Bacterial genomes are simpler than mammalian ones, and yet assembling the former from the data currently generated by high-throughput short-read sequencing machines still results in hundreds of contigs. To improve ass...
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Bacterial genomes are simpler than mammalian ones, and yet assembling the former from the data currently generated by high-throughput short-read sequencing machines still results in hundreds of contigs. To improve assembly quality, recent studies have utilized longer Pacific Biosciences (PacBio) reads or jumping libraries to connect contigs into larger scaffolds or help assemblers resolve ambiguities in repetitive regions of the genome. However, their popularity in contemporary genomic research is still limited by high cost and error rates. In this work, we explore the possibility of improving assemblies by using complete genomes from closely related species/ strains. We present Ragout, a genome rearrangement approach, to address this problem. In contrast with most reference-guided algorithms, where only one reference genome is used, Ragout uses multiple references along with the evolutionary relationship among these references in order to determine the correct order of the contigs. Additionally, Ragout uses the assembly graph and multi-scale synteny blocks to reduce assembly gaps caused by small contigs from the input assembly. In simulations as well as real datasets, we believe that for common bacterial species, where many complete genome sequences from related strains have been available, the current high-throughput short-read sequencing paradigm is sufficient to obtain a single highquality scaffold for each chromosome.
Recently, microblogging is widely studied by the researchers in the domain of the online social network (OSN). How to evaluate the popularities of microblogging users is an important research field, which can be appli...
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Recently, microblogging is widely studied by the researchers in the domain of the online social network (OSN). How to evaluate the popularities of microblogging users is an important research field, which can be applied to commercial advertising, user behavior analysis and information dissemination, and so forth. Previous studies on the evaluation methods cannot effectively solve and accurately evaluate the popularities of the microbloggers. In this paper, we proposed an electromagnetic field theory based model to analyze the popularities of microbloggers. The concept of the source in microblogging field is first put forward, which is based on the concept of source in the electromagnetic field;then, one's microblogging flux is calculated according to his/her behaviors (send or receive feedbacks) on the microblogging platform;finally, we used three methods to calculate one's microblogging flux density, which can represent one's popularity on the microblogging platform. In the experimental work, we evaluated our model using real microblogging data and selected the best one from the three popularity measure methods. We also compared our model with the classic PageRank algorithm;and the results show that our model is more effective and accurate to evaluate the popularities of the microbloggers.
High-throughput AP-MS methods have allowed the identification of many protein complexes. However, most post-processing methods of this type of data have been focused on detection of protein complexes and not its subco...
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High-throughput AP-MS methods have allowed the identification of many protein complexes. However, most post-processing methods of this type of data have been focused on detection of protein complexes and not its subcomplexes. Here, we review the results of some existing methods that may allow subcomplex detection and propose alternative methods in order to detect subcomplexes from AP-MS data. We assessed and drew comparisons between the use of overlapping clustering methods, methods based in the core-attachment model and our own prediction strategy (TRIBAL). The hypothesis behind TRIBAL is that subcomplex-building information may be concealed in the multiple edges generated by an interaction repeated in different contexts in raw data. The CACHET method offered the best results when the evaluation of the predicted subcomplexes was carried out using both the hypergeometric and geometric scores. TRIBAL offered the best performance when using a strict meet-min score.
Soft faults in navigation sensors will lead to the degradation of the accuracy and reliability of integrated navigation system. To solve this problem, a wavelet analysis and signal singularities based soft fault detec...
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Soft faults in navigation sensors will lead to the degradation of the accuracy and reliability of integrated navigation system. To solve this problem, a wavelet analysis and signal singularities based soft fault detection method are given out. To find signal singularities and detect the faults, the modulus maxima values are calculated after the wavelet transform of original signal. By calculating the Lipschitz exponent using the modulus maxima value at the fault point, the fault types are distinguished. Then, a fault-tolerant federated filtering algorithm for the calibration of INS/GPS/DVL integrated navigation system is proposed. Simulations are conducted and results show that sensor soft faults can be detected accurately. By effectively isolating the fault and refactoring information, the accuracy and reliability of navigation system are improved.
A novel multiagent system (MAS) has been proposed to integrate individual UAV (unmanned aerial vehicle) to form a UAV team which can accomplish complex missions with better efficiency and effect. The MAS based UAV tea...
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A novel multiagent system (MAS) has been proposed to integrate individual UAV (unmanned aerial vehicle) to form a UAV team which can accomplish complex missions with better efficiency and effect. The MAS based UAV team control is more able to conquer dynamic situations and enhance the performance of any single UAV. In this paper, the MAS proposed and established combines the reacting and thinking abilities to be an initiative and autonomous hybrid system which can solve missions involving coordinated flight and cooperative operation. The MAS uses BDI model to support its logical perception and to classify the different missions;then the missions will be allocated by utilizing auction mechanism after analyzing dynamic parameters. Prim potential algorithm, particle swarm algorithm, and reallocation mechanism are proposed to realize the rational decomposing and optimal allocation in order to reach the maximum profit. After simulation, the MAS has been proved to be able to promote the success ratio and raise the robustness, while realizing feasibility of coordinated flight and optimality of cooperative mission.
The rock and soil aggregate (RSA) is a special inhomogeneous multiphase geomaterial. It is crucial for stability of engineering by study of RSA mesodamage characteristic. This paper aims at investigating the porosity ...
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The rock and soil aggregate (RSA) is a special inhomogeneous multiphase geomaterial. It is crucial for stability of engineering by study of RSA mesodamage characteristic. This paper aims at investigating the porosity evolution characteristics of RSA by Xray computed tomography (CT) under uniaxial compressive loading. X-ray tomography images were used to extract defects of RSA specimen under different compressive loading. In this paper, we proposed an improved Ostu method to calibrate the beam hardening phenomenon which is caused by X-ray. Also, based on this Ostu method, the outline of rock blocks in RSA is extracted, and the double gray level threshold of soil and rock block is obtained to ensure the reliability of the porosity calculation. We can conclude that the main reason of RSA cracking is the elasticity mismatch between rock blocks and soil, and the porosity evolution of RSA can be divided into four typical stages. These results may be useful to reveal the mesoscopic cracking mechanism and establish mesodamage evolution equation and constitutive relation for RSA.
We propose a systematic framework for Intelligence Video Surveillance System (IVSS) with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorit...
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We propose a systematic framework for Intelligence Video Surveillance System (IVSS) with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. The target detection and tracking is realized by fixed cameras using a moving target detection and tracking algorithm;the PTZ camera is manoeuvred to actively track the target from the tracking results of the static camera. The experiments are carried out using practical surveillance system data, and the experimental results show that the systematic framework and algorithms presented in this paper are efficient.
The three-dimensional Petersen-torus network 3PT is based on the Petersen graph and has recently been proposed as an interconnection network. 3PT is better than the well-known 3D torus and 3D honeycomb mesh in terms o...
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The three-dimensional Petersen-torus network 3PT is based on the Petersen graph and has recently been proposed as an interconnection network. 3PT is better than the well-known 3D torus and 3D honeycomb mesh in terms of diameter and network cost. In this paper, we propose one-to-all and all-to-all broadcasting algorithms for 3PT(l;m;n) under SLA (single-link available) and MLA (multiple-link available) models.
A quantum random walk optimization model and algorithm in network cluster server traffic control and task scheduling is proposed. In order to solve the problem of server load balancing, we research and discuss the dis...
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A quantum random walk optimization model and algorithm in network cluster server traffic control and task scheduling is proposed. In order to solve the problem of server load balancing, we research and discuss the distribution theory of energy field in quantum mechanics and apply it to data clustering. We introduce the method of random walk and illuminate what the quantum random walk is. Here, we mainly research the standard model of one-dimensional quantum random walk. For the data clustering problem of high dimensional space, we can decompose one-dimensional quantum random walk into m one-dimensional quantum random walk. In the end of the paper, we compare the quantum random walk optimization method with GA (genetic algorithm), ACO (ant colony optimization), and SAA (simulated annealing algorithm). In the same time, we prove its validity and rationality by the experiment of analog and simulation.
An enhanced differential evolution based algorithm, named multi-objective differential evolution with simulated annealing algorithm (MODESA), is presented for solving multiobjective optimization problems (MOPs). The p...
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An enhanced differential evolution based algorithm, named multi-objective differential evolution with simulated annealing algorithm (MODESA), is presented for solving multiobjective optimization problems (MOPs). The proposed algorithm utilizes the advantage of simulated annealing for guiding the algorithm to explore more regions of the search space for a better convergence to the true Pareto-optimal front. In the proposed simulated annealing approach, a new acceptance probability computation function based on domination is proposed and some potential solutions are assigned a life cycle to have a priority to be selected entering the next generation. Moreover, it incorporates an efficient diversity maintenance approach, which is used to prune the obtained nondominated solutions for a good distributed Pareto front. The feasibility of the proposed algorithm is investigated on a set of five biobjective and two triobjective optimization problems and the results are compared with three other algorithms. The experimental results illustrate the effectiveness of the proposed algorithm.
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