A profile hidden Markov model (PHMM) is widely used in assigning protein sequences to protein families. In this model, the hidden states only depend on the previous hidden state and observations are independent given hidden states. In other words, in the PHMM, only the information of the left side of a hidden state is considered. However, it makes sense that considering the information of the b...

School choice systems aspire to delink residential location and school assignments by allowing children apply schools outside of their neighborhood. However, programs also affect incentives live in certain neighborhoods, this feedback may undermine the goals choice. We investigate possibility developing a model public narrows range between highest lowest quality compared neighborhood assignment...

Several recent deep neural networks experiments leverage the generalist-specialist paradigm for classification. However, no formal study compared the performance of different clustering algorithms for class assignment. In this paper we perform such a study, suggest slight modifications to the clustering procedures, and propose a novel algorithm designed to optimize the performance of of the spe...

We propose a novel class of deep stochastic predictors for classifying metric data on graphs within the PAC-Bayes risk certification paradigm. Classifiers are realized as linearly parametrized assignment flows with random initial conditions. Building recent literature and data-dependent priors, this approach enables (i) to use bounds training objectives learning posterior distributions hypothes...

The purpose of the study is to identify socio-psychological challenges that influence distance learning education performance be recognized and evaluated in COVID-19 pandemic situation develop planning utilization strategy for smooth high-quality online uninterrupted teaching environment future. A systematic random sampling survey method used collect information from 100 respondents on a ten-po...

a new powerful optimization algorithm inspired from colonizing weeds is utilized to solve the well-known quadratic assignment problem (qap) which is of application in a large number of practical areas such as plant layout, machinery layout and so on. a set of reference numerical problems from qaplib is taken in order to evaluate the efficiency of the algorithm compared with the previous ones wh...

Consider a set-classification task where c objects must be labelled simultaneously in c classes, knowing that there is only one object coming from each class (full-class set). Such problems may occur in automatic attendance registration systems, simultaneous tracking of fast moving objects and more. A Bayes-optimal solution to the full-class set classification problem is proposed using a single...

In this paper, an analytical approach is used for assembly line rebalancing and worker assignment for single and mixed-model assembly lines based on a heuristic-simulation algorithm. This approach helps to managers to select a better marketing strategy when different combinations of demands are suitable.Furthermore, they can use it as a guideline to know which worker assignment is better for ea...