from experiments to confirm infection by the studied parasite. This unfortunately does not allow disease to progress within the nest as it may be assumed would happen under natural conditions. Therefore, the approach taken so far has resulted in a limited knowledge of diseases dynamics within the nest environment. Here we introduced a single infectious cadaver killed by the fungus Beauveria bassiana into small nests of the ant Camponotus castaneus. We then observed the natural progression of the disease by not removing the corpses of the ants that died following the first entry of the disease. Because some behaviors such as social isolation of sick individuals or the removal of cadavers by nestmates are considered social immune functions and thus adaptations at the colony level that reduce disease spread, we also experimentally confined some sub-colonies to one or two chamber nests to prevent the expression of such behaviors. Based on 51 small nests and survival studies in 1,003 ants we found that a single introduced infectious cadaver was able to transmit within the nest, and social immunity did not prevent the collapse of the small sub-colonies here tested. This was true whether ants did or did not have the option to remove the infectious cadaver. Therefore, we found no evidence that the typically studied social immunity behaviors can reduce disease spread in the conditions here tested.

Field suppression of the invasive ant Wasmannia auropunctata (Hymenoptera: Formicidae) in a tropical fruit orchard in Hawaii.

PubMed

Souza, Evann; Follett, Peter A; Price, Don K; Stacy, Elizabeth A

2008-08-01

The little fire ant, Wasmannia auropunctata (Roger) (Hymenoptera: Formicidae), is an invasive ant that forms supercolonies when it successfully invades new areas. W. auropunctata was first reported in Hawaii in 1999, and it has since invaded a variety of agricultural sites, including nurseries, orchards, and pastures. Amdro (hydramethylnon; in bait stations), Esteem (pyriproxyfen; broadcast bait), and Conserve (spinosad; ground spray) were tested for their efficacy against W. auropunctata in a rambutan, Nephelium lappaceum L. and mangosteen, Garcinia mangostana L., orchard by making treatments every 2 wk for 16 wk. Relative estimates of ant numbers in plots was determined by transect sampling using peanut butter-baited sticks. Significant treatment effects were observed on weeks 13-17, with reductions in ant counts occurring in the Amdro and Esteem treatments. During this period, the reduction in ant numbers from pretreatment counts averaged 47.1 and 92.5% in the Amdro and Esteem plots, respectively, whereas ant numbers in the untreated control plots increased by 185.9% compared with pretreatment counts. Conserve did not cause a reduction in ant counts as applied in our experiment. No plots for any of the treatments achieved 100% reduction. Pseudococcidae were counted on branch terminals at 4-wk intervals. The two predominant species, Nipaecoccus nipae (Maskell) and Nipaecoccus viridis (Newstead) were significantly lower in the Amdro and Esteem treatments on week 16 compared with controls. Many W. auropunctata were found nesting in protected sites in the orchard trees, which may have compromised the ground-based control methods. Absolute density estimates from shallow core samples taken from the orchard floor indicated the W. auropunctata supercolony exceeded 244 million ants and 22.7 kg wet weight per ha.

Disease in the Society: Infectious Cadavers Result in Collapse of Ant Sub-Colonies

PubMed Central

Loreto, Raquel G.; Hughes, David P.

2016-01-01

Despite the growing number of experimental studies on mechanisms of social immunity in ant societies, little is known about how social behavior relates to disease progression within the nests of ants. In fact, when empirically studying disease in ant societies, it is common to remove dead ants from experiments to confirm infection by the studied parasite. This unfortunately does not allow disease to progress within the nest as it may be assumed would happen under natural conditions. Therefore, the approach taken so far has resulted in a limited knowledge of diseases dynamics within the nest environment. Here we introduced a single infectious cadaver killed by the fungus Beauveria bassiana into small nests of the ant Camponotus castaneus. We then observed the natural progression of the disease by not removing the corpses of the ants that died following the first entry of the disease. Because some behaviors such as social isolation of sick individuals or the removal of cadavers by nestmates are considered social immune functions and thus adaptations at the colony level that reduce disease spread, we also experimentally confined some sub-colonies to one or two chamber nests to prevent the expression of such behaviors. Based on 51 small nests and survival studies in 1,003 ants we found that a single introduced infectious cadaver was able to transmit within the nest, and social immunity did not prevent the collapse of the small sub-colonies here tested. This was true whether ants did or did not have the option to remove the infectious cadaver. Therefore, we found no evidence that the typically studied social immunity behaviors can reduce disease spread in the conditions here tested. PMID:27529548

Ant Brood Function as Life Preservers during Floods

PubMed Central

Purcell, Jessica; Avril, Amaury; Jaffuel, Geoffrey; Bates, Sarah; Chapuisat, Michel

2014-01-01

Social organisms can surmount many ecological challenges by working collectively. An impressive example of such collective behavior occurs when ants physically link together into floating ‘rafts’ to escape from flooded habitat. However, raft formation may represent a social dilemma, with some positions posing greater individual risks than others. Here, we investigate the position and function of different colony members, and the costs and benefits of this functional geometry in rafts of the floodplain-dwelling ant Formica selysi. By causing groups of ants to raft in the laboratory, we observe that workers are distributed throughout the raft, queens are always in the center, and 100% of brood items are placed on the base. Through a series of experiments, we show that workers and brood are extremely resistant to submersion. Both workers and brood exhibit high survival rates after they have rafted, suggesting that occupying the base of the raft is not as costly as expected. The placement of all brood on the base of one cohesive raft confers several benefits: it preserves colony integrity, takes advantage of brood buoyancy, and increases the proportion of workers that immediately recover after rafting. PMID:24586600

[Ants and aliens. An episode in the history of entomological and sociological construction of knowledge].

PubMed

Werber, Niels

2011-09-01

The frequent use of biological metaphors in descriptions of society is well known and has already been investigated. Even the traces of biological theory in sociology have been explored. In this field of science, studies of social insects play an important role, because ants, bees, and termites have been considered to be genuinely political animals and founders of societies. Like men, social insects exist only in collectives; thus, the entomologist's research directs him from the individual insect, its morphology and taxonomy to the analysis of insect societies. Entomologists like Wheeler or Wilson become sociologists and develop methods to deal with a society whose members are dumb, soulless, without reason, rational choice, or motives. Tools invented to describe the evolution of insect societies have been picked up by sociological founders of systems theory like Parsons or Luhmann, who were busy building a theory of a society, which for heuristic reasons is not composed of men (individuals with souls, motives, consciousness and so on) but rather of communications, media, or codes. My paper treats 1.) the genealogy of this discursive mixture of problems, methods, and focuses on 2.) the rhetorical dimension of this entomological-sociological passage. I will sketch certain 'evident' pictures of society, which function as media of a subliminal crossing of entomological and sociological premises, models, and assumptions. Both can be found in novels like Wilson's Anthill, which this paper analyzes with respect to the concepts of society implied by them, that is, concepts whose blueprints are based on models of an ant society.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Diversification amongst the South American fire ants: how when and why species barriers break down

USDA-ARS?s Scientific Manuscript database

Fire ants (Solenopsis) are an ideal model system for studying speciation and coexistence. Based on preliminary mitochondrial work, they appear to be a relatively recent radiation, and possibly a species swarm (ancient hybridization among young species). We are using a variety of phylogenetic, phylog...

ANTS AS INDICATORS OF EXPOSURE TO ENVIRONMENTAL STRESSORS IN NORTH AMERICAN DESERT GRASSLANDS

EPA Science Inventory

The relative abundance of ant species was measured by pit-fall trapping at 44 sites in southern New Mexico and southeastern Arizona, U.S.A..Sites were selected for study based on documentation of a history of disturbance or protection from disturbance, exposure to varying intens...

Fidelity and Promiscuity in an Ant-Plant Mutualism: A Case Study of Triplaris and Pseudomyrmex

PubMed Central

Sanchez, Adriana

2015-01-01

The association between the myrmecophyte Triplaris and ants of the genus Pseudomyrmex is an often-reported example of mutualism but no molecular studies have examined this association to date. In this study, the interspecific relationships of Triplaris were reconstructed using five molecular markers (two chloroplast and three nuclear), and the relationships of the associated Pseudomyrmex using two molecular regions (one mitochondrial and one nuclear). A data set including all known collections of plant hosts and resident ants was also compiled. The pattern of distribution of both organisms reveals that there are varying degrees of host specificity; most ants show broader host usage (promiscuous) but one species (P. dendroicus) is faithful to a single species of Triplaris. In most ant-plant interactions, host usage is not specific at the species level and preferences may result from geographical or ecological sorting. The specificity of P. dendroicus could be based on chemical recognition of the host they were raised on. PMID:26630384

Refined genetic algorithm -- Economic dispatch example

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheble, G.B.; Brittig, K.

1995-02-01

A genetic-based algorithm is used to solve an economic dispatch (ED) problem. The algorithm utilizes payoff information of perspective solutions to evaluate optimality. Thus, the constraints of classical LaGrangian techniques on unit curves are eliminated. Using an economic dispatch problem as a basis for comparison, several different techniques which enhance program efficiency and accuracy, such as mutation prediction, elitism, interval approximation and penalty factors, are explored. Two unique genetic algorithms are also compared. The results are verified for a sample problem using a classical technique.

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry.

PubMed

Bedggood, Phillip; Metha, Andrew

2010-01-01

Recently many software-based approaches have been suggested for improving the range and accuracy of Hartmann-Shack aberrometry. We compare the performance of four representative algorithms, with a focus on aberrometry for the human eye. Algorithms vary in complexity from the simplistic traditional approach to iterative spline extrapolation based on prior spot measurements. Range is assessed for a variety of aberration types in isolation using computer modeling, and also for complex wavefront shapes using a real adaptive optics system. The effects of common sources of error for ocular wavefront sensing are explored. The results show that the simplest possible iterative algorithm produces comparable range and robustness compared to the more complicated algorithms, while keeping processing time minimal to afford real-time analysis.

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry

NASA Astrophysics Data System (ADS)

Bedggood, Phillip; Metha, Andrew

2010-11-01

Recently many software-based approaches have been suggested for improving the range and accuracy of Hartmann-Shack aberrometry. We compare the performance of four representative algorithms, with a focus on aberrometry for the human eye. Algorithms vary in complexity from the simplistic traditional approach to iterative spline extrapolation based on prior spot measurements. Range is assessed for a variety of aberration types in isolation using computer modeling, and also for complex wavefront shapes using a real adaptive optics system. The effects of common sources of error for ocular wavefront sensing are explored. The results show that the simplest possible iterative algorithm produces comparable range and robustness compared to the more complicated algorithms, while keeping processing time minimal to afford real-time analysis.

How to catch more prey with less effective traps: explaining the evolution of temporarily inactive traps in carnivorous pitcher plants.

PubMed

Bauer, Ulrike; Federle, Walter; Seidel, Hannes; Grafe, T Ulmar; Ioannou, Christos C

2015-02-22

Carnivorous Nepenthes pitcher plants capture arthropods with specialized slippery surfaces. The key trapping surface, the pitcher rim (peristome), is highly slippery when wetted by rain, nectar or condensation, but not when dry. As natural selection should favour adaptations that maximize prey intake, the evolution of temporarily inactive traps seems paradoxical. Here, we show that intermittent trap deactivation promotes 'batch captures' of ants. Prey surveys revealed that N. rafflesiana pitchers sporadically capture large numbers of ants from the same species. Continuous experimental wetting of the peristome increased the number of non-recruiting prey, but decreased the number of captured ants and shifted their trapping mode from batch to individual capture events. Ant recruitment was also lower to continuously wetted pitchers. Our experimental data fit a simple model that predicts that intermittent, wetness-based trap activation should allow safe access for 'scout' ants under dry conditions, thereby promoting recruitment and ultimately higher prey numbers. The peristome trapping mechanism may therefore represent an adaptation for capturing ants. The relatively rare batch capture events may particularly benefit larger plants with many pitchers. This explains why young plants of many Nepenthes species additionally employ wetness-independent, waxy trapping surfaces.

Chemical camouflage--a frog's strategy to co-exist with aggressive ants.

PubMed

Rödel, Mark-Oliver; Brede, Christian; Hirschfeld, Mareike; Schmitt, Thomas; Favreau, Philippe; Stöcklin, Reto; Wunder, Cora; Mebs, Dietrich

2013-01-01

Whereas interspecific associations receive considerable attention in evolutionary, behavioural and ecological literature, the proximate bases for these associations are usually unknown. This in particular applies to associations between vertebrates with invertebrates. The West-African savanna frog Phrynomantis microps lives in the underground nest of ponerine ants (Paltothyreus tarsatus). The ants usually react highly aggressively when disturbed by fiercely stinging, but the frog is not attacked and lives unharmed among the ants. Herein we examined the proximate mechanisms for this unusual association. Experiments with termites and mealworms covered with the skin secretion of the frog revealed that specific chemical compounds seem to prevent the ants from stinging. By HPLC-fractionation of an aqueous solution of the frogs' skin secretion, two peptides of 1,029 and 1,143 Da were isolated and found to inhibit the aggressive behaviour of the ants. By de novo sequencing using tandem mass spectrometry, the amino acid sequence of both peptides consisting of a chain of 9 and 11 residues, respectively, was elucidated. Both peptides were synthesized and tested, and exhibited the same inhibitory properties as the original frog secretions. These novel peptides most likely act as an appeasement allomone and may serve as models for taming insect aggression.

Quantity judgments in the context of risk/reward decision making in striped field mice: first “count,” then hunt

PubMed Central

Panteleeva, Sofia; Reznikova, Zhanna; Vygonyailova, Olga

2013-01-01

We simulated the situation of risky hunting in the striped field mouse Apodemus agrarius in order to examine whether these animals are able to make a choice between small and large quantities of live prey (ants). In the first (preliminary) experiment we investigated to what extent mice were interested in ants as a live prey and how their hunting activity depended on the quantity of these edible but rather aggressive insects. We placed mice one by one into arenas together with ant groups of different quantities, from 10 to 60. Surprisingly, animals, both wild-caught and laboratory-reared, displayed rather skilled predatory attacks: mice killed and ate from 0.37 ± 003 to 4 ± 0.5 ants per minute. However, there was a threshold number of ants in the arenas when rodents expressed signs of discomfort and started to panic, likely because ants bit them. This threshold corresponds to the dynamic density (about 400 individuals per m2 per min) in the vicinity of anthills and ants' routes in natural environment. In the second experiment mice had to choose between different quantities of ants placed in two transparent tunnels. Ants here served both as food items and as a source of danger. As far as we know, this is the first experimental paradigm based on evaluation of quantity judgments in the context of risk/reward decision making where the animals face a trade-off between the hedonistic value of the prey and the danger it presents. We found that when mice have to choose between 5 vs. 15, 5 vs. 30, and 10 vs. 30 ants, they always tend to prefer the smaller quantity, thus displaying the capacity for distinguishing more from less in order to ensure comfortable hunting. The results of this study are ecologically relevant as they reflect situations and challenges faced by free-living small rodents. PMID:23407476

ANTS-anchored Zn-Al-CO{sub 3}-LDH particles as fluorescent probe for sensing of folic acid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Pengfei; Liu, Dan; Liu, Yanhuan

2016-09-15

A novel fluorescent nanosensor for detecting folic acid (FA) in aqueous media has been developed based on 8-aminonaphthalene-1,3,6-trisulfonate (ANTS) anchored to the surface of Zn-Al-CO{sub 3}-layered double hydroxides (LDH) particles. The nanosensor showed high fluorescence intensity and good photostability due to a strong coordination interaction between surface Zn{sup 2+} ions of Zn-Al-CO{sub 3}-LDH and N atoms of ANTS, which were verified by result of X-ray photoelectron spectroscopy (XPS). ANTS-anchored on the surface of Zn-Al-CO{sub 3}-LDH restricted the intra-molecular rotation leading to ANTS-anchored J-type aggregation emission enhancement. ANTS-anchored Zn-Al-CO{sub 3}-LDH particles exhibited highly sensitive and selective response to FA over othermore » common metal ions and saccharides present in biological fluids. The proposed mechanism was that oxygen atoms of -SO{sub 3} groups in ANTS-anchored on the surface of Zn-Al-CO{sub 3}-LDH were easily collided by FA molecules to form potential hydrogen bonds between ANTS-anchored and FA molecules, which could effectively quench the ANTS-anchored fluorescence. Under the simulated physiological conditions (pH of 7.4), the fluorescence quenching was fitted to Stern-Volmer equation with a linear response in the concentration range of 1 μM to 200 μM with a limit of detection of 0.1 μM. The results indicate that ANTS-anchored Zn-Al-CO{sub 3}-LDH particles can afford a very sensitive system for the sensing FA in aqueous solution. - Highlights: • A novel fluorescent nanosensor has been developed. • The sensor exhibited highly sensitive and selective response to FA. • The fluorescence quenching was fitted to Stern–Volmer equation. • The linear response range was 1–200 μM with a limit of detection of 0.1 μM.« less

Seeing through Transparency in Education Reform: Illuminating the "Local"

ERIC Educational Resources Information Center

Koyama, Jill; Kania, Brian

2016-01-01

Utilizing "assemblage," a notion associated with Actor-Network Theory (ANT), we explore what discourses of transparency can, and cannot, accomplish in a network of education reform that includes schools, government agencies, and community organizations. Drawing on data collected between July 2011 and March 2013 in an…