Due to the importance of the signature vector in studying the reliability of networks, some methods have been proposed by researchers to obtain the signature. The notion of signature is used when at most one link may ...
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Due to the importance of the signature vector in studying the reliability of networks, some methods have been proposed by researchers to obtain the signature. The notion of signature is used when at most one link may fail at each time instant. It is more realistic to consider the case where none of the components, one component, or more than one component of the network may be destroyed at each time. Motivated by this, the concept of t-signature has been recently defined to get the reliability of such a network. The t-signature is a probability vector and depends only on the network structure. In this article, we propose an algorithm to compute the t-signature. The performance of the proposed algorithm is evaluated for some networks.
This paper introduces a novel technique for optimal distribution system (DS) planning with distributed generation (DG) systems. It is being done to see how active and reactive power injections affect the system's ...
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This paper introduces a novel technique for optimal distribution system (DS) planning with distributed generation (DG) systems. It is being done to see how active and reactive power injections affect the system's voltage profile and energy losses. DG penetration in the power systems is one approach that has several advantages such as peak savings, loss lessening, voltage profile amelioration. It also intends to increase system reliability, stability, and security. The main goal of optimal distributed generation (ODG) is a guarantee to achieve the benefits mentioned previously to increase the overall system efficiency. For extremely vast and complicated systems, analytical approaches are not suitable and insufficient. Therefore, several meta-heuristic techniques are favored to obtain better performance from were convergence and accuracy for large systems. In this paper, an Improved Wild Horse Optimization algorithm (IWHO) is proposed as a novel metaheuristic method for solving optimization issues in electrical power systems. IWHO is devised with inspirations from the social life behavior of wild horses. The suggested method is based on the horse's decency. To assess the efficacy of the IWHO, it is implemented on the 23 benchmark functions Reliability amelioration is the most things superb as a result of DGs incorporation. Thus, in this research, a customer-side reliability appraisal in the DS that having a DG unit was carried out by a Monte Carlo Simulation (MCS) approach to construct an artificial history for each ingredient across simulation duration. For load flow calculations, the backward Forward Sweep (bfs) technique has been employed as a simulation tool to assess the network performance considering the power handling restrictions. The proposed IWHO method has been measured on IEEE 33 69 and 119 buses to ascertain the network performing in the presence of the optimal DG and the potential benefits of the suggested technique for enhancing the tools used by opera
With the increasing maturity of automated guided vehicles(AGV)technology and the widespread application of flexible manufacturing systems,enhancing the efficiency of AGVs in complex environments has become *** paper a...
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With the increasing maturity of automated guided vehicles(AGV)technology and the widespread application of flexible manufacturing systems,enhancing the efficiency of AGVs in complex environments has become *** paper analyzes the challenges of path planning and scheduling in multi-AGV systems,introduces a map-based path search algorithm,and proposes the bfs algorithm for shortest path *** optimization using the breadth-first search(bfs)algorithm,efficient scheduling of multiple AGVs in complex environments is *** addition,this paper validated the effectiveness of the proposed method in a production workshop *** experimental results show that the bfs algorithm can quickly search for the shortest path,reduce the running time of AGVs,and significantly improve the performance of multi-AGV scheduling systems.
Tensor network and tensor computation are widely applied in scientific and engineering domains like quantum physics, electronic design automation, and machine learning. As one of the most fundamental operations for te...
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Tensor network and tensor computation are widely applied in scientific and engineering domains like quantum physics, electronic design automation, and machine learning. As one of the most fundamental operations for tensor networks, a tensor contraction eliminates the sharing orders among tensors and produces a compact sub-network. Different contraction sequence usually yields distinct storage and compute costs, and searching the optimal sequence is known as a hard problem. Prior work have designed heuristic and fast algorithms to solve this problem, however, several issues still remain unsolved. For example, the data format and data structure are not efficient, the constraints during modeling are impractical, the search of the optimal solution might fail, and the search cost is very high. In this paper, we first introduce a log(k) order representation and design an adjacency matrix-based data structure to efficiently accelerate the search of the optimal contraction sequence. Then, we propose an outer product pruning method with acceptable overhead to reduce the search space. Finally, we use a multithread optimization in our implementation to further improve the execution performance. We also present indepth analysis of factors that influence the search time. This work provides a full-stack solution for optimal contraction sequence search from both high-level data structure and search algorithm to low-level execution parallelism, and it will benefit a broad range of tensor-related applications.
Path planning algorithms are crucial components in the process of smart parking. At present, there are many path planning algorithms designed for smart parking. A well-designed path planning algorithm has a significan...
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Path planning algorithms are crucial components in the process of smart parking. At present, there are many path planning algorithms designed for smart parking. A well-designed path planning algorithm has a significant impact on the efficiency of smart parking. Firstly, this paper comprehensively describes the principles and steps of four types of path planning algorithms: the Dijkstra algorithm (including its optimized derivatives), the A* algorithm (including its optimized derivatives), the RRT (Rapidly exploring Random Trees) algorithm (including its optimized derivatives), and the bfs (Breadth First Search) algorithm. Secondly, the Dijkstra algorithm, the A* algorithm, the bfs algorithm, and the Dynamic Weighted A* algorithm were utilized to plan the paths required for the process of smart parking. During the analysis, it was found that the Dijkstra algorithm had the drawbacks of planning circuitous paths and taking too much time in the path planning for smart parking. Although the traditional A* algorithm based on the Dijkstra algorithm had greatly reduced the planning time, the effect of path planning was still unsatisfactory. The bfs (Breadth First Search) algorithm had the shortest planning time among the four algorithms, but the paths it plans were unstable and not optimal. The Dynamic Weighted A* algorithm could achieve better path planning results, and with adjustments to the weight values, this algorithm had excellent adaptability. This review provides a reference for further research on path planning algorithms in the process of smart parking.
High altitude is characterized by low oxygen, low pressure, and high radiation. When migrates from low to high altitudes, the body's tissues and organs experience hypoxic stress and will present acoustic adaptatio...
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High altitude is characterized by low oxygen, low pressure, and high radiation. When migrates from low to high altitudes, the body's tissues and organs experience hypoxic stress and will present acoustic adaptation as the protective response. However, the mechanisms of acoustic adaptation at high altitudes remain unclear. In this study, cochlear tissues from Wistar rats were collected at 15, 30, 60, 120, and 180 days after high-altitude migration. Transcriptome sequencing was conducted and DESeq algorithm revealed expression patterns of Differentially Expressed Genes(DEGs) after high altitude migration. Day 60 is a critical stage for cochlear tissue "damage" and "repair" in high-altitude conditions. Transmission Electron Microscopy (TEM) observations of structures also support the findings. A time-series gene co-expression network algorithm was used to investigate gene regulatory patterns and key genes after migration. Immunofluorescence, immunohistochemistry, and qPCR were per-formed for key gene validation and localization. At Day 60, the peak DEG count occurs in rats migrating to high altitude, aligning with the critical phase for cochlear tissue damage and repair at high altitudes. Repair hinges on synaptic plasticity and myelination-linked processes, influencing modules M4 to M6. Module M4's activation gradually diminishes from its peak. However, the 'damage' effect is orchestrated by inflammation-related processes in modules M3 to M5, with module M3's activation also waning. Key gene module M4, pivotal for repair during this pivotal phase, encompasses Sptbn5, Cldn1, Gfra2, and Lims2 as its core genes. Immunohistochemistry reveals Sptbn5's presence in cochlear neurons, hair cells, Schwann cells and stria vascularis tissue. Cldn1 and Gfra2 predominantly localize within the cochlear neuron region. These results may suggest new directions for future research on acoustic acclimatization to high altitude.
At the age of big data, the information changes quickly. How to extract the key information timely seems to be quite important. Therefore, improving the execution speed of bfs algorithm means a lot to the processing o...
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At the age of big data, the information changes quickly. How to extract the key information timely seems to be quite important. Therefore, improving the execution speed of bfs algorithm means a lot to the processing of big data. This paper firstly introduces the implementation flow, features and performance evaluation criteria of the breadth-first search algorithm, and secondly introduce the research status of bfs algorithm based on current CPU platform both at home and abroad. Thirdly, this paper optimizes the algorithm by using the local principle of program, load balancing method and so on. Finally, the comparison of the algorithm performance is shown in this paper: the program optimized in this paper gets good performance and could be popularized further in practice.
The Internet of Vehicles is a new Intelligent Transportation System paradigm and a promising solution to improve conventional Vehicular Ad-hoc NETworks (VANETs) performances. It has received a great deal of attention ...
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The Internet of Vehicles is a new Intelligent Transportation System paradigm and a promising solution to improve conventional Vehicular Ad-hoc NETworks (VANETs) performances. It has received a great deal of attention in recent years, from many researchers. For this reason, several control mechanisms have been proposed for these networks to confront their challenges, such as dynamic topology and the scalability problem due to the high mobility of vehicles and the high number of connected vehicles, respectively. As an important mechanism used in a VANET, clustering has significantly improved the performance in numerous applications. In this regard, the present work proposes a new Multi-hop Clustering Approach over Vehicle-to-Internet called MCA-V2I to improve VANETs' performance. MCA-V2I is based on the reasonable assumption that a vehicle can connect to the Internet via a special infrastructure called a Road Side Unit Gateway. Once connected to the Internet, each vehicle can obtain and share the necessary information about its Multi-hop neighbors to perform the clustering process. This latter is performed using a Breadth-first search (bfs) algorithm for traversing a graph based on a Mobility Rate that is calculated according to mobility metrics. MCA-V2I strengthens clusters' stability through the selection of a Slave Cluster Head in addition to the Master Cluster Head. We evaluate the performances of the proposed scheme using network simulator NS-2 and the VanetMobiSim integrated environment. (C) 2019 Elsevier B.V. All rights reserved.
This study presents an efficient power flow method for analysing distribution systems. The proposed method utilises efficient quadratic-based (QB) models for various components of distribution systems. The power flow ...
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This study presents an efficient power flow method for analysing distribution systems. The proposed method utilises efficient quadratic-based (QB) models for various components of distribution systems. The power flow problem is formulated and solved by a backward/forward sweep (bfs) algorithm. The proposed QBbfs method accommodates multi-phase laterals, different load types, capacitors, distribution transformers, and distributed generation. The advantageous feature of the proposed method is robust convergence characteristics against ill conditions, guaranteeing lower iteration numbers than the existing bfs methods. The proposed method is tested and validated on several distribution test systems. The accuracy is verified using OpenDSS. Comparisons are made with other commonly used bfs methods. The results confirm the effectiveness and robustness of the proposed QBbfs at different conditions.
In this paper, a new viable bandwidth reduction algorithm for reducing the bandwidth of sparse symmetric matrices, is described. The proposed algorithm provides a reliable procedure to reduce the bandwidth and can eas...
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In this paper, a new viable bandwidth reduction algorithm for reducing the bandwidth of sparse symmetric matrices, is described. The proposed algorithm provides a reliable procedure to reduce the bandwidth and can easily be applied to the sparse symmetric matrices of any size. This algorithm is tested on structured graphs and the reduced bandwidth results obtained are compared with the GPS algorithm. The bandwidth obtained by the present method is smaller than or equal to the one obtained by the GPS and standard examples are included to illustrate in detail the proposed algorithm. (C) 2016 Kalasalingam University. Publishing Services by Elsevier B.V.
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