The paper describes the design and implementation of a robot manipulation system on a hardware platform based on a Programmable Logic Controller (PLC) and The Robot Operating System 2 (ROS 2). The controlled robot is ...
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Cycling road racing is a popular sport for people all over the world. Different types of cycling road races require different abilities from the riders. Flexible riding strategies also play an important role in these ...
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It is a widely held view that software engineers should not be "burdened" with the responsibility of making their application components elastic;and that elasticity should be either be implicit and automatic...
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ISBN:
(纸本)9781479919345
It is a widely held view that software engineers should not be "burdened" with the responsibility of making their application components elastic;and that elasticity should be either be implicit and automatic in the programming framework;or that it is the responsibility of the cloud provider's operational staff (DevOps) to make distributed applications written for dedicated clusters elastic and execute them on cloud environments. In this paper, we argue the opposite - we present a case for explicit elasticity, where software engineers are given the flexibility to explicitly engineer elasticity into their distributed applications. We present several scenarios where elasticity retrofitted to applications by DevOps is ineffective, present preliminary empirical evidence that explicit elasticity improves efficiency, and argue for elastic programming languages and frameworks to reduce programmer effort in engineering elastic distributed applications. We also present a bird's eye view of ongoing work on two explicitly elastic programming frameworks - ElasticThrift (based on Apache Thrift [6]) and ElasticJava, an extension of Java with support for explicit elasticity.
Principal Component Analysis (PCA) is one of the famous statistical methods which eliminates the correlation between different data components and consequently decrease the size of data. In classical method covariance...
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ISBN:
(纸本)9781424444564
Principal Component Analysis (PCA) is one of the famous statistical methods which eliminates the correlation between different data components and consequently decrease the size of data. In classical method covariance matrix of input data is used for extracting singular values and vectors. In this paper neural networks are used for extracting principal value components in order to compress image data. First, different principal component analysis neural networks are discussed. Then a nonlinear PCA neural network is used which ends up to better results as shown in simulation results.
This article presents how the genetic algorithm (GA) based stochastic simulation can be used for solving fuzzy goal programming (FGP) model of a chance constrained bilevel programming problem (BLPP). A numerical examp...
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ISBN:
(纸本)9788132222507;9788132222491
This article presents how the genetic algorithm (GA) based stochastic simulation can be used for solving fuzzy goal programming (FGP) model of a chance constrained bilevel programming problem (BLPP). A numerical example is solved to illustrate the proposed approach.
Unmanned aerial vehicles have gained prominence in diverse applications spanning non-military and military domains. Despite their simple mechanical structure, quadrotor UAVs are characterized as nonlinear and under-ac...
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ISBN:
(纸本)9798350349740;9798350349757
Unmanned aerial vehicles have gained prominence in diverse applications spanning non-military and military domains. Despite their simple mechanical structure, quadrotor UAVs are characterized as nonlinear and under-actuated systems, which has led to a requirement for controllers that are able to overcome these challenges. Intelligent control methods like fuzzy logic have proven to be practical for controlling nonlinear systems. This paper proposes the development of a Type-2 fuzzy controller for addressing the trajectory tracking challenge of a quadrotor. The membership functions of this controller are optimized using the particle swarm optimization (PSO) algorithm based on the uncertainties values. To assess the effectiveness of the proposed controller, a comparative analysis with a type-1 fuzzy controller and a standard PID controller is conducted.
Developing IoT, Data Computing and Cloud Computing software requires different programming skills and different programming languages. This cause a problem for many companies and researchers that need to hires many pr...
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ISBN:
(纸本)9781450347747
Developing IoT, Data Computing and Cloud Computing software requires different programming skills and different programming languages. This cause a problem for many companies and researchers that need to hires many programmers to develop a complete solution. The problem is related directly to the financial cost and the development time which are very important factors to many research projects. In this paper we present and propose the PWCT visual programming tool for developing IoT, Data Computing and Cloud Computing applications and Systems without writing textual code directly. Using PWCT increase productivity and provide researchers with one visual programming tool to develop different solutions.
programming paradigms for networks of symmetric multiprocessor (SMP) workstation (2(nd) generation of clusters) are discussed and a new paradigm is introduced. The SMP cluster environments are explored in regard to th...
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ISBN:
(纸本)3540221166
programming paradigms for networks of symmetric multiprocessor (SMP) workstation (2(nd) generation of clusters) are discussed and a new paradigm is introduced. The SMP cluster environments are explored in regard to their advantages and drawbacks with a special focus on memory architectures and communication. The new programming paradigm provides a solution to write efficient parallel applications for the 2(nd) generation of clusters. The paradigm aims at improving the overlap of computation and communication and the locality of communication operations. The preliminary results with large message sizes indicate improvements in excess of 30% over traditional MPI implementations.
Robot prosthesis has 6 degrees of freedom, including outward swinging and forward and backward swinging, which are droved by servo motors. In order to reduce the servo motors' driving torque, a gas spring was adde...
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ISBN:
(纸本)9783037855010
Robot prosthesis has 6 degrees of freedom, including outward swinging and forward and backward swinging, which are droved by servo motors. In order to reduce the servo motors' driving torque, a gas spring was added on shoulder to balance the gravity torque. In this paper, the difference between gravity torque and balanced torque was created and taken as optimized object firstly, and then a mathematical model was created and Matlab program on the base of nonlinearprogramming genetic algorithm were made for obtaining the optimum, lastly the simulation model and optimizing process diagrams were outputted.
Sliding mode control is a typical nonlinear control strategy which was easy realized and with strong robustness, in this paper, a neuro sliding mode controller was designed with RBF neural networks and the stability o...
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ISBN:
(纸本)9780769539829
Sliding mode control is a typical nonlinear control strategy which was easy realized and with strong robustness, in this paper, a neuro sliding mode controller was designed with RBF neural networks and the stability of the proposed control scheme is proved by Lyapnouv theorem. For the chattering of sliding mode control are often derive from switching gain, the gain was adjusted with neural networks with RBF networks' output, the algorithm with fixed gain and adaptive gain are all proposed, also the control scheme is applied to a nonlinear system, simulation studies shows the methods is effective and can applied into nonlinear control system.
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