Swarm robotics is a branch of robotics that deals with numerous, semi-autonomous robots to accomplish a task. A robotic swarm of unmanned drones can be configured to work as a collective, in order to carry out Search ...
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ISBN:
(数字)9781665478694
ISBN:
(纸本)9781665478700
Swarm robotics is a branch of robotics that deals with numerous, semi-autonomous robots to accomplish a task. A robotic swarm of unmanned drones can be configured to work as a collective, in order to carry out Search and Rescue (SAR), localization and mapping, in an efficient and cost-effective manner. Proper simulation and modelling of swarm robotics are highly essential, as it enables liability-free development and testing of a large-scale multi-agent system. The intelligence of semiautonomous agents within a swarm can be driven by nature-inspired algorithms such as Stigmergy, Flocking, and Differential Evolution. This paper serves to highlight the development of a modern multi-agent simulation platform designed to simulate a swarm of robots assigned with a task, in a procedurally generated environment, alongside a swarm system architecture where nature-inspired algorithms drive the intelligence of each agent.
software effort estimation is a complicated task being carried out by software developers as very little information is available to them in the early phases of software development. The information collected about va...
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ISBN:
(纸本)9781509006700
software effort estimation is a complicated task being carried out by software developers as very little information is available to them in the early phases of software development. The information collected about various attributes of software needs to be subjective, which otherwise can lead to uncertainty. Inaccurate software effort estimation can be disastrous as both underestimation and overestimation may result in schedule overruns and incorrect estimation of budget. This paper focuses on the comparative study of various non-algorithmic techniques used for estimating the software effort by empirical evaluation of five different evolutionary learning algorithms. The accuracy of these algorithms is found out and the behavior of these algorithms is analyzed with respect to the size and the type of data. All the five techniques are applied on three different datasets and various paramenters such as MMRE, PRED(25), PRED(50), PRED(75) are calculated. The proposed results are compared to other machine learning methods like SVR, ANFIS etc. The results show that evolutionary learning algorithms give more accurate results than machine learning algorithms.
Steganography as the art of concealing messages to other object has been widely used in term of information security. The process of Steganography allows the hidden messages for not being apparent to an observer. Furt...
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Steganography as the art of concealing messages to other object has been widely used in term of information security. The process of Steganography allows the hidden messages for not being apparent to an observer. Furthermore, there is another way that is commonly used to improve the security of the information, which is usually called Cryptography. Cryptography defines the art and science of transforming data into a sequence of bits that appears as random and meaningless for the observer. Most of the time, people use only one technique either Steganoraphy or Cryptography to secure the important information. However, the combination of Cryptography and Steganography that is proposed can be applied for enhancing the security of hiding information. The proposed concept also can provide an easiness of exchanging important messages secretly between a receiver and a sender with multimedia files as carriers of the messages.
Two algorithms are described for electron microscopy tasks: (1) 3-D reconstruction of an infectious bacteriophage, including the tail, based on a set of single-particle cryo electron microscopy images of identical pha...
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ISBN:
(纸本)9781424439317
Two algorithms are described for electron microscopy tasks: (1) 3-D reconstruction of an infectious bacteriophage, including the tail, based on a set of single-particle cryo electron microscopy images of identical phage particles with one image per particle and (2) restoration, resolution enhancement, and classification of spherical viruses in a cell based on a tomographic reconstruction of the entire cell. While different tasks, the statistical algorithms, which are maximum likelihood estimators, have extensive commonality. In order to provide solutions for such tasks in a timely fashion, a software toolkit has been created, based on the commonality, for writing parallel software systems to solve these problems.
Summary form only given. We present a model that comprehensively addresses the goals of partitioning an application software mesh into clusters of modules and assigning (or mapping) the clusters onto the most appropri...
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Summary form only given. We present a model that comprehensively addresses the goals of partitioning an application software mesh into clusters of modules and assigning (or mapping) the clusters onto the most appropriate processors in the computational grid. Our approach to solving this challenging combinatorial problem is based on a computational model known as a cascaded Boltzmann machine, which advantageously blends the principles of neural computing and simulated annealing to achieve high quality partitions in a practical amount of execution time. We develop implementations of the algorithms, and focus on the study and refinement of the operational parameters that determine the performance of the Boltzmann algorithms. Through computational experimentation and empirical observations, we are able to characterize the speed and effectiveness of this partitioning and mapping process. We also note that the partitioning and mapping algorithm itself can be implemented as a parallel computation.
Summary form only given, as follows. We study the development of integrated fault-tolerant scheduling algorithms. The proposed algorithms ensure ultra-reliable execution of tasks where both hardware and software failu...
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Summary form only given, as follows. We study the development of integrated fault-tolerant scheduling algorithms. The proposed algorithms ensure ultra-reliable execution of tasks where both hardware and software failures are considered, and system performance improvement. Also, the proposed algorithms have the capability for on-line system-level fault diagnosis.
Cryptol is a programming language designed for specifying cryptographic algorithms. Despite its high-level modeling nature, Cryptol programs are fully executable. Further, a large subset of Cryptol can be automaticall...
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Cryptol is a programming language designed for specifying cryptographic algorithms. Despite its high-level modeling nature, Cryptol programs are fully executable. Further, a large subset of Cryptol can be automatically synthesized to hardware. To meet the inherent high-assurance requirements of cryptographic systems, Cryptol comes with a suite of formal-methods based tools that enable users to perform various program verification tasks. In this paper, we provide an overview of Cryptol and its verification toolset, especially focusing on the co-verification of third-party VHDL implementations against highlevel Cryptol specifications. As a case study, we demonstrate the technique on two hand-written VHDL implementations of the Skein hash algorithm.
The purpose of this paper is to give an overview of recent developments in algorithms and software for linear matrix inequality (LMI) problems. We review the definition and some basic properties of the semidefinite pr...
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The purpose of this paper is to give an overview of recent developments in algorithms and software for linear matrix inequality (LMI) problems. We review the definition and some basic properties of the semidefinite programming (SDP) problem, and describe recent developments in interior point algorithms and available software. We conclude with some extensions of the SDP.
There are many large system problems that are hard to model exactly or in a computationally tractable fashion. Examples include the mapping of human DNA, speech recognition, and automated learning in computer chess. T...
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There are many large system problems that are hard to model exactly or in a computationally tractable fashion. Examples include the mapping of human DNA, speech recognition, and automated learning in computer chess. Traditional artificial intelligence solution techniques for such problems rely on a combination of custom encoding of expert knowledge and heuristic search. They take much time to hand craft and then often are unable to take advantage of faster computers as they become available. In this context, the authors explore the advantage of using statistical search techniques in which the knowledge is encoded in some form of statistical model whose parameters are automatically adjusted or trained with domain data. The benefits are faster development times, greater solution accuracy (compared to hand crafted solutions) and the ability to allow the problem size and desired solution accuracy to be scaled up with computational resources. They apply this approach to certain critical computational problems in mapping the human genome. They use a Bayesian model to provide the best solution accuracy as a function of the number of parameters. Heuristic search techniques derived from artificial intelligence are used to search the model space in an efficient manner in the average case.
Iterative decoding has emerged as one of the most promising techniques for improving receivers performance. This paper is focused on exploring the feasibility of software implementation of iterative decoding algorithm...
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Iterative decoding has emerged as one of the most promising techniques for improving receivers performance. This paper is focused on exploring the feasibility of software implementation of iterative decoding algorithms for the 2nd and 3rd generations of the cellular communications standards. Two examples for iterative decoding algorithms are described: turbo decoding for the 3G cellular standards and turbo equalization for a GSM receiver. The principles described can be used to efficiently construct and implement other iterative decoding algorithms.
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