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Inspired by potential application in power systems and a fully distributed primal-dual method, we investigate how a novel distributed optimization algorithm can be used to solve the dispath response problem in power systems with a distributed manner, whose main target is to minimize the generation cost of the whole network. The problem we study here can be formulated as a kind of optimization problem,...
In this paper, we use the combination of graph theory and consensus algorithm to realize the formation control of nonholonomic wheeled robots. A novel edge-weight function is designed so that the desired formation-shape can be achieved. In addition, the consensus problem is usually solved on the assumption that the robots are modeled as particle model, but this assumption is not suitable when we are...
This paper presents a kinematic model based path planning algorithm for autonomous vehicle. Polynomial parameterization is used to generate the trajectory. All constraints including kinematic constraints and obstacles are represented by polynomial parameters. Using this parameterization method the velocity can be planned simultaneously. Road information is taken into account in the object function...
Identifying influential spreaders in social network is of great theoretical and practical significance. In this paper, we propose an improved weighted LeaderRank algorithm. Instead of considering degree of node only, we also take clustering coefficient into account to depict the weight. Moreover, we change the way of score assignment, which can give more scores to those high-influence nodes. Compared...
In industrial production, the application of the on-line detection and recognition technology of capsule defects is more and more widely. The correct segmentation of the target capsule is essential for the feature extraction and accurate recognition. Because the difference between the oval transparent capsule and background is small and the image exists uneven illumination interference, common methods...
Firefly Algorithm (FA) is a bio-inspired algorithm simulating the flashing behavior of fireflies. In original algorithm, all the fireflies are unisex and only the flashing behavior is simulated. This paper presents a novel hybrid firefly algorithm (HFA) adding mating behavior in original firefly algorithm. The new algorithm is compared with FA and other three well-known bio-inspired algorithms on...
This paper addresses the classical triangle listing problem, which aims at enumerating all the tuples of three vertices connected with each other by edges. This problem has been intensively studied in internal and external memory, but it is still an urgent challenge in distributed environment where multiple machines across the network can be utilized to achieve good performance and scalability. As...
Malaria remains one of the most important public health concerns worldwide. It causes nearly half a million deaths every year, and about 40% of the world's population lives in the endemic regions of malaria. A major hurdle in antimalarial development is our limited understanding of the dynamic cellular networks in the malaria parasite. In this study, by coupling RNA-Seq analysis and network mining...
In the underwater sensor network, the deployment of multiple water surface gateway can effectively improve the network capacity, reduce the network delay and save the energy of underwater sensor nodes. Due to the underwater sensor nodes is easily affected by ocean currents affect which occurred in the position drift, surface gateway deployment locations need regular dynamic optimization and update...
Aiming at issues of load imbalance and low energy efficiency in the existing underwater sensor network clustering algorithm, a novel global optimal clustering algorithm with the low complexity and parallel processing is proposed. The algorithm is based on the basic idea of particle swarm optimization algorithm (PSO). After the binary initial code of the sensor nodes, the particle code is adjusted...
Frequent pattern mining is an important data mining task. Since its introduction, it has drawn attention from many researchers. Consequently, many frequent pattern mining algorithms have been proposed, which include level-wise Apriori-based algorithms, tree-based algorithms, and hyperlinked array structure based algorithms. While these algorithms are popular and benefit from a few advantages, they...
This paper analyzes the shortcomings of traditional multilayer BP neural network in intrusion detection, and gives an optimized multilayer BP neural network algorithm based on matrix, which has good readability, higher recognition rates and the faster program execution speed, etc. On the basis of this, the improved algorithm, combined with principal component analysis and other methods, is applied...
Extracting prior knowledge from previous high quality normal-dose computed tomography (NdCT) data for Bayesian reconstruction of current low-dose CT (LdCT) images has attracted great research interests recently. While most efforts focused on registering the previous NdCT data to the current LdCT reconstruction, this work investigated an alternative strategy by extracting the local structure-specific...
In nuclear magnetic resonance (NMR) quantum computation, the selective control of multiple homonuclear spins is usually slow because their resonance frequencies are very close to each other. To quickly implement the controls against decoherence effects, this brief presents an efficient numerical algorithm for designing minimum-time local transformations in two homonuclear spins. We obtain an accurate...
Reconstructing signals that have a sparse representation has been studied in the recent years. However, most of the work dealing with this problem requires a low-coherent dictionary matrix. This article presents a novel procedure for sparse signal reconstruction with high coherent dictionary by partitioning the dictionary in the preprocessing step and addressing the reconstruction of hierarchical...
In this paper, we consider the problem of distributed detection of sparse signals with a sensor network. Due to practical constraints on communication bandwidth and computational capacity, detection of sparse signals in a distributed manner is more efficient than centralized processing in terms of communication and computation. We develop a greedy algorithm named distributed subspace pursuit (DSP)...
Large scale Social Network Service (SNS) applications use graph as the default data organization model. To discover hidden useful information, data clustering techniques are widely adopted in data analysis tasks. State-of-the-art clustering algorithms are based on distributed programming paradigms such as MapReduce and Bulk Synchronization Parallel (BSP) models. These solutions suffer from heavy data...
Methods for assessing the impact of factors and image-quality metrics for still face images are well-understood. The extension of these factors and quality measures to faces in video has not, however, been explored. We present a specific methodology for carrying out this extension from still to video. Using the Point-and-Shoot Challenge (PaSC) dataset, our study investigates the effect of nine factors...
An active RFID tag design based on nRF24L01 is proposed in this paper. This active RFID tag works in 2.4GHz. The requirements for low power consumption and low system complexity of RFID tags have been well considered. The circuit diagram and the communication protocol are fully described in the paper. Particularly, an anti-collision algorithm has been proposed to improve the effectiveness of thecommunication...
Inexpensive “point-and-shoot” camera technology has combined with social network technology to give the general population a motivation to use face recognition technology. Users expect a lot; they want to snap pictures, shoot videos, upload, and have their friends, family and acquaintances more-or-less automatically recognized. Despite the apparent simplicity of the problem, face recognition in this...
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