The restricted EM algorithm under inequality restrictions on the parameters

AbstractOne of the most powerful algorithms for maximum likelihood estimation for many incomplete-data problems is the EM algorithm. The restricted EM algorithm for maximum likelihood estimation under linear restrictions on the parameters has been handled by Kim and Taylor (J. Amer. Statist. Assoc. 430 (1995) 708–716). This paper proposes an EM algorithm for maximum likelihood estimation under inequality restrictions A0β⩾0, where β is the parameter vector in a linear model W=Xβ+ε and ε is an error variable distributed normally with mean zero and a known or unknown variance matrix Σ>0. Some convergence properties of the EM sequence are discussed. Furthermore, we consider the consistency of the restricted EM estimator and a related testing problem

Numeričko istraživanje utjecaja radijalne zračnosti na performanse kompresora s kombiniranim tokom

In mixed-flow compressor, the leakage flow through the tip clearance generates the tip leakage vortex by the interaction with the main flow, and consequently makes the flow in the impeller passage more complex. Different tip clearances generate different intensity of disturbance to main flow. In this paper, numerical analysis is performed using a commercial code to investigate tip clearance effects on main flow. The performance of mixed-flow impeller with four different clearances between impeller and stationary shroud are evaluated and compared with experimental results. The impeller performance curves are obtained for different mass flow parameters with different tip clearances at design speed. The results show that the tip leakage flow strongly interacts with main flow and contributes to total pressure loss and performance reduction. The pressure and performance decrement are approximately linearly proportional to the gap between impeller and stationary shroud. Though the velocity vectors distribution, the computed results reveal that the intensity of the disturbance generated by the leakage flow interacts with the main flow has rather a large influence over efficiency. And the quantity of backflow is minimum when the tip clearance is 0.5 mm, while the 0.75mm tip clearance, by contrast, has a considerable effect on main flow by the interaction with leakage flow.Kod kompresora s kombiniranim tokom, protok rasipanja kroz radijalnu zračnost stvara vršni vrtlog rasipanja zbog interakcije s glavnim tokom te uzročno tok u prolazu rotora čini kompleksnijim. Različite veličine radijalne zračnosti uzrokuju različiti intenzitet smetnje glavnom toku. U ovom članku, numerička analiza provodi se korištenjem komercijalnog koda kako bi se istražio utjecaj radijalne zračnosti na glavni tok. Ocjenjene su performanse rotora kombiniranog toka sa četiri različite radijalne zračnosti između rotora i stacionarnog kućišta te su uspoređene s eksperimentalnim rezultatima. Krivulje performansa rotora dobivene su za različite parametre masenog protoka sa različitim radijalnim zračnostima pri konstrukcijskoj brzini. Rezultati pokazuju kako protok vršnog rasipanja ima snažno međudjelovanje s glavnim tokom i da pridonosi potpunom gubitku tlaka i smanjenju performansa. Smanjenje tlaka i performansi približno je linearno proporcionalno razmaku između rotora i stacionarnog kućišta. Kroz raspored vektora brzine, računalni izračuni otkrivaju kako intenzitet smetnja koje se stvaraju kod međudjelovanja protoka rasipanja i glavnog toka, ima priličan utjecaj na efikasnost. Kvantiteta protutoka je minimalna kad radijalna zračnost iznosi 0.5mm, a usporedno tome, kad je radijalna zračnost 0.75mm, ima značajan utjecaj na glavni tok kroz međudjelovanje s protokom rasipanja

Maximum likelihood estimates of two-locus recombination fractions under some natural inequality restrictions

<p>Abstract</p> <p>Background</p> <p>The goal of linkage analysis is to determine the chromosomal location of the gene(s) for a trait of interest such as a common disease. Three-locus linkage analysis is an important case of multi-locus problems. Solutions can be found analytically for the case of triple backcross mating. However, in the present study of linkage analysis and gene mapping some natural inequality restrictions on parameters have not been considered sufficiently, when the maximum likelihood estimates (MLEs) of the two-locus recombination fractions are calculated.</p> <p>Results</p> <p>In this paper, we present a study of estimating the two-locus recombination fractions for the phase-unknown triple backcross with two offspring in each family in the framework of some natural and necessary parameter restrictions. A restricted expectation-maximization (EM) algorithm, called REM is developed. We also consider some extensions in which the proposed REM can be taken as a unified method.</p> <p>Conclusion</p> <p>Our simulation work suggests that the REM performs well in the estimation of recombination fractions and outperforms current method. We apply the proposed method to a published data set of mouse backcross families.</p

Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis

Tissue characterization has long been an important component of Computer Aided Diagnosis (CAD) systems for automatic lesion detection and further clinical planning. Motivated by the superior performance of deep learning methods on various computer vision problems, there has been increasing work applying deep learning to medical image analysis. However, the development of a robust and reliable deep learning model for computer-aided diagnosis is still highly challenging due to the combination of the high heterogeneity in the medical images and the relative lack of training samples. Specifically, annotation and labeling of the medical images is much more expensive and time-consuming than other applications and often involves manual labor from multiple domain experts. In this work, we propose a multi-stage, self-paced learning framework utilizing a convolutional neural network (CNN) to classify Computed Tomography (CT) image patches. The key contribution of this approach is that we augment the size of training samples by refining the unlabeled instances with a self-paced learning CNN. By implementing the framework on high performance computing servers including the NVIDIA DGX1 machine, we obtained the experimental result, showing that the self-pace boosted network consistently outperformed the original network even with very scarce manual labels. The performance gain indicates that applications with limited training samples such as medical image analysis can benefit from using the proposed framework.Comment: accepted by 8th International Workshop on Machine Learning in Medical Imaging (MLMI 2017

Joint Design of Access and Backhaul in Densely Deployed MmWave Small Cells

With the rapid growth of mobile data traffic, the shortage of radio spectrum resource has become increasingly prominent. Millimeter wave (mmWave) small cells can be densely deployed in macro cells to improve network capacity and spectrum utilization. Such a network architecture is referred to as mmWave heterogeneous cellular networks (HetNets). Compared with the traditional wired backhaul, The integrated access and backhaul (IAB) architecture with wireless backhaul is more flexible and cost-effective for mmWave HetNets. However, the imbalance of throughput between the access and backhaul links will constrain the total system throughput. Consequently, it is necessary to jointly design of radio access and backhaul link. In this paper, we study the joint optimization of user association and backhaul resource allocation in mmWave HetNets, where different mmWave bands are adopted by the access and backhaul links. Considering the non-convex and combinatorial characteristics of the optimization problem and the dynamic nature of the mmWave link, we propose a multi-agent deep reinforcement learning (MADRL) based scheme to maximize the long-term total link throughput of the network. The simulation results show that the scheme can not only adjust user association and backhaul resource allocation strategy according to the dynamics in the access link state, but also effectively improve the link throughput under different system configurations.Comment: 15 page