A survey of symbiotic organisms search algorithms and applications

Nature-inspired algorithms take inspiration from living things and imitate their behaviours to accomplish robust systems in engineering and computer science discipline. Symbiotic organisms search (SOS) algorithm is a recent metaheuristic algorithm inspired by symbiotic interaction between organisms in an ecosystem. Organisms develop symbiotic relationships such as mutualism, commensalism, and parasitism for their survival in ecosystem. SOS was introduced to solve continuous benchmark and engineering problems. The SOS has been shown to be robust and has faster convergence speed when compared with genetic algorithm, particle swarm optimization, differential evolution, and artificial bee colony which are the traditional metaheuristic algorithms. The interests of researchers in using SOS for handling optimization problems are increasing day by day, due to its successful application in solving optimization problems in science and engineering fields. Therefore, this paper presents a comprehensive survey of SOS advances and its applications, and this will be of benefit to the researchers engaged in the study of SOS algorithm.

     

View planning in robot active vision: A survey of systems,algorithms, and applications

Computational Visual Media - Rapid development of artificial intelligence motivates researchers to expand the capabilities of intelligent and autonomous robots. In many robotic applications, robots...     

On consensus algorithms design for double integrator dynamics

This paper considers the consensus problem of double integrator multi-agent systems where: (i) each agent is subject to input saturations, and (ii) the velocity (second state) of each agent is not available for feedback. We present new consensus algorithms that handle simultaneously the above mentioned situations. Sufficient conditions are derived such that consensus algorithms developed for first- and second-order multi-agent systems in ideal situations can be used to account for input saturations and remove the requirement of velocity measurements. To illustrate the effectiveness of the proposed approach, we propose solutions to two different second-order consensus problems in the case where the input is saturated and the velocity states are not available for feedback and simulation results are provided in each case.     

Graphlet decomposition: framework,algorithms, and applications

From social science to biology, numerous applications often rely on graphlets for intuitive and meaningful characterization of networks. While graphlets have witnessed a tremendous success and impact in a variety of domains, there has yet to be a fast and efficient framework for computing the frequencies of these subgraph patterns. However, existing methods are not scalable to large networks with billions of nodes and edges. In this paper, we propose a fast, efficient, and parallel framework as well as a family of algorithms for counting k-node graphlets. The proposed framework leverages a number of theoretical combinatorial arguments that allow us to obtain significant improvement on the scalability of graphlet counting. For each edge, we count a few graphlets and obtain the exact counts of others in constant time using the combinatorial arguments. On a large collection of \(300+\) networks from a variety of domains, our graphlet counting strategies are on average \(460{\times }\) faster than existing methods. This brings new opportunities to investigate the use of graphlets on much larger networks and newer applications as we show in the experiments. To the best of our knowledge, this paper provides the largest graphlet computations to date.     

Toeplitz matrices: Structures,algorithms and applications

This volume contains papers presented at the workshop “Toeplitz Matrices: Structures, Algorithms and Applications”. The workshop was held in Cortona, Italy, from 9 through 12 September 1996.     

A survey on Blockchain mechanisms (BCM) based on internet of things (IoT) applications

Multimedia Tools and Applications - The Internet of Things (IoT), fast-growing smart equipment and high-speed networks, has become generally embraced and popular. Most IoT devices are nevertheless...     

A survey of shadow algorithms

The various types of shadows are characterized. Most existing shadow algorithms are described, and their complexities, advantages, and shortcomings are discussed. Hard shadows, soft shadows, shadows of transparent objects, and shadows for complex modeling primitives are considered. For each type, shadow algorithms within various rendering techniques are examined. The aim is to provide readers with enough background and insight on the various methods to allow them to choose the algorithm best suited to their needs and to help identify the areas that need more research and point to possible solutions     

Some applications of randomized algorithms for control system design

In this paper a few “difficult” problems related to simultaneous stabilization of three plants (equivalent to a certain problem related to unit interpolation in H_∞) have been addressed through the framework of randomized algorithms. These problems which were proposed by Blondel (Simultaneous Stabilization of Linear Systems, Springer, Berlin, 1994) and Blondel and Gevers (Math. Control Signals Systems 6 (1994) 135) concern the existence of a controller.     

An median graphs: properties, algorithms, and applications

In object prototype learning and similar tasks, median computation is an important technique for capturing the essential information of a given set of patterns. We extend the median concept to the domain of graphs. In terms of graph distance, we introduce the novel concepts of set median and generalized median of a set of graphs. We study properties of both types of median graphs. For the more complex task of computing generalized median graphs, a genetic search algorithm is developed. Experiments conducted on randomly generated graphs demonstrate the advantage of generalized median graphs compared to set median graphs and the ability of our genetic algorithm to find approximate generalized median graphs in reasonable time. Application examples with both synthetic and nonsynthetic data are shown to illustrate the practical usefulness of the concept of median graphs     

Curve-skeleton properties, applications, and algorithms

Curve-skeletons are thinned 1D representations of 3D objects useful for many visualization tasks including virtual navigation, reduced-model formulation, visualization improvement, animation, etc. There are many algorithms in the literature describing extraction methodologies for different applications; however, it is unclear how general and robust they are. In this paper, we provide an overview of many curve-skeleton applications and compile a set of desired properties of such representations. We also give a taxonomy of methods and analyze the advantages and drawbacks of each class of algorithms     

A survey of cellular automata: types,dynamics, non-uniformity and applications

Cellular automata (CAs) are dynamical systems which exhibit complex global behavior from simple local interaction and computation. Since the inception of cellular automaton (CA) by von Neumann in 1950s, it has attracted the attention of several researchers over various backgrounds and fields for modeling different physical, natural as well as real-life phenomena. Classically, CAs are uniform. However, non-uniformity has also been introduced in update pattern, lattice structure, neighborhood dependency and local rule. In this survey, we tour to the various types of CAs introduced till date, the different characterization tools, the global behavior of CAs, like universality, reversibility, dynamics etc. Special attention is given to non-uniformity in CAs and especially to non-uniform elementary CAs, which have been very useful in solving several real-life problems.

     

A survey: algorithms simulating bee swarm intelligence

Swarm intelligence is an emerging area in the field of optimization and researchers have developed various algorithms by modeling the behaviors of different swarm of animals and insects such as ants, termites, bees, birds, fishes. In 1990s, Ant Colony Optimization based on ant swarm and Particle Swarm Optimization based on bird flocks and fish schools have been introduced and they have been applied to solve optimization problems in various areas within a time of two decade. However, the intelligent behaviors of bee swarm have inspired the researchers especially during the last decade to develop new algorithms. This work presents a survey of the algorithms described based on the intelligence in bee swarms and their applications.     

The time dimension: A theory towards the evolution, classification, characterization and design of computational algorithms for transient/ dynamic applications

Summary Via new perspectives, for the time dimension, the present exposition overviews new and recent advances describing a standardized formal theory towards the evolution, classification, characterization and generic design of time discretized operators for transient/dynamic applications. Of fundamental importance in the present exposition are the developments encompassing the evolution of time discretized operators leading to the theoretical design of computational algorithms and their subsequent classification and characterization. And, the overall developments are new and significantly different from the way traditional modal type and a wide variety of step-by-step time marching approaches which we are mostly familiar with have been developed and described in the research literature and in standard text books over the years. The theoretical ideas and basis towards the evolution of a generalized methodology and formulations emanate under the umbrella and framework and are explained via a generalized time weighted philosophy encompassing the semi-discretized equations pertinent to transient/dynamic systems. It is herein hypothesized that integral operators and the associated representations and a wide variety of the so-called integration operators pertain to and emanate from the same family, with the burden which is being carried by a virtual field or weighted time field specifically introduced for the time discretization is strictly enacted in a mathematically consistent manner so as to first permit obtaining the adjoint operator of the original semi-discretized equation system. Subsequently, the selection or burden carried by the virtual or weighted time fields originally introduced to facilitate the time discretization process determines the formal development and outcome of “exact integral operators”, “approximate integral operators”, including providing avenues leading to the design of new computational algorithms which have not been exploited and/or explored to-date and the recovery of most of the existing algorithms, and also bridging the relationships systematically leading to the evolution of a wide variety of “integration operators”. Thus, the overall developments not only serve as a prelude towards the formal developments for “exact integral operators”, but also demonstrate that the resulting “approximate integral operators” and a wide variety of “new and existing integration operators and known methods” are simply subsets of the generalizations of a standardizedW _p -Family, and emanate from the principles presented herein. The developments first leading to integral operators in time, and the resulting consequences then systematically leading to not only providing new avenues but additionally also explaining a wide variety of generalized integration operators in time of which single-step time integration operators and various widely recognized algorithms which we are familiar are simply subsets, the associated multi-step time integration operators, and a class of finite element in time integration operators, and their relationships are particularly addressed. The theoretical design developments encompass and explain a variety of time discretized operators, the recovery of various original methods of algorithmic development, and the development of new computational algorithms which have not been exploited and/or explored to-date, and furthermore, permit time discretized operators to be uniquely classified and characterized by algorithmic markers. The resulting and so-called discrete numerically assigned [DNA] algorithmic markers not only serve as a prelude towards providing a standardized formal theory of development of time discretized operators and forum for selecting and identifying time discretized operators, but also permit lucid communication when referring to various time discretized operators. That which constitutes characterization of time discretized operators are the so-called DNA algorithmic markers which essentially comprise of both: (i) the weighted time fields introduced for enacting the time discretization process, and (ii) the corresponding conditions (if any) these weighted time fields impose (dictate) upon the approximations for the dependent field variables and updates in the theoretical development of time discretized operators. As such, recent advances encompassing the theoretical design and development of computational algorithms for transient/dynamic analysis of time dependent phenomenon encountered in engineering, mathematical and physical sciences are overviewed.     

Distance-based outliers: algorithms and applications

This paper deals with finding outliers (exceptions) in large, multidimensional datasets. The identification of outliers can lead to the discovery of truly unexpected knowledge in areas such as electronic commerce, credit card fraud, and even the analysis of performance statistics of professional athletes. Existing methods that we have seen for finding outliers can only deal efficiently with two dimensions/attributes of a dataset. In this paper, we study the notion of DB (distance-based) outliers. Specifically, we show that (i) outlier detection can be done efficiently for large datasets, and for k-dimensional datasets with large values of k (e.g., ); and (ii), outlier detection is a meaningful and important knowledge discovery task. First, we present two simple algorithms, both having a complexity of , k being the dimensionality and N being the number of objects in the dataset. These algorithms readily support datasets with many more than two attributes. Second, we present an optimized cell-based algorithm that has a complexity that is linear with respect to N, but exponential with respect to k. We provide experimental results indicating that this algorithm significantly outperforms the two simple algorithms for . Third, for datasets that are mainly disk-resident, we present another version of the cell-based algorithm that guarantees at most three passes over a dataset. Again, experimental results show that this algorithm is by far the best for . Finally, we discuss our work on three real-life applications, including one on spatio-temporal data (e.g., a video surveillance application), in order to confirm the relevance and broad applicability of DB outliers. Received February 15, 1999 / Accepted August 1, 1999     

遗传算法在结构优化中的应用

采用遗传算法求解桁架结构优化设计问题,建立了平面桁架结构优化的数学模型,应用改进的自适应遗传算法对其进行求解。为了加快遗传算法进化过程,本文采用精英选择与轮盘赌选择相结合的策略,鲁棒性更好,收敛速度更快,拥有较强的寻优能力。算例表明,该遗传算法可用于桁架结构的优化设计,优化速度快,效率高,优化结果更加可靠。     

The image foresting transform: theory, algorithms, and applications

The image foresting transform (IFT) is a graph-based approach to the design of image processing operators based on connectivity. It naturally leads to correct and efficient implementations and to a better understanding of how different operators relate to each other. We give here a precise definition of the IFT, and a procedure to compute it-a generalization of Dijkstra's algorithm-with a proof of correctness. We also discuss implementation issues and illustrate the use of the IFT in a few applications.     

Proxy cache algorithms: design, implementation, and performance

Caching at proxy servers is one of the ways to reduce the response time perceived by World Wide Web users. Cache replacement algorithms play a central role in the response time reduction by selecting a subset of documents for caching, so that a given performance metric is maximized. At the same time, the cache must take extra steps to guarantee some form of consistency of the cached documents. Cache consistency algorithms enforce appropriate guarantees about the staleness of the cached documents. We describe a unified cache maintenance algorithm, LNC-R-WS-U, which integrates both cache replacement and consistency algorithms. The LNC-R-WS-U algorithm evicts documents from the cache based on the delay to fetch each document into the cache. Consequently, the documents that took a long time to fetch are preferentially kept in the cache. The LNC-R-W3-U algorithm also considers in the eviction consideration the validation rate of each document, as provided by the cache consistency component of LNC-R-WS-U. Consequently, documents that are infrequently updated and thus seldom require validations are preferentially retained in the cache. We describe the implementation of LNC-R-W3-U and its integration with the Apache 1.2.6 code base. Finally, we present a trace-driven experimental study of LNC-R-W3-U performance and its comparison with other previously published algorithms for cache maintenance