Fast-RRT: A RRT-Based Optimal Path Finding Method

As a sampling-based pathfinding algorithm, Rapidly Exploring Random Trees (RRT) has been widely used in motion planning problems due to the ability to find a feasible path quickly. However, the RRT algorithm still has several shortcomings, such as the large variance in the search time, poor performance in narrow channel scenarios, and being far from the optimal path. In this paper, we propose a new RRT-based path find algorithm, Fast-RRT, to find a near-optimal path quickly. The Fast-RRT algorithm consists of two modules, including Improved RRT and Fast-Optimal. The former is aims to quickly and stably find an initial path, and the latter is to merge multiple initial paths to obtain a near-optimal path. Compared with the RRT algorithm, Fast-RRT shows the following improvements: (1) A Fast-Sampling strategy that only samples in the unreached space of the random tree was introduced to improve the search speed and algorithm stability; (2) A Random Steering strategy expansion strategy was proposed to solve the problem of poor performance in narrow channel scenarios; (3) By fusion and adjustment of paths, a near-optimal path can be faster found by Fast-RRT, 20 times faster than the RRT* algorithm. Owing to these merits, our proposed Fast-RRT outperforms RRT and RRT* in both speed and stability during experiments.

The Modification of pBFT Algorithm to Increase Network Operations Efficiency in Private Blockchains

The use of blockchain technology is becoming more widespread. Governments have expanded their use of the technology from online polls to business management of smaller local governments while private institutions have increased their services from financial to medical services management. This paper presents the modified pBFT blockchain consensus algorithm for a more efficient data management method in cases of applying blockchains in authorized nodes such as governmental agencies. The network communication cost was minimized while the consensus accuracy was maximized by applying a method of simplifying the request management process and electing the reliability-based consensus node during the pBFT consensus algorithm process. By applying the modified pBFT consensus algorithm, stability and speed of the consensus and verification process among various organizations can be guaranteed as well as application in efficient management and value creation of data.

CORRECT DETERMINATION OF INTEGRAL CONDUCTIVITY IN SOLVING INCORRECT INVERSE PROBLEMS OF ELECTROMAGNEIC LOGGING

The paper suggests and investigates a problem statement of well-logging inverse problem that is based on the integral conductivity parameter to describe a geoelectric section. Approach was introduced for a layered cylindrical model with radially heterogeneous continuous distribution of electric properties that parametrize the problem with a function of total longitudinal conductivity. The results of hydrodynamic modeling for oil/fresh water- and brine-based drilling muds were used to study multiple propagation resistivity tool signal equivalency for two classes of models with continuous and piece-wise constant conductivity distribution. Physically based algorithm enabling one to convert one model class to the other, preserving the signal equivalency was proposed. It was demonstrated that the radial models with different radial conductivity distribution and similar integral conductivity curves are equivalent. This fact lays a rationale of using the integral conductivity parameters along with conductivity while inversion. The integral conductivity parameter can be used to build the functionals, whose minimization improves algorithm stability and enables determining functional parameters in hydrodynamic filtration models.

A Hybridization of Dragonfly Algorithm Optimization and Angle Modulation Mechanism for 0-1 Knapsack Problems

The dragonfly algorithm (DA) is a new intelligent algorithm based on the theory of dragonfly foraging and evading predators. DA exhibits excellent performance in solving multimodal continuous functions and engineering problems. To make this algorithm work in the binary space, this paper introduces an angle modulation mechanism on DA (called AMDA) to generate bit strings, that is, to give alternative solutions to binary problems, and uses DA to optimize the coefficients of the trigonometric function. Further, to improve the algorithm stability and convergence speed, an improved AMDA, called IAMDA, is proposed by adding one more coefficient to adjust the vertical displacement of the cosine part of the original generating function. To test the performance of IAMDA and AMDA, 12 zero-one knapsack problems are considered along with 13 classic benchmark functions. Experimental results prove that IAMDA has a superior convergence speed and solution quality as compared to other algorithms.

An Improved Multisensor Self-Adaptive Weighted Fusion Algorithm Based on Discrete Kalman Filtering

When the multisensor self-adaptive weighted fusion algorithm fuses the data sources that were severely interfered by noise, its fusion precision, data smoothness, and algorithm stability will be reduced. To overcome this drawback, the idea was proposed with respect to an improved algorithm which optimized acquisition of fusion data sources with discrete Kalman filtering technique, thus reducing the negative impact on the fusion performance from noise. To verify the effectiveness of the improved algorithm, this paper simulated the fusion process of soil moisture data with fusion samples. The result proved that, under the same circumstance, the improved algorithm has a stronger restrain ability to noise and a better performance in fusion precision, data smoothness, and algorithm stability compared with the general algorithm.

Investigating Clarinet Articulation Using a Physical Model and an Artificial Blowing Machine

A time-domain physical model is presented that is capable of simulating a variety of articulation techniques in single-reed woodwind instruments and suitable for real-time sound synthesis. Due to the nonlinear nature of the excitation mechanism, an energy-based approach is adopted for the construction of the numerical scheme in order to ensure algorithm stability. To validate the model, measurements are carried out using an artificial blowing machine. The construction of the machine, including a sensor-equipped reed and mouthpiece as well as an automated artificial tongue and lip, is described in detail. By adjusting the motion of the tongue, the blowing machine can generate audio signals corresponding to portato and staccato articulation. These signals are resynthesised following an inverse modelling approach based on the presented physical model, during which model parameters are estimated. All estimated parameters lie in a physically feasible range and may be used for sound synthesis and sound analysis applications.