Set Of Initial Values Research Articles

Multi-channel non-negative matrix factorization with binary mask initialization for automatic speech recognition

Non-negative Matrix Factorization (NMF) factorizes a non-negative matrix into two non-negative matrices. In the field of acoustics, multichannel expansion has been proposed to consider spatial information for sound source separation. Conventional multi-channel NMF has a difficulty in an initial-value dependency of the separation performance due to local minima. This paper proposes initial value settings by using binary masking based sound source separation whose masks on the time frequency domain are calculated from the time difference of arrival of each source. The proposed method calculates initial spatial correlation matrices using separated sources by binary masking. The music separation experiments confirmed that the separation performance of the proposed method was better than that of the conventional method. In addition, we evaluated initial value settings by using binary masking for automatic speech recognition (ASR) tasks in noisy environments. The ASR experiments confirmed that appropriate initi...

Enhancing the Flexibility of TCP in Heterogeneous Network.

Due to a set of constant initial values, the performance of conventional TCP drops significantly encountering heterogeneous network, showing low throughput and unfairness. This paper firstly demonstrates the chaotic character of TCP congestion control in heterogeneous network, especially the sensitivity to initial value. Inspired by merit of nature-inspired algorithm, a novel structure of TCP congestion control (IPPM, Internet Prey-Predator Model) is proposed. Parameters such as available link capacity(C), congestion window (W) and queue length (Q) are collected by IPPM, which calculates the max value of C according to the interacting relationship existing in C, W and Q, and IPPM initiates the TCP ssthresh with the calculated value. Plenty of simulation results show that the modified TCP can effectively avoid network congestion and packet loss. Besides, it holds high resource utilization, convergence speeds, fairness and stability.

A mathematical model for simulating heat and moisture transfer within porous cotton fabric drying inside the domestic air-vented drum dryer

A mathematical model was developed to describe the processes of coupled heat and mass and momentum transfer occurring in convective drying of 100% porous cotton fabric. In this model, the variation in both air and fabric properties were expressed as a function of temperature and moisture content. The resulting systems of transient non-linear partial differential equations in the space-time domain together with the set of initial values and boundary conditions were numerically solved by utilizing the finite difference method. A series of laboratory drying experiments were performed using a computer-controlled dehydration system, which was developed to obtain data of drying kinetics under varying operating conditions for the validation of the predicted results from the proposed model. The experimental results has shown a very good agreement with the predictions of the model, which indicates that the proposed numerical model can be used with confidence as a tool in optimizing the design and operation of the fabric drying system. A parametric study was performed using the modeling tool has demonstrated the impact of key operational parameters on the drying kinetics, which has significant meaning on improving fabric’s appearance smoothness and decreasing the damage. It is expected that the model can be applied for other fiber products and processes involving similar phenomena.

Quantitative Analysis of [18F]FMISO PET for Tumor Hypoxia: Correlation of Modeling Results with Immunohistochemistry.

Quantitative evaluation of tumor hypoxia based on H-1-(3-[18F]fluoro-2-hydroxypropyl)-2-nitroimidazole ([18F]FMISO) positron emission tomography (PET) can deliver important information for treatment planning in radiotherapy. However, the merits and limitations of different analysis methods in revealing the underlying physiological feature are not clear. This study aimed to assess these quantitative analysis methods with the support of immunohistological data. Sixteen nude mice bearing xenografted human squamous cell carcinomas (FaDu or CAL-33) were scanned using 2-h dynamic [18F]FMISO PET. Tumors were resected and sliced, and the hypoxia marker pimonidazole was immunostained followed by H&E staining. The pimonidazole signal was segmented using a k-means clustering algorithm, and the hypoxic fraction (HF) was calculated as the hypoxic area/viable tumor-tissue-area ratio pooled over three tissue slices from the apical, center, and basal layers. PET images were analyzed using various methods including static analysis [standard uptake value (SUV), tumor-to-blood ratio (T/B), tumor-to-muscle ratio (T/M)] and kinetic modeling (Casciari αk A , irreversible and reversible two-tissue compartment k 3, Thorwarth w A k 3, Patlak K i , Logan V d , Cho K), and correlated with HF. No significant correlation was found for static analysis. A significant correlation between k 3 of the irreversible two-tissue compartment model and HF was observed (r = 0.61, p = 0.01). The correlation between HF and αk A of the Casciari model could be improved through reducing local minima by testing more sets of initial values (r = 0.59, p = 0.02) or by reducing the model complexity by fixing three parameters (r = 0.63, p = 0.0008). With support of immunohistochemistry data, this study shows that various analysis methods for [18F]FMISO PET perform differently for assessment of tumor hypoxia. A better fitting quality does not necessarily mean a higher physiological correlation. Hypoxia PET analysis needs to consider both the mathematical stability and physiological fidelity. Based on the results of this study, preference should be given to the irreversible two-tissue compartment model as well as the Casciari model with reduced parameters.

Finding a good initial configuration of parameters for restricted Boltzmann machine pre-training

Restricted Boltzmann machines (RBMs) have been successfully applied in unsupervised learning and image density-based modeling. The aim of the pre-training step for RBMs is to discover an unknown stationary distribution based on the sample data that has the lowest energy. However, conventional RBM pre-training is sensitive to the initial weights and bias. The selection of initial values in RBM pre-training will directly affect the capabilities and efficiency of the learning process. This paper uses principal component analysis to capture the principal component directions of the training data. A set of initial parameter values for the RBM can be obtained by computing the same reconstruction of the data. Experiments on the Yale and MNIST datasets show that the proposed method not only retains a strong learning ability, but also significantly accelerates the learning speed.

Learning-based EM algorithm for normal-inverse Gaussian mixture model with application to extrasolar planets

ABSTRACTKarlis and Santourian [14] proposed a model-based clustering algorithm, the expectation–maximization (EM) algorithm, to fit the mixture of multivariate normal-inverse Gaussian (NIG) distribution. However, the EM algorithm for the mixture of multivariate NIG requires a set of initial values to begin the iterative process, and the number of components has to be given a priori. In this paper, we present a learning-based EM algorithm: its aim is to overcome the aforementioned weaknesses of Karlis and Santourian's EM algorithm [14]. The proposed learning-based EM algorithm was first inspired by Yang et al. [24]: the process of how they perform self-clustering was then simulated. Numerical experiments showed promising results compared to Karlis and Santourian's EM algorithm. Moreover, the methodology is applicable to the analysis of extrasolar planets. Our analysis provides an understanding of the clustering results in the ln P−ln M and ln P−e spaces, where M is the planetary mass, P is the orbital period and e is orbital eccentricity. Our identified groups interpret two phenomena: (1) the characteristics of two clusters in ln P−ln M space might be related to the tidal and disc interactions (see [9]); and (2) there are two clusters in ln P−e space.

Reliable estimation of anisotropic BRDF

Bidirectional reflectance distribution function (BRDF) estimation is one of the fundamental problems in computer graphics, computer vision and related fields, yet most work relies on conventional local minimisation. Two global optimisation methods for estimating the anisotropic Ward BRDF model and its variants under an L 2-cost function are introduced. The presented algorithms are based on branch-and-bound search which guarantees to provide globally optimal solutions. In contrast to the traditional local optimisation, the methods mentioned here are not affected by the setting of initial BRDF parameter values. Experiments have been carried out to validate the presented methods using anisotropic materials from the UTIA BRDF database.

Some Methods for Determining the Parameters of Mathematical Models of Forest Growth

Some methods for determining the parameters of mathematical models of forest stand dynamics by main forest inventory indices, and a tree height function of tree diameter are developed. A least square method is applied for the parameter estimations. A differential evolution method is used for obtaining a set of initial values of the parameters. For estimation of the parameters of forest growth models a classic method of initial set identification that is specific for such model types is used. For minimizing the time of the initial set identification physical meaning of the parameters and their limits are taken into account. For more precise identification of the initial set the Levenberg - Marquardt algorithm is applied. The proposed optimization methods are programmed in Visual Basic for Applications in the MS Access environment. An interface for choosing of the algorithm parameters and selection of the input data by location or tree species is developed.

An unbiased computation methodology for estimating the probability of informed trading (PIN)

Computational drawbacks regarding the maximum likelihood estimation (MLE) of the widely used PIN (probability of informed trading) measure (Easley et al., 1996) heavily distort the findings of a broad literature. Previously proposed methodologies are not free of computational biases mainly because involved problems are not treated accurately and in unity. Upon revealing the mistreatment in commonly used YZ algorithm (Yan and Zhang, 2012), we suggest a remedy for the problem of boundary solutions. Next, we differentiate and focus on another computational issue: “determination of powerful initial value sets”. We develop a new algorithm that employs cluster analysis to assign multiple powerful sets of initial values for the MLE function. The analyses of the simulated quarterly datasets reflect that applying the algorithm outperforms the existing methods in accuracy. Most notably, none of the mean estimates on PIN and five intermediary parameters contains significant bias at 1% level. Empirical evidence from BIST-30 Index constituents provides consistent and supportive results. In addition to accuracy concerns, consuming one-seventeenth of the time spent in YZ algorithm, the algorithm is highly applicable by researchers and professionals.

Crack identification of beam structures using homotopy continuation algorithm

An approach based on homotopy continuation algorithm is presented to identify the parameters of a cracked beam. Euler–Bernoulli finite beam element with a fully opened crack model is adopted to establish the dynamic equation of the structural system. In the inverse problem, the homotopy equation is derived from minimizing the error between the calculated and the simulated measured acceleration responses. The range of homotopy parameter is divided into a number of divisions. Newton iterative method is employed to estimate the solution at each of these division points. The solution at the last division point corresponds to the homotopy equation matching the objective function. Numerical simulations with a simply supported beam and two-span beam show that the proposed method is very accurate compared to an existing method for both single and multiple cracks identification. The effects of type of excitation, division of the homotopy parameter and measurement noise on the identified results are discussed. It is noted that there is no need for an accurate set of initial values with the proposed approach.

A Novel WSNs Localization Algorithm Based on Artificial Fish Swarm Algorithm

In node localization algorithm in Wireless Sensor Networks (WSNs), the least square method is affected by the measurement error, which leads to position error of the unknown node. In order to solve the problem that the error is too high, we propose a novel WSNs localization algorithm based on artificial fish swarm (AFSA). In the proposed algorithm, artificial fish swarm, which has some advantages such as requirements for the initial value and parameter setting is not high, the optimization speed is quick and so on, is introduced in position process. Firstly, the distances between nodes are obtained by using the TDOA algorithm. Then the geometrical position of the unknown nodes is estimated by the artificial fish swarm optimization algorithm. The simulation results show that compared with the least square method, the algorithm proposed in the paper can reduce the computation amount, get the optimal solution quickly and improve the accuracy of the node without increasing the cost and power consumption. Moreover, the number of beacon nodes is relatively small, so the network cost is reduced to a certain extent.

Формализация определения ошибок при статическом символьном выполнении

This paper is devoted to the formalization of the error criteria for program static analysis, based on symbolic execution. Using the original error criteria of symbolic execution approach in program static analysis leads to an excessive number of false positives. To solve this problem, we propose an alternative definition of the error criteria. Proposed definition reports errors only if they occur on a certain set of input variables. Examples of such sets are the set of values of input variables in which control will pass through a given point of the program, or set of values in which the controls take place along a given path in the control flow graph. This paper discusses the various ways to specify such sets of initial values, including analysis of the final error criteria. We overview algorithms corresponding to the error criteria and prove their correctness. Finally, we consider the practical applications of the given error criteria, which include classification of the warnings generated by static analysis tools; taking into account unknown function contracting, especially preconditions; using the proposed error criteria as formulas for a SMT-solver. The latest application allows to get the precise solution of the particular error criteria, including the error trace.

НЕКЛАССИЧЕСКИЕ УРАВНЕНИЯ МАТЕМАТИЧЕСКОЙ ФИЗИКИ. ЛИНЕЙНЫЕ УРАВНЕНИЯ СОБОЛЕВСКОГО ТИПА ВЫСОКОГО ПОРЯДКА

The article presents the review of authors’ results in the field of non-classical equations of mathematical physics. The theory of Sobolev-type equations of higher order is introduced. The idea is based on generalization of degenerate operator semigroups theory in case of the following equations: decomposition of spaces, splitting of operators' actions, the construction of propagators and phase spaces for a homogeneous equation, as well as the set of valid initial values for the inhomogeneous equation. The author uses a proven phase space technology for solving Sobolev type equations consisting of reduction of a singular equation to a regular one defined on some subspace of initial space. However, unlike the first order equations, there is an extra condition that guarantees the existence of the phase space. There are some examples where the initial conditions should match together if the extra condition can’t be fulfilled to solve the Cauchy problem. The reduction of nonclassical equations of mathematical physics to the initial problems for abstract Sobolev type equations of high order is conducted and justified

A Flow-on-Manifold Formulation of Differential-Algebraic Equations

We derive a flow formulation of differential-algebraic equations (DAEs), implicit differential equations whose dynamics are restricted by algebraic constraints. Using the framework of derivatives arrays and the strangeness-index, we identify the systems that are uniquely solvable on a particular set of initial values and thus possess a flow, the mapping that uniquely relates a given initial value with the solution through this point. The flow allows to study system properties like invariant sets, stability, monotonicity or positivity. For DAEs, the flow further provides insights into the manifold onto which the system is bound to and into the dynamics on this manifold. Using a projection approach to decouple the differential and algebraic components, we give an explicit representation of the flow that is stated in the original coordinate space. This concept allows to study DAEs whose dynamics are restricted to special subsets in the variable space, like a cone or the nonnegative orthant.

Implementation of hybrid harmony search/random search algorithm for single area unit commitment problem

Abstract Harmony Search (HS) is a population based metaheuristics search algorithm inspired from the musical process of searching for a perfect state of harmony and has ability to escape from local minima, does not require differential gradients and initial value setting for the variables and free from divergence and has strong ability on exploring the regions of solution space in a reasonable time. However, it has lower exploitation ability in later period and it easily trapped into local optima and converges very slowly. To improve the exploitation ability of HS algorithm in later stage and provide global optimal solution, a memetic algorithm approach considering Harmony Search and Random Search is presented in the proposed research to solve unit commitment problem of electric power system. The proposed memetic algorithm is tested for IEEE benchmarks consisting of 4, 10, 20 and 40 generating units. The effectiveness of proposed hybrid algorithm is tested for unimodal and multimodal benchmark functions and is compared with others well known evolutionary, heuristics and meta-heuristics search algorithms and it has been found that performance of proposed hybrid algorithm is much better than classical Harmony Search Algorithm and Improved Harmony Search Algorithm as well as recently developed algorithms.

Hybrid HS–random search algorithm considering ensemble and pitch violation for unit commitment problem

Harmony search (HS) is a population-based metaheuristics search algorithm inspired from the musical process of searching for a perfect state of harmony. The pitch of each musical instrument determines the aesthetic quality, just as the fitness function value determines the quality of decision variables. In the musical improvisation process, all players sound pitches within possible range together to make one harmony. If all the pitches make a good harmony, each player stores in his memory that experience and the possibility of making a good harmony is increased next time. Even though HS has the ability to escape from local minima, it does not require differential gradients and initial value setting for the variables, is free from divergence and has strong ability to explore the regions of solution space in a reasonable time. However, it has lower exploitation ability in later period and it easily trapped into local optima and converges very slowly. To improve the exploitation ability of HS algorithm in later stage and provide global optimal solution, a novel and hybrid version of harmony search combined with random search algorithm is presented in the proposed research to solve single-area unit commitment problem of electric power system. The proposed algorithm is tested for standard IEEE systems consisting of 4, 10, 20 and 40 generating units. The effectiveness of proposed hybrid algorithm is compared with other well-known evolutionary, heuristics and metaheuristics search algorithms, and it has been found that performance of proposed algorithm is much better than of classical harmony search algorithm and improved harmony search algorithm as well as recently developed algorithms. Sensitivity analysis on proposed algorithm shows that low value of pitch adjustment rate results in better cost, and parametric test on proposed algorithm shows the rejection of the null hypothesis at the alpha significance level.

Painlevé transcendents and -symmetric Hamiltonians

Unstable separatrix solutions for the first and second Painlevé transcendents are studied both numerically and analytically. For a fixed initial condition, say there is a discrete set of initial slopes that give rise to separatrix solutions. Similarly, for a fixed initial slope, say y’(0) = 0, there is a discrete set of initial values that give rise to separatrix solutions. For Painlevé I the large-n asymptotic behavior of bn is () and that of cn is (), and for Painlevé II the large-n asymptotic behavior of bn is () and that of cn is (). The constants and which are the coefficients in these asymptotic behaviors, are first determined numerically. Then, by using asymptotic methods, they are found analytically by reducing the nonlinear equations to the linear eigenvalue problems associated with the cubic and quartic -symmetric Hamiltonians and

Hybrid harmony search algorithm and fuzzy mechanism for solving congestion management problem in an electricity market

A hybrid technique for solving the congestion management problem in an electricity market based on harmony search algorithm (HAS) and Fuzzy mechanism is presented in this article. This algorithm does not require initial value setting for the variables and does not require differential gradients, thus it can consider discontinuous functions as well as continuous functions. The HAS is a recently developed powerful evolutionary algorithm, inspired by the improvisation process of musicians, for solving single/multiobjective optimization problems. In the proposed technique, each musician plays a note for finding a best harmony all together. Transmission pricing and congestion management are the key elements of a competitive electricity market based on direct access. They also focus of much of the debate concerning alternative approaches to the market design and the implementation of a common carrier electricity system. This article focuses on the tradeoffs between simplicity and economic efficiency in meeting the objectives of a transmission pricing and congestion management scheme. The effectiveness of the proposed technique is applied on 30 and 118 bus IEEE standard power system in comparison with CPSO, PSO‐TVAC, and PSO‐TVIW. The numerical results demonstrate that the proposed technique is better and superior than other compared methods. © 2015 Wiley Periodicals, Inc. Complexity 21: 90–98, 2016

The rvfit Code: A Detailed Adaptive Simulated Annealing Code for Fitting Binaries and Exoplanets Radial Velocities

The fitting of radial velocity curves is a frequent procedure in binary star and exoplanet research. In the majority of cases, the fitting routines need to be fed with a set of initial parameter values and priors from which to begin the computations and their results can be affected by local minima. We present a new code, the rvfit code, for fitting radial velocities of stellar binaries and exoplanets using an adaptive simulated annealing (ASA) global minimization method, which quickly converges to a global solution minimum without the need to provide preliminary parameter values. We show the performance of the code using both synthetic and real datasets: double-lined binaries, single-lined binaries, and exoplanet systems. In all examples, the Keplerian orbital parameters fitted by the rvfit code and their computed uncertainties are compared with literature solutions. Finally, we provide the source code, with a working example and a detailed description of how to use it.

ARSTAN程序和R语言dplR扩展包进行树轮年表分析的比较研究

PDF HTML阅读 XML下载 导出引用 引用提醒 ARSTAN程序和R语言dplR扩展包进行树轮年表分析的比较研究 DOI: 10.5846/stxb201403300597 作者: 作者单位: 北京师范大学资源学院;北京师范大学地表过程与资源生态国家重点实验室,北京师范大学资源学院;北京师范大学地表过程与资源生态国家重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目(41171067) A comparative analysis of ARSTAN and the dplr package of R language in analyses of tree-ring chronologies Author: Affiliation: College of Resources Science and Technology, Beijing Normal University; State Key Laboratory of Earth Surface Process and Re-source Ecology, Beijing Normal University,College of Resources Science and Technology, Beijing Normal University; State Key Laboratory of Earth Surface Process and Re-source Ecology, Beijing Normal University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在树轮年代学领域,ARSTAN是去趋势处理和建立年表方面应用最为广泛的程序,而新兴的R语言dplR扩展包实现了ARSTAN的主要功能,且具有源代码公开、扩展性强等优点,是传统程序的良好补充.使用贺兰山青海云杉(Picea Crassifolia)树轮宽度数据,分析了ARSTAN和dplR进行树轮年代学分析所得结果的差异.结果显示,两种程序计算平均敏感度和一阶自相关系数的平均误差为0.005-0.008,但具有确定的转换关系;两种程序如果使用同种方法去趋势,拟合曲线的参数相近,建立标准年表的平均误差为0.002;拟合自回归模型时差异较大,其中时域上表现为差值年表起始30a内差异显著,在频域上表现为dplR的差值年表保留的低频信息较少;年表统计量计算和公共区间分析中,不同程序计算样本总体代表性和信噪比的差异较大.分析表明,两程序在拟合生长趋势和自回归模型时存在算法上的较大差异,同时年表统计量和公共区间各指标的算法也不尽一致,但存在较为确定的转换关系.对开展不同来源数据的整合分析提出了建议,应明确不同研究中树轮数据的处理过程,在条件允许时使用同一程序或算法重新处理数据,确保结果的可比性. Abstract:Dendrochronology plays an important role in estimating past climatic conditions and predicting future climate change. Detrending and chronology development are the fundamental steps of the study of dendrochronology. ARSTAN is the most popular program used to accomplish this step, and it has played an important role in the development of dendrochronology. However, ARSTAN uses the Fortran programming language, so users find it difficult to understand and revise the algorithm of the source program to meet their needs. An emerging package of the R language named dplR provides similar functions to ARSTAN. R and dplR's source code is fully open to the public; thus, it has numerous users. When scholars from different domains communicate and share the methods and results of dendrochronology, it can help them improve those chronologies. In addition, R and dplR have become a good supplement to traditional analysis software. This paper compares the different dendrochronological analysis algorithms and results provided by ARSTAN and dplR with tree ring width data from Picea crassifolia on Helan Mountain, Ningxia Hui Autonomous Region, China. The results show that the two programs calculated exactly the same means and standard deviations. The mean error of the mean sensitivities (MS) and first-order autocorrelations (AC) were 0.005 and 0.008, respectively, but they had a clear conversion relationship. When using the same method for detrending with both types of software, the parameters of fitting curves were generally equal, and the corresponding standard chronologies developed by the two programs had a mean error of only 0.002. However, the residual chronologies were very different. In the time domain, a significant difference was observed in the residual chronologies in the first 20-30 years. In the frequency domain, the residual chronologies created using ARSTAN showed more low frequency information than that created using dplR. For example, the former showed periods of 32 years with higher power than those of dplR. In the common interval analysis, ARSTAN gave a higher expressed population signal (EPS) and signal-to-noise ratio (SNR) of chronologies than dplR. EPS error was 0.4% and SNR error was 30%-40%. By comparing the algorithms of the two programs, we found that ARSTAN and dplR have different initial value setting rules and nonlinear fitting methods to choose the best fitting model during detrending. When fitting an autoregression model, ARSTAN used a pooled algorithm to find the integral growing pattern and used the same fitting order for different sequences. However, dplR directly used different optimal fitting models for different sequences. In addition, the two programs used different, but similar, formulas for calculating MS, AC, EPS, and SNR. Although the absolute value of the results was different, calculation results of the same program using different data were comparable. In conclusion, this paper offers two suggestions for the meta-analysis of tree ring data from different sources. First, if the source data are available, researchers should choose a single program for statistical calculation, detrending, and common interval analysis based on their needs. Second, if the source data are not available, information related to the chronologies is sufficient; researchers should use only a single program to calculate EPS and SNR chronological statistics to ensure that the results will be comparable. 参考文献 相似文献 引证文献