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We consider the problem of causal structure learning from data with missing values, assumed to be drawn from a Gaussian copula model. First, we extend the 'Rank PC' algorithm, designed for Gaussian copula models with purely continuous data (so-called nonparanormal models), to incomplete data by applying rank correlation to pairwise complete observations and replacing the sample size with an effective...
This paper proposes an algorithm that uses predefined weights to create broadcast routes for a WirelessHART network. The network topology is represented by a graph, and the algorithm uses information of the devices present in the network to build the broadcast graph. At each iteration of the algorithm, a device is selected and then added to the broadcast solution graph. A cost function determines...
In this paper, an implicit iterative algorithm is developed to obtain the unique positive definite solution of the generalized algebraic Riccati matrix equation. For this proposed algorithm, there exisits a tuning parameter which can be chosen such that this algorithm achieves better convergence performance. Some convergence results are given for the proposed algorithm. Moreover, an approach is also...
The non-iterative algorithm that reveals the general physical basis of measuring processes and instrumental (computer) computations is proposed and investigated. The algorithm is based on the previously proposed postulate and consists in finding the optimal, locally defined width of the averaging interval. The optimal width of the interval provides the smallest error when measuring or computing the...
This work presents a low-area scalable architecture for the Depth Modelling Mode 1 (DMM-1) encoder of the 3D High Efficiency Video Coding (3D-HEVC) standard, removing the refinement stage. This simplification causes a small BD-rate increase (0.09%) but a significant reduction in memory usage of 30%. The scalable architecture can support different block sizes. Synthesis results for ST 65 nm Standard...
Determinism is a key concern in the certification of software for safety-critical systems. In this paper, we evaluate the role of determinism in certification standards, using airborne software as example. We analyze and speculate how the requirements and underlying concepts related to determinism can be adapted for Machine Learning algorithms.In addition, we systematically identify and analyze a...
In a non-uniform Constraint Satisfaction problem CSP(Γ), where G is a set of relations on a finite set A, the goal is to find an assignment of values to variables subject to constraints imposed on specified sets of variables using the relations from Γ. The Dichotomy Conjecture for the non-uniform CSP states that for every constraint language \Gm the problem CSP(Γ)...
Clustering is a classic topic in optimization with k-means being one of the most fundamental such problems. In the absence of any restrictions on the input, the best known algorithm for k-means with a provable guarantee is a simple local search heuristic yielding an approximation guarantee of 9+≥ilon, a ratio that is known to be tight with respect to such methods.We overcome this barrier...
Active shape model is widely used for facial feature localization. Regarding the traditional ASM algorithm can't describe the object shape precisely, an improved ASM algorithm is proposed. At first, we establish shape model and use PCA (Principle Component Analysis) to transform high-dimensional data to lower dimensions. Another work is to establish local texture model giving sample points with different...
This paper proposes an algorithm for QRS-complex onset detection in single channel ECG signals based on the first differential of the ECG signal and an adaptive baseline estimation. The proposed algorithm was developed and tested using the Physionet QT Database. A 100% detection rate on the onset of the QRS complex, with a mean error±(standard deviation) of −0.48±(11.26) ms was achieved against the...
The report considers the modified Peters algorithm to calculate the Hurst exponent (HE), the essential properties of HE are proved, an example, analysis of a random time series is given.
We design a deterministic polynomial time cn approximation algorithm for the permanent of positive semidefinite matrices where c = e+1 ⋍ 4:84. We write a natural convex relaxation and show that its optimum solution gives a cn approximation of the permanent. We further show that this factor is asymptotically tight by constructing a family of positive semidefinite matrices. We also show that...
Exploration and exploitation are two strategies used to search the problem space in Evolutionary Algorithms (EAs). To significantly increase the performance of these optimization techniques in terms of the solution optimality is to strike the right balance between exploration and exploitation. Firefly is one of the most favored EAs. In this study, we introduce an entire fuzzy system to tune dynamically...
This study rewrote a fractional-order particle swarm optimizer algorithmic equation and used an improved uniform design method (IUDM) to find the best combination for parameters of FPSO. Compared to PSO, FPSO makes a high convergence rate. In the improved FPSO, there are 4 parameters to influence effectiveness. Uniform design is an experimental method and suitable for multiple parameters and multiple...
The weighted k-server problem is a natural generalization of the k-server problem where each server has a different weight. We consider the problem on uniform metrics, which corresponds to a natural generalization of paging. Our main result is a doubly exponential lower bound on the competitive ratio of any deterministic online algorithm, that essentially matches the known upper bounds for the problem...
Quantum-behaved particle swarm optimization (QPSO) is a novel variant of particle swarm optimization (PSO), inspired by quantum mechanics. Compared with traditional PSO, the QPSO algorithm guarantees global convergence and has less number of controlling parameters. However, QPSO is likely to get trapped into a local optimum because of using a single search strategy. This paper proposes a cooperative...
Recently a number of evolutionary multiobjective optimization algorithms have been proposed in the framework of MOEA/D (Multi-Objective Evolutionary Algorithm based on Decomposition). A multiobjective problem is decomposed into multiple single-objective problems using a set of weight vectors in MOEA/D. The number of single-objective problems is the same as the number of weight vectors, which is also...
With the development of cloud computing, storage of whole world started shifting to the cloud. Management and security of such a large data was very difficult, to lower the security issues, Tokenization was developed, but for maintaining the security and safety of the Tokenization servers, there was need of a strong encryption algorithm. This paper presents Next Generation Encryption Algorithm, a...
This paper introduces a new integrated algorithm to achieve the complete coverage path planning (CCPP) task for the mobile robot in a given obstacles-included terrain. The algorithm combines the cellular decomposition approach and the chaotic Standard map together to design the coverage procedure. The cellular decomposition approach decompose the target region into several rectangular feasible sub-regions...
The paper describes the study on the problem of applying classification techniques in medical datasets with a class imbalance. The aim of the research is to identify factors that negatively affect classification results and propose actions that may be taken to improve the performance. To alleviate the impact of uneven and complex class distribution, methods of balancing the datasets are proposed and...
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